Change search
Refine search result
123 1 - 50 of 104
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Abdel-Rahman, Suzan
    et al.
    Department of Demography and Biostatistics, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt.
    Awwad, Fuad A.
    Department of Quantitative Analysis, College of Business Administration, King Saud University, P.O. Box 71115, Riyadh, 11587, Saudi Arabia.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Abonazel, Mohamed R.
    Department of Applied Statistics and Econometrics, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt.
    New evidence of gender inequality during COVID-19 outbreak in the Middle East and North Africa2023In: Heliyon, E-ISSN 2405-8440, Vol. 9, no 7, article id e17705Article in journal (Refereed)
    Abstract [en]

    The COVID-19 pandemic has significantly altered employment and income distribution, impacting women and men differently. This study investigates the negative effects of COVID-19 on the labour market, focusing on the gender gap in five countries in the Middle East and North Africa (MENA) region. The study indicates whether women are more susceptible to losing their jobs, either temporarily or permanently, switching their primary occupation, and experiencing decreased working hours and income compared to men during the COVID-19 outbreak. The study utilizes a multivariate Probit model to estimate the relationship between gender and adverse labour outcomes controlling for correlations among outcomes. Data are obtained from the Combined COVID-19 MENA Monitor Household Survey, covering Egypt, Tunisia, Morocco, Jordan, and Sudan. The findings of this study offer empirical evidence of the gender gap in labour market outcomes during the pandemic. Women are more likely than men to experience negative work outcomes, such as permanent job loss and change in their main job. The increased childcare and housework responsibilities have significantly impacted women's labour market outcomes during the pandemic. However, the availability of telework has reduced the likelihood of job loss among women. The study's results contribute to a better understanding of the impact of COVID-19 on gender inequality in understudied MENA countries. Mitigation policies should focus on supporting vulnerable women who have experienced disproportionate negative effects of COVID-19.

  • 2.
    Akram, Muhammad Nauman
    et al.
    Department of Statistics, University of Sargodha, Sargodha, Pakistan.
    Amin, Muhammad
    Department of Statistics, University of Sargodha, Sargodha, Pakistan.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    A new Liu-type estimator for the Inverse Gaussian Regression Model2020In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 90, no 7, p. 1153-1172Article in journal (Refereed)
    Abstract [en]

    The Inverse Gaussian Regression Model (IGRM) is used when the response variable is positively skewed and follows the inverse Gaussian distribution. In this article, we propose a Liu-type estimator to combat multicollinearity in the IGRM. The variance of the Maximum Likelihood Estimator (MLE) is overstated due to the presence of severe multicollinearity. Moreover, some estimation methods are suggested to estimate the optimal value of the shrinkage parameter. The performance of the proposed estimator is compared with the MLE and some other existing estimators in the sense of mean squared error through Monte Carlo simulation and different real-life applications. Under certain conditions, it is concluded that the proposed estimator is superior to the MLE, ridge, and Liu estimator.

  • 3.
    Alheety, M. I.
    et al.
    Department of Mathematics, College of Education for Pure Sciences, University of Anbar, Ramadi, Iraq.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Kibria, B. M. Golam
    Department of Mathematics and Statistics, Florida International University, Miami, FL, United States.
    A new kind of stochastic restricted biased estimator for logistic regression model2021In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 48, no 9, p. 1559-1578Article in journal (Refereed)
    Abstract [en]

    In the logistic regression model, the variance of the maximum likelihood estimator is inflated and unstable when the multicollinearity exists in the data. There are several methods available in literature to overcome this problem. We propose a new stochastic restricted biased estimator. We study the statistical properties of the proposed estimator and compare its performance with some existing estimators in the sense of scalar mean squared criterion. An example and a simulation study are provided to illustrate the performance of the proposed estimator. 

  • 4.
    Alheety, Mustafa I.
    et al.
    Univ Anbar, Dept Math, Coll Educ Pure Sci, Ramadi, Iraq..
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Kibria, B. M. Golam
    Florida Int Univ, Dept Math & Stat, Miami, FL 33199 USA..
    Modifed almost unbiased two-parameter estimator for the Poisson regression model with an application to accident data2021In: SORT - Statistics and Operations Research Transactions, ISSN 1696-2281, E-ISSN 2013-8830, Vol. 45, no 2, p. 121-142Article in journal (Refereed)
    Abstract [en]

    Due to the large amount of accidents negatively affecting the wellbeing of the survivors and their families, a substantial amount of research is conducted to determine the causes of road accidents. This type of data come in the form of non-negative integers and may be modelled using the Poisson regression model. Unfortunately, the commonly used maximum likelihood estimator is unstable when the explanatory variables of the Poisson regression model are highly correlated. Therefore, this paper proposes a new almost unbiased estimator which reduces the instability of the maximum likelihood estimator and at the same time produce smaller mean squared error. We study the sta-tistical properties of the proposed estimator and a simulation study has been conducted to compare the performance of the estimators in the smaller mean squared error sense. Finally, Swedish traffic fatality data are analyzed to show the beneft of the proposed method.

  • 5.
    Ali, Abdul Aziz
    et al.
    Linnéuniversitetet, Institutionen för nationalekonomi och statistik (NS).
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Shukur, Ghazi
    Linnéuniversitetet, Institutionen för nationalekonomi och statistik (NS).
    A wavelet-based variance ratio unit root test for a system of equations2020In: Studies in Nonlinear Dynamics and Econometrics, ISSN 1081-1826, E-ISSN 1558-3708, Vol. 24, no 3, p. 1-16, article id 20180005Article in journal (Refereed)
    Abstract [en]

    In this paper, we suggest a unit root test for a system of equations using a spectral variance decomposition method based on the Maximal Overlap Discrete Wavelet Transform. We obtain the limiting distribution of the test statistic and study its small sample properties using Monte Carlo simulations. We find that, for multiple time series of small lengths, the wavelet-based method is robust to size distortions in the presence of cross-sectional dependence. The wavelet-based test is also more powerful than the Cross-sectionally Augmented Im et al. unit root test (Pesaran, M. H. 2007. "A Simple Panel Unit Root Test in the Presence of Cross-section Dependence." Journal of Applied Econometrics 22 (2): 265-312.) for time series with between 20 and 100 observations, using systems of 5 and 10 equations. We demonstrate the usefulness of the test through an application on evaluating the Purchasing Power Parity theory for the Group of 7 countries and find support for the theory, whereas the test by Pesaran (Pesaran, M. H. 2007. "A Simple Panel Unit Root Test in the Presence of Cross-section Dependence." Journal of Applied Econometrics 22 (2): 265-312.) finds no such support. 

  • 6.
    Alka, Singh
    et al.
    Banasthali Univ, Dept Math & Stat, Jaipur 304022, Rajasthan, India..
    Rai, Piyush Kant
    Banaras Hindu Univ, Dept Stat, Varanasi 221005, Uttar Pradesh, India..
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Two-Step Calibration Estimator with Double Use of Auxiliary Variable: Method and Application2022In: Journal of the Iranian Statistical Society, ISSN 1726-4057, Vol. 21, no 1, p. 37-54Article in journal (Refereed)
    Abstract [en]

    This article introduces a two-step calibration technique for the inverse relationship between study variable and auxiliary variable along with the double use of the auxiliary variable. In the first step, the calibration weights and design weights are set proportional to each other for a given sample. While in the second step, the constant of proportionality is to be obtained on the basis of some different objectives of the investigation viz. bias reduction or minimum Mean Squared Error (MSE) of the proposed estimator. Many estimators based on inverse relationship between x and y have been already developed and are considered to be special cases of the proposed estimator. Properties of the proposed estimator is discussed in details. Moreover, a simulation study has also been conducted to compare the performance of the proposed estimator under Simple Random Sampling Without Replacement (SRSWOR) and Lahiri-Midzuno (L-M) sampling design in terms of percent relative bias and MSE. The benefits of two-step calibration estimator are also demonstrated using real life data.

  • 7.
    Almasri, Abdullah
    et al.
    Department of Economics and Statistics, Karlstad University, Karlstad, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Economics and Statistics, Göteborg University, Göteborg, Sweden.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Economics and Statistics, Linnaeus University, Växjö, Sweden.
    A wavelet-based panel unit-root test in the presence of an unknown structural break and cross-sectional dependency, with an application of purchasing power parity theory in developing countries2017In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 49, no 21, p. 2096-2105Article in journal (Refereed)
    Abstract [en]

    This article introduces two different non-parametric wavelet-based panel unit-root tests in the presence of unknown structural breaks and cross-sectional dependencies in the data. These tests are compared with a previously suggested non-parametric wavelet test, the parameteric Im-Pesaran and Shin (IPS) test and a Wald type of test. The results from the Monte Carlo simulations clearly show that the new wavelet-ratio tests are superior to the traditional tests both in terms of size and power in panel unit-root tests because of its robustness to cross-section dependency and structural breaks. Based on an empirical Central American panel application, we can, in contrast to previous research (where bias due to structural breaks is simply disregarded), find strong, clear-cut support for purchasing power parity (PPP) in this developing region.

  • 8.
    Amin, Muhammad
    et al.
    Department of Statistics, University of Sargodha, Sargodha, Punjab, Pakistan.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Afzal, Saima
    Department of Statistics, Bahauddin Zakariya University, Multan, Punjab, Pakistan.
    Naveed, Khalid
    Department of Statistics, Bahauddin Zakariya University, Multan, Punjab, Pakistan.
    New ridge estimators in the inverse Gaussian regression: Monte Carlo simulation and application to chemical data2022In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 51, no 10, p. 6170-6187Article in journal (Refereed)
    Abstract [en]

    In numerous application areas, when the response variable is continuous, positively skewed, and well fitted to the inverse Gaussian distribution, the inverse Gaussian regression model (IGRM) is an effective approach in such scenarios. The problem of multicollinearity is very common in several application areas like chemometrics, biology, finance, and so forth. The effects of multicollinearity can be reduced using the ridge estimator. This research proposes new ridge estimators to address the issue of multicollinearity in the IGRM. The performance of the new estimators is compared with the maximum likelihood estimator and some other existing estimators. The mean square error is used as a performance evaluation criterion. A Monte Carlo simulation study is conducted to assess the performance of the new ridge estimators based on the minimum mean square error criterion. The Monte Carlo simulation results show that the performance of the proposed estimators is better than the available methods. The comparison of proposed ridge estimators is also evaluated using two real chemometrics applications. The results of Monte Carlo simulation and real applications confirmed the superiority of the proposed ridge estimators to other competitor methods.

  • 9.
    Amin, Muhammad
    et al.
    Department of Statistics, University of Sargodha, Sargodha, Pakistan.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Statistics and Computer Science, University of Veterinary and Animal Sciences, Lahore, Pakistan.
    Amanullah, Muhammad
    Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.
    Performance of Asar and Genç and Huang and Yang’s Two-Parameter Estimation Methods for the Gamma Regression Model2019In: Iranian Journal of Science and Technology, Transactions A: Science, ISSN 1028-6276, Vol. 43, no 6, p. 2951-2963Article in journal (Refereed)
    Abstract [en]

    This study assesses the performance of two-parameter estimation methods to combat multicollinearity in the Gamma regression model. We derived optimal values for two-parameter estimation methods in the Gamma regression model. Furthermore, we proposed some estimation methods to estimate the shrinkage parameters and these methods improve the efficiency of the two-parameter estimator. We compare the performance of these estimators by means of Monte Carlo simulation study where the mean squared error (MSE) is considered as a performance criterion. Finally, consider a reaction rate data to evaluate the performance of the estimators. The simulation and numerical example results showed that the two-parameter biased estimators have smaller MSE than the maximum likelihood estimator under certain conditions.

  • 10.
    Amin, Muhammad
    et al.
    Department of Statistics, University of Sargodha, Sargodha, Pakistan.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Yasin, Ahad
    Department of Statistics, University of Sargodha, Sargodha, Pakistan.
    Amanullah, Muhammad
    Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.
    Almost unbiased ridge estimator in the gamma regression model2022In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 51, no 7, p. 3830-3850Article in journal (Refereed)
    Abstract [en]

    This article introduces the almost unbiased gamma ridge regression estimator (AUGRRE) estimator based on the gamma ridge regression estimator (GRRE). Furthermore, some shrinkage parameters are proposed for the AUGRRE. The performance of the AUGRRE by using different shrinkage parameters is compared with the existing GRRE and maximum likelihood estimator. A Monte Carlo simulation is carried out to assess the performance of the estimators where the bias and mean squared error performance criteria are used. We also used a real-life dataset to demonstrate the benefit of the proposed estimators. The simulation and real-life example results show the superiority of AUGRRE over the GRRE and the maximum likelihood estimator for the gamma regression model with collinear explanatory variables.

  • 11.
    Amin, Muhammad
    et al.
    Department of Statistics, University of Sargodha, Sargodha, Pakistan.
    Ullah, Muhammad Aman
    Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Diagnostic techniques for the inverse Gaussian regression model2022In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 51, no 8, p. 2552-2564Article in journal (Refereed)
    Abstract [en]

    In this article, we propose some diagnostic techniques for the inverse Gaussian regression model (IGRM), which are appropriate for modeling the response variable that undertakes positively skewed continuous dataset. Moreover, two new diagnostic methods are mainly proposed for the IGRM, which named as covariance ratio (CVR) and Welsch?s distance (WD). The comparison of our proposed methods of influence diagnostics with the existing approaches has been made through Monte Carlo simulation under different factors. In addition, the benefit of the proposed methods is assessed using a real application. Based on the simulation and empirical application results, we observed that the performance of the proposed method is better than the existing methods for detection of influential observations.

  • 12.
    Amjad, M.
    et al.
    University of Veterinary and Animal Sciences, Lahore, Pakistan.
    Saleem, M. H.
    University of Veterinary and Animal Sciences, Lahore, Pakistan.
    Iqbal, M. Z.
    University of Veterinary and Animal Sciences, Lahore, Pakistan.
    Hassan, A.
    Department of Veterinary Surgery and Pet Sciences, Faculty of Veterinary Science, University of Veterinary and Animal Sciences, Lahore, Pakistan.
    Jabbar, A.
    University of Veterinary and Animal Sciences, Lahore, Pakistan.
    Ashraf, M.
    University of Veterinary and Animal Sciences, Lahore, Pakistan.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Ullah, A.
    University of Veterinary and Animal Sciences, Lahore, Pakistan.
    Tolba, M. M.
    Biomedical Informatics and Biotechnology Group, Informatics and Systems Department, Division of Engineering Research, National Research Centre, Cairo, Egypt.
    Nasser, H. A.
    Microbiology and Public Health Department. Faculty of Pharmacy, Helipolis, University, Egypt.
    Naaz, S.
    Livestock and Dairy Development Department Punjab Pakistan.
    Ahmad, I.
    Department of Veterinary Clinical Sciences, University of Poonch Rawalakot Azad Kashmir, Pakistan.
    Efficacy of Quinapyramine Sulphate, Isometamedium Chloride and Diminazene Aceturate For Treatment of Surra2022In: Journal of Animal and Plant Sciences, ISSN 1018-7081, Vol. 32, no 3, p. 663-669Article in journal (Refereed)
    Abstract [en]

    Trypanosomiasis (Surra) is a parasitic and zoonotic disease caused by Trypanosoama evansi, transmitted by insect vectors Tabanus and Stomoxys mechanically. The aim of the present study was to determine the therapeutic efficacy of various trypanosidal drugs against trypanosomiasis in Thoroughbred horses. Horses having clinical signs of trypanosomiasis were diagnosed through blood smear through a microscope were selected for this study. The infected horses were divided into three experimental groups for therapeutic trials. Animals in group A were treated with a single dose of quinapyramine sulphate @ 3000mg/ml per 50/kg body weight; group B was treated with a single dose of isometamedium chloride Hydrochloride@ 0.5 mg/2.5 ml of 1% solution per 50/kg body weight; group C was treated with a single dose of diminazene aceturate@ 2360 mg/15 ml per 100/kg. Results revealed that significant (P<0.0001) de cline in the values of erythrocyte counts (RBC), hemoglobin concentration (Hb), packed cell volume (PCV), platelets (PLT) and a significant (P<0.0001) increase in white blood cells (WBC), granulocytes, and monocytes in infected horses as compared to healthy ones. Therapeutic trials indicated that quinapyramine sulphate that showed 100% efficacy at 21th days had significantly higher than isometamedium chloride and diminazene aceturate (95.83 and 75% efficacy, respectively). The hematological parameters of recovered horses were significantly restored to normal values on day 21 after treatment. It is concluded that quinapyramine sulphate is the drug of choice against trypanosomiasis in Thoroughbred horses.

  • 13.
    Canabarro, Ana P. F.
    et al.
    Department of Global Public Health, Karolinska Institutet, Widerströmska Huset, Stockholm, Sweden.
    Eriksson, Malin
    Department of Social Work, Umeå University, Umeå, Sweden.
    Nielsen, Anna
    Department of Global Public Health, Karolinska Institutet, Widerströmska Huset, Stockholm, Sweden.
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Global Public Health, Karolinska Institutet, Widerströmska Huset, Stockholm, Sweden.
    Salazar, Mariano
    Department of Global Public Health, Karolinska Institutet, Widerströmska Huset, Stockholm, Sweden.
    Cognitive social capital as a health-enabling factor for STI testing among young men in Stockholm, Sweden: A cross-sectional population-based study2023In: Heliyon, E-ISSN 2405-8440, Vol. 9, no 10, article id e20812Article in journal (Refereed)
    Abstract [en]

    Objective: To assess whether different forms of cognitive social capital increased the relative probability of testing for sexually transmitted infections (STIs) among young men living in Stockholm, Sweden.

    Methods: A population-based cross-sectional study was conducted in 2017 with men aged 20–29 years living in Stockholm County, Sweden (n = 523). The main outcome was STI testing patterns (never tested, tested only within a 12-month period, tested only beyond a 12-month period, repeatedly tested). The main exposure were two forms of cognitive social capital: social support (having received help, having someone to share inner feelings with) and institutionalized trust (in school, healthcare, media). Data were analyzed using weighted multivariable multinomial logistic regression to obtain adjusted weighted relative probability ratio (aRPR).

    Results: After adjusting for confounding factors, receiving help (aRPR: 5.2, 95% CI: 1.7–16.2) and having someone to share inner feelings with (aRPR: 3.1, 95% CI: 1.2–7.7) increased the relative probabilities of young men testing for STIs, but only for those testing beyond a 12-month period. Trust in media increased the relative probability of STI testing for those testing only within a 12-month period (aRPR: 2.6, 95% CI: 1.1–6.1) and for those testing repeatedly (aRPR: 3.6, 95% CI: 1.5–8.8).

    Conclusion: Young men in Stockholm County exhibit distinct STI testing patterns. Social support and trust in media were factors that increased the probability of being tested for STIs, with this effect varying according to the young men's STI testing pattern. Further studies are required to explore how trust in media might promote STI testing in this population.

  • 14.
    Duras, Toni
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    A comparison of two estimation methods for common principal components2019In: Communications in statistics. Case studies, data analysis and applications, E-ISSN 2373-7484, Vol. 5, no 4, p. 366-393Article in journal (Refereed)
    Abstract [en]

    Common principal components (CPCs) are often estimated using maximum likelihood estimation through an algorithm called the Flury–Gautschi (FG) Algorithm. Krzanowski proposed a simpler estimation method via a principal component analysis of a weighted sum of the sample covariance matrices. These methods are compared for real-world datasets and in a Monte Carlo simulation. The real-world data is used to compare the selection of a common eigenvector model and the estimated coefficients. The simulation study investigates how the accuracy of the methods is affected by autocorrelation, the number of covariance matrices, dimensions, and sample sizes for multivariate normal and chi-square distributed data. The findings in this article support the use of Krzanowski’s method in situations where the CPC assumption is appropriate. 

  • 15.
    Duras, Toni
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    An extension of the fixed effects principal component model to a common principal component environmentManuscript (preprint) (Other academic)
  • 16.
    Duras, Toni
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Applications of common principal components in multivariate and high-dimensional analysis2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis consists of four papers, all exploring some aspect of common principal component analysis (CPCA), the generalization of PCA to multiple groups. The basic assumption of the CPC model is that the space spanned by the eigenvectors is identical across several groups, whereas eigenvalues associated with the eigenvectors can vary. CPCA is used in essentially the same areas and applications as PCA.

    The first paper compares the performance of the maximum likelihood and Krzanowski’s estimators of the CPC model for two real-world datasets and in a Monte Carlo simulation study. The simplicity and intuition of Krzanowski's estimator and the findings in this paper support and promote the use of this estimator for CPC models over the maximum likelihood estimator.

    Paper number two uses CPCA as a tool for imposing restrictions on system-wise regression models. The paper contributes to the field by proposing a variety of explicit estimators, deriving their properties and identifying the appropriate amount of smoothing that should be imposed on the estimator. 

    In the third paper, a generalization of the fixed effects PCA model to multiple populations in a CPC environment is proposed. The model includes mainly geometrical, rather than probabilistic, assumptions, and is designed to account for any possible prior information about the noise in the data to yield better estimates, obtained by minimizing a least squares criterion with respect to a specified metric.

    The fourth paper survey some properties of the orthogonal group and the associated Haar measure on it. It is demonstrated how seemingly abstract results contribute to applied statistics and, in particular, to PCA.

    Download full text (pdf)
    Kappa
    Download (png)
    Cover
  • 17.
    Duras, Toni
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Aspects of common principal components2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The focus of this thesis is the common principal component (CPC) model, the generalization of principal components to several populations. Common principal components refer to a group of multidimensional datasets such that their inner products share the same eigenvectors and are therefore simultaneously diagonalized by a common decorrelator matrix. Common principal component analysis is essentially applied in the same areas and analysis as its one-population counterpart. The generalization to multiple populations comes at the cost of being more mathematically involved, and many problems in the area remains to be solved.

    This thesis consists of three individual papers and an introduction chapter.In the first paper, the performance of two different estimation methods of the CPC model is compared for two real-world datasets and in a Monte Carlo simulation study. The second papers show that the orthogonal group and the Haar measure on this group plays an important role in PCA, both in single- and multi-population principal component analysis. The last paper considers using common principal component analysis as a tool for imposing restrictions on system-wise regression models. When the exogenous variables of a multi-dimensional model share common principal components, then each of the marginal models in the system is, up to their eigenvalues, identical. They henceform a class of regression models situated in between the classical seemingly unrelated regressions, where each set of explanatory variables is unique, and multivariate regression, where each marginal model shares the same common set of regressors.

    Download full text (pdf)
    Kappa
  • 18.
    Duras, Toni
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    The fixed effects PCA model in a common principal component environment2022In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 51, no 6, p. 1653-1673Article in journal (Refereed)
    Abstract [en]

    This paper explores multivariate data using principal component analysis (PCA). Traditionally, two different approaches to PCA have been considered, an algebraic descriptive one and a probabilistic one. Here, a third type of PCA approach, lying somewhere between the two traditional approaches, called the fixed effects PCA model, is considered. This model includes mainly geometrical, rather than probabilistic assumptions, such as the optimal choice of dimensionality and metric. The model is designed to account for any possible prior information about the noise in the data to yield better estimates. Parameters are estimated by minimizing a least-squares criterion with respect to a specified metric. A suggestion of how the fixed effects PCA estimates can be improved in a common principal component (CPC) environment is made. If the CPC assumption is fulfilled, then the fixed effects PCA model can consider more information by incorporating common principal component analysis (CPCA) theory into the estimation procedure. 

  • 19.
    Duras, Toni
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Holgersson, Thomas
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    A small excursion on the Haar measure on OpManuscript (preprint) (Other academic)
  • 20.
    Duras, Toni
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Holgersson, Thomas
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Common principal components with applications in regressionManuscript (preprint) (Other academic)
  • 21.
    Duras, Toni
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Javed, F.
    Lund University, Lund, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE).
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Söderberg, M.
    Griffith University, Brisbane, Australia.
    Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution data2023In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 120, article id 106621Article in journal (Refereed)
    Abstract [en]

    Agencies that regulate electricity providers often apply nonparametric data envelopment analysis (DEA) to assess the relative efficiency of each firm. The reliability and validity of DEA are contingent upon selecting relevant input variables. In the era of big (wide) data, the assumptions of traditional variable selection techniques are often violated due to challenges related to high-dimensional data and their standard empirical properties. Currently, regulators have access to a large number of potential input variables. Therefore, our aim is to introduce new machine learning methods for regulators of the energy market. We also propose a new two-step analytical approach where, in the first step, the machine learning-based adaptive least absolute shrinkage and selection operator (ALASSO) is used to select variables and, in the second step, selected variables are used in a DEA model. In contrast to previous research, we find, by using a more realistic data-generating process common for production functions (i.e., Cobb–Douglas and Translog), that the performance of different machine learning techniques differs substantially in different empirically relevant situations. Simulations also reveal that the ALASSO is superior to other machine learning and regression-based methods when the collinearity is low or moderate. However, in situations of multicollinearity, the LASSO approach exhibits the best performance. We also use real data from the Swedish electricity distribution market to illustrate the empirical relevance of selecting the most appropriate variable selection method.

  • 22.
    Elinder, Liselotte S.
    et al.
    Department of Public Health Sciences, Karolinska Institutet, Solna, Sweden.
    Sundblom, Elinor
    Department of Public Health Sciences, Karolinska Institutet, Solna, Sweden.
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Public Health Sciences, Karolinska Institutet, Solna, Sweden.
    Bergström, Helena
    Department of Public Health Sciences, Karolinska Institutet, Solna, Sweden.
    Effect and process evaluation of a structural health intervention in community residences for adults with intellectual disabilities2018In: Journal of Policy and Practice in Intellectual Disabilities, ISSN 1741-1122, E-ISSN 1741-1130, Vol. 15, no 4, p. 319-328Article in journal (Refereed)
    Abstract [en]

    Interventions to improve health among adults with intellectual disabilities (ID) living in community residences are needed as unhealthy behaviors, obesity, and chronic diseases are more common in this group than in the general population. This study evaluated effectiveness of a structural health intervention, a study circle for paid carers aiming to improve health promotion work routines for residents, and explored barriers and facilitators in the implementation process. A quasi-experimental design was used. Eight municipalities with 84 community residences agreed to participate with 70 of these completing the study. A 26-item questionnaire was used regarding staff work routines in three domains (general health promotion, food and meals, physical activity) and a total score to evaluate effectiveness. An inductive qualitative method was used to explore barriers and facilitators in the implementation process. The intervention group (n = 42 residences) improved their health promoting work routines significantly more than the comparison group (n = 28 residences) in the domains of general health promotion (p =.05), physical activity (p =.02), and for the total score (p =.002), but no significant change was found in the food and meal domain (p =.11). Regarding barriers and facilitators in the implementation process, a “Need for a supportive structure and key persons with a mandate to act,” was identified as an overarching theme. Barriers and facilitators were identified within four categories: (1) characteristics of the study circle, (2) staff capacity, (3) organizational capacity, and (4) external support. This study provides evidence that a structural intervention targeting staff in community residences for people with ID can improve health promoting work routines and that the results might be generalizable. If disseminated on a wider scale, this intervention has the potential of improving health and preventing obesity and other chronic diseases in adults with ID. 

  • 23.
    Florida, Richard
    et al.
    Rotman School of Management, University of Toronto.
    Mellander, Charlotta
    Jönköping University, Jönköping International Business School, JIBS, The Prosperity Institute of Scandinavia (PIS). Jönköping University, Jönköping International Business School, JIBS, Economics.
    Holgersson, Thomas
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Up in the air: The role of airports for regional economic development2015In: The annals of regional science, ISSN 0570-1864, E-ISSN 1432-0592, Vol. 54, no 1, p. 197-214Article in journal (Refereed)
    Abstract [en]

    Our research examines the role of airports in regional development. Specifically, we examine two things: (1) the factors associated with whether or not a metro will have an airport, and (2) the effect of airport activities on regional economic development. Based on multiple regression analysis for U.S. metros, our research generates four key findings. First, airports are more likely to be located in larger metros with higher shares of cultural workers and warmer winters. Second, airports add significantly to regional development measured as economic output per capita. Third, the effect of airports on regional development occurs through two channels—their capacity to move both people and cargo, with the former being somewhat more important. Fourth, the impact of airports on regional development varies with their size and scale.

    Download full text (pdf)
    fulltext
  • 24.
    Habimana, Olivier
    et al.
    Rwanda Academy of Sciences, Kigali, Rwanda.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    A wavelet-based approach for Johansen’s likelihood ratio test for cointegration in the presence of measurement errors: An application to CO2 emissions and real GDP data2021In: Communications in Statistics Case Studies Data Analysis and Applications, ISSN 2373-7484, Vol. 7, no 2, p. 128-145Article in journal (Refereed)
    Abstract [en]

    We suggest a wavelet filtering technique as a remedy to the problem of measurement errors when testing for cointegration using Johansen’s (1988) likelihood ratio test. Measurement errors, which more or less are always present in empirical economic data, essentially indicates that the variable of interest (the true signal) is contaminated with noise, which may induce biased and inconsistent estimates and erroneous inference. Our Monte Carlo experiments demonstrate that measurement errors distort the statistical size of Johansen’s cointegration test in finite samples; the test is significantly oversized. A contribution and major finding of this article is that the proposed wavelet-based technique significantly improves the statistical size of the traditional Johansen test in small and medium sized samples. Since Johansen’s test is a standard cointegration test, and we demonstrate that the constantly present measurement errors in empirical data over sizes the test, this simple alteration can be used in most situations with more reliable finite sample inference. We empirically examine the long-run relation between CO2 emissions and the real GDP in the G7 countries. The traditional Johansen tests provide evidence of an equilibrium relation for Canada and weak evidence for the US. However, the suggested size-unbiased wavelet-filtering approach consistently indicates no evidence of cointegration for all six countries.

  • 25.
    Habimana, Olivier
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics. Department of Applied Statistics, College of Business and Economics, University of Rwanda, Kigali, Rwanda.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Testing for nonlinear unit roots in the presence of a structural break2015In: Festschrift in honor of Professor Ghazi Shukur on the occasion of his 60th birthday / [ed] Thomas Holgersson, Växjö: Linnaeus University Press , 2015Chapter in book (Other academic)
  • 26.
    Habimana, Olivier
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics. Department of Applied Statistics, College of Business and Economics, University of Rwanda, Kigali, Rwanda.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Testing for nonlinear unit roots in the presence of a structural break with an application to the qualified PPP during the 1997 Asian financial crisis2018In: International journal of finance and economics, ISSN 1076-9307, E-ISSN 1099-1158, Vol. 23, no 3, p. 221-232Article in journal (Refereed)
    Abstract [en]

    This paper applies Monte Carlo simulations to evaluate the size and power properties in the presence of a structural break, for the standard Augmented Dickey-Fuller (ADF) test versus nonlinear exponential smooth transition autoregressive unit root tests. The break causes the tests to be undersized, and the statistical power considerably decreases. Moreover, the effect is intensified in small samples and very much increased for more persistent nonlinear series. As a remedy, we modify the standard ADF and exponential smooth transition autoregressive unit root tests in order to adjust for a structural break. This improves both the power and the size considerably, even though the empirical size still is lower than the nominal one. More persistent series are more affected by structural breaks, and the new tests are most powerful under the existence of a rather persistent nonlinear data generating process (which is an empirically relevant and common type of data generating process). The proposed tests are applied to investigate mean reversion in the real effective exchange rates of 5 East and Southeast Asian countries, taking into account the structural change in exchange rate regime brought about by the 1997 Asian financial crisis. The empirical findings corroborate our simulation results; the modified more powerful tests are able to reject the unit root in all 5 countries, whereas the tests that do not consider the structural break could only reject in one of these cases.

  • 27.
    Hallgren, Mats
    et al.
    Epidemiology of Psychiatric Conditions, Substance use and Social Environment (EPiCSS), Department of Public Health Sciences, Karolinska Institutet, Sweden.
    Owen, Neville
    Behavioral Epidemiology Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia.
    Stubbs, Brendon
    Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, United Kingdom.
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Public Health Sciences, Karolinska Institutet, Solna, Sweden.
    Vancampfort, Davy
    KU Leuven, Department of Rehabilitation Sciences, Leuven, Belgium.
    Schuch, Felipe
    Centro Universitário La Salle (Unilasalle) Canoas, Brazil.
    Bellocco, Rino
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden.
    Dunstan, David
    Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia.
    Trolle Lagerros, Ylva
    Department of Medicine, Clinic of Endocrinology, Metabolism and Diabetes, Karolinska University, Hospital Huddinge, Stockholm, Sweden.
    Passive and mentally-active sedentary behaviors and incident major depressive disorder: A 13-year cohort study2018In: Journal of Affective Disorders, ISSN 0165-0327, E-ISSN 1573-2517, Vol. 241, p. 579-585Article in journal (Refereed)
    Abstract [en]

    Background: Regular physical activity reduces the risk of depression onset and is an effective treatment for mood disorders. Recent studies have reported that sedentary behavior (SB) increases the risk of depression in adults, but relationships of different types of SBs with depression have not been examined systematically. We explored longitudinal relationships of passive (e.g. watching TV) and mentally-active (e.g. office-work) SBs with incident major depressive disorder (MDD).

    Methods: Self-report questionnaires were completed by 40,569 Swedish adults in 1997; responses were linked to clinician-diagnosed MDD obtained from medical registers until 2010. Relationships between passive, mentally-active and total SBs with incident MDD were explored using survival analysis with Cox proportional hazards regression. Models controlled for leisure time moderate-vigorous physical activity and occupational physical activity. Moderating effects of gender were examined.

    Results: In fully-adjusted models, including only non-depressed adults at baseline, those reporting ≥ 3 h of mentally-active SBs on a typical day (versus < 3 h) had significant lower hazards of incident MDD at follow-up (HR = 0.74, 95% CI = 0.58–0.94, p = 0.018). There was a non-significant positive relationship of passive SBs with incident MDD (HR = 1.20, 95% CI = 0.96–1.52, p = 0.106). The association between total SBs (passive and mentally-active combined) was not significant (HR = 0.91, 95% CI = 0.75–1.10, p = 0.36). Gender did not moderate these associations.

    Limitations: Physical activity and SBs were self-reported.

    Conclusion: Mentally-active SBs may have beneficial effects on adults’ mental well-being. These effects are largely independent of habitual physical activity levels. 

  • 28.
    Hartmann, Miriam
    et al.
    Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden; Women's Global Health Imperative, RTI International, Berkely, CA, USA.
    Giovenco, Danielle
    Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa.
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
    Itzikowitz, Gina
    Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa.
    Ekström, Anna Mia
    Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden; Department of Infectious Diseases, South General Hospital, Stockholm, Sweden .
    Nielsen, Anna
    Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
    Pettifor, Audrey
    Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, USA.
    Bekker, Linda-Gail
    Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa.
    Kågesten, Anna E.
    Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
    Associations between psychosocial wellbeing and experience of gender-based violence at community, household, and intimate-partner levels among a cross-sectional cohort of young people living with and without HIV during COVID-19 in Cape Town, South Africa2023In: BMC Public Health, E-ISSN 1471-2458, Vol. 23, no 1, article id 2115Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Growing evidence indicates that gender-based violence (GBV) increased during COVID-19. We investigated self-reported impact of the pandemic on GBV at community, household and intimate partner (IPV) levels among young people and its associations with psychosocial wellbeing, i.e., COVID-related stressors and mental health.

    METHODS: Cross-sectional data were drawn from a survey with young people ages 13-24 (N = 536) living with HIV (YPLWH) and without HIV (YPLWoH), in peri-urban Cape Town, South Africa. The survey, conducted February-October 2021, examined the impact of the initial lockdown on experience and perceived changes in GBV at each level, and pandemic-related psychosocial wellbeing. Descriptive statistics and binomial and multinomial regression analyses were conducted to illustrate exposure and perceived changes in GBV since lockdown, and their association with COVID-related stress factors (e.g., social isolation, anxiety about COVID), mental health (e.g., depression, anxiety), and other risk factors (e.g., age, gender, socioeconomic status) by HIV status.

    RESULTS: Participants were 70% women with mean age 19 years; 40% were living with HIV. Since lockdown, YPLWoH were significantly more likely than YPLWH to perceive community violence as increasing (45% vs. 28%, p < 0.001), and to report household violence (37% vs. 23%, p = 0.006) and perceive it as increasing (56% vs. 27%, p = 0.002) (ref: decreasing violence). YPLWoH were also more likely to report IPV experience (19% vs. 15%, p = 0.41) and perception of IPV increasing (15% vs. 8%, p = 0.92). In adjusted models, COVID-related stressors and common mental health disorders were only associated with household violence. However, indicators of economic status such as living in informal housing (RRR = 2.07; 95% CI = 1.12-3.83) and food insecurity (Community violence: RRR = 1.79; 95% CI = 1.00-3.20; Household violence: RRR = 1.72; 95% CI = 1.15-2.60) emerged as significant risk factors for exposure to increased GBV particularly among YPLWoH.

    CONCLUSIONS: Findings suggest that for young people in this setting, GBV at community and household levels was more prevalent during COVID-19 compared to IPV, especially for YPLWoH. While we found limited associations between COVID-related stressors and GBV, the perceived increases in GBV since lockdown in a setting where GBV is endemic, and the association of household violence with mental health, is a concern for future pandemic responses and should be longitudinally assessed.

  • 29.
    Holgersson, Thomas
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Festschrift in honor of Professor Ghazi Shukur on the occasion of his 60th birthday2015Collection (editor) (Other academic)
  • 30.
    Holgersson, Thomas
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Centre for Data Intensive Sciences and Applications, Linnaeus University, Växjö, Sweden.
    Kekezi, Orsa
    Jönköping University, Jönköping International Business School, JIBS, Economics. Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE).
    Towards a multivariate innovation index2018In: Economics of Innovation and New Technology, ISSN 1043-8599, E-ISSN 1476-8364, Vol. 27, no 3, p. 254-272Article in journal (Refereed)
    Abstract [en]

    This paper argues that traditional measures of innovation as a univariate phenomenon may not be dynamic enough to adequately describe the complex nature of innovation. Consequently, the purpose is to develop a multidimensional index of innovation that is able to reflect innovation enablers and outputs. The index may then be used (i) to assess and quantify temporal changes of innovation, (ii) to describe regional differences and similarities of innovation, and (iii) serve as exogenous variables to analyze the importance of innovation for other economic phenomena. Our index is defined in a four-dimensional space of orthogonal axes. An empirical case study is used for demonstration of the index, where 44 variables are collected for all municipalities in Sweden. The index spanning the four-dimensional innovation comprises size, accessibility, firm performance, and agglomeration. The proposed index offers a new way of defining and analyzing innovation and should have a wide range of important applications in a world where innovation is receiving a great deal of recognition.

    Download full text (pdf)
    fulltext
  • 31.
    Holgersson, Thomas
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Linnaeus University, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Göteborg University, Sweden .
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Testing for panel unit roots under general cross-sectional dependence2016In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 45, no 5, p. 1785-1801Article in journal (Refereed)
    Abstract [en]

    In this paper we generalize four tests of multivariate linear hypothesis to panel data unit root testing. The test statistics are invariant to certain linear transformations of data and therefore simulated critical values may conveniently be used. It is demonstrated that all four tests remains well behaved in cases of where there are heterogeneous alternatives and cross-correlations between marginal variables. A Monte Carlo simulation is included to compare and contrast the tests with two well-established ones.

  • 32.
    Holgersson, Thomas
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Nordström, Louise
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Öner, Özge
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    On regression modelling with dummy variables versus separate regressions per group: comment on Holgersson et al.2016In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, no 8, p. 1564-1565Article in journal (Other academic)
  • 33.
    Irum, S.
    et al.
    Department of Zoology, University of Gujrat, Gujrat, Pakistan.
    Aftab, M.
    Department of Zoology, University of Gujrat, Gujrat, Pakistan.
    Khan, A.
    Department of Biosciences, COMSATS University Islamabad (CUI), Park Road, Chak Shahzad, Islamabad, Pakistan.
    Naz, S.
    Department of Biological Sciences, National University of Medical Sciences (NUMS), Rawalpindi, Pakistan.
    Simsek, S.
    Department of Parasitology, Faculty of Veterinary Medicine, Firat University, Elazig, Turkey.
    Habib, A.
    Department of Biosciences, COMSATS University Islamabad (CUI), Park Road, Chak Shahzad, Islamabad, Pakistan.
    Afzal, M. S.
    Department of Life Sciences, School of Science, University of Management & Technology (UMT), Lahore, Pakistan.
    Nadeem, M. A.
    Department of Life Sciences, School of Science, University of Management & Technology (UMT), Lahore, Pakistan.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Ahmed, H.
    Department of Biosciences, COMSATS University Islamabad (CUI), Park Road, Chak Shahzad, Islamabad, Pakistan.
    Cutaneous Leishmaniasis (CL): A Cross-Sectional Community Based Survey on Knowledge, Attitude and Practices in a Highly Endemic Area of Waziristan (KPK Province), Pakistan2021In: Acta Tropica, ISSN 0001-706X, E-ISSN 1873-6254, Vol. 213, article id 105746Article in journal (Refereed)
    Abstract [en]

    Recent outbreaks of Cutaneous Leishmaniasis (CL) in Waziristan make the disease a public health concern in Khyber Pakhtunkhwa (KPK) province, Pakistan. The awareness and behavior of local community towards the disease is an important factor towards effective control and management of CL in endemic areas of Pakistan. A cross-sectional community based survey was piloted in new emerging district of North Waziristan Agency (KPK province), Pakistan from August 2019- February 2020. The study aimed to examine the Knowledge, Attitude and Practices (KAP) of the local community members regarding CL. The results revealed that majority of the participants were male. Only 48.2% participants have knowledge about CL and the respondents had a moderate knowledge of CL vector and the disease. Few of the respondents were aware that CL is caused by sand flies, their breeding place, biting time, transmission of CL and control measures. Skin infection and sand-flies were the main disease symptoms and disease vector were known to some of the respondents. Most of the respondents showed positive attitude towards disease seriousness and believed that the disease could be cured and can be treated through modern medicines. Admission to hospitals, cleanliness and use of bed nets were the treatment measures for the disease in suspected patients, whereas some believed that the use of bed nets could be helpful in preventing the leishmaniasis. Moderate knowledge of the CL and its transmission in the study area emphasize the need to initiate health education and awareness campaigns to reduce the disease risk and burden in this highly endemic area in near future.

  • 34.
    Jabbar, Abdul
    et al.
    Department of Clinical Medicine, University of Veterinary and Animal Sciences, Lahore, Punjab, Pakistan.
    Saleem, Muhammad H.
    Department of Clinical Medicine, University of Veterinary and Animal Sciences, Lahore, Punjab, Pakistan.
    Iqbal, Muhammad Z.
    Department of Clinical Medicine, University of Veterinary and Animal Sciences, Lahore, Punjab, Pakistan.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Ashraf, Muhammad
    Department of Theriogenology, University of Veterinary and Animal Sciences, Lahore, Pakistan.
    Tolba, Mahmoud M.
    Biomedical Informatics and Biotechnology Group, Department of Informatics and Systems, Division of Engineering research, National Research Centre, Cairo, Egypt.
    Nasser, Hebatallah A.
    Department of Microbiology and Public Health, Faculty of Pharmacy, Helipolis University, Cairo, Egypt.
    Sajjad, Hira
    Department of Food Science and Human Nutrition, University of Veterinary and Animal Sciences, Lahore, Punjab, Pakistan.
    Hassan, Ayesha
    Department of Surgery and Pet sciences, University of Veterinary and Animal Sciences, Lahore, Punjab, Pakistan.
    Imran, Muhammad
    Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore, Punjab, Pakistan.
    Ahmad, Imtiaz
    Department of Veterinary Clinical Sciences, University of Poonch Rawalakot, Azad Jammu and Kashmir, Pakistan.
    Epidemiology and antibiogram of common mastitis-causing bacteria in Beetal goats2020In: Veterinary World, ISSN 0972-8988, E-ISSN 2231-0916, Vol. 13, no 12, p. 2596-2607Article in journal (Refereed)
    Abstract [en]

    Background and Aim: Mastitis has been identified as the most prevalent and economically imperative disease among dairy animals. Thus, understanding its common bacterial pathogens and risk factors is necessary to improve udder health at herd, region, or country level. However, scientific research on caprine mastitis, especially on Beetal breed, has remained to be insufficient in Pakistan. Therefore, this study aimed to evaluate the epidemiology and antibiogram assay of common mastitis-causing bacterial agents, that is, Staphylococcus, Streptococcus, and Escherichia coli, in dairy goats.

    Materials and Methods: In total, 500 Beetal goats, irrespective of age and those that were not treated with any kind of antimicrobial agents during the past 120 h, were screened using California Mastitis Test in Pattoki, Kasur District, whereas epidemiological factors were recorded. The milk samples of mastitic goats were then collected and processed using standard methods. Each sample was primarily cultured on nutrient agar. Using a specific medium, each bacterial colony was separated using several streak methods. Six antibiotic disks belonging to different antibiotic groups were used for antibiogram profiling of bacterial isolates. Chi-square test was used to assess the association of baseline characteristics and mastitis occurrence. Meanwhile, multivariable logistic regression (p<0.001) was utilized to determine the risk factors associated with positive and negative dichotomous outcome of mastitis.

    Results: The results revealed that the overall prevalence of goat mastitis was 309 (61.8%), in which 260 (52%) and 49 (9.8%) cases were positive for subclinical mastitis (SCM) and clinical mastitis (CM), respectively. Streptococcus and E. coli were found to be the predominant isolates causing SCM and CM, respectively (p<0.001). It was observed that amoxicillin+clavulanic acid was highly sensitive to isolates of Staphylococcus and Streptococcus and ceftiofur sodium to isolates of Streptococcus and E. coli, while enrofloxacin was found to be sensitive to isolates of Streptococcus and E. coli. Risk factors such as herd structure, deworming, vaccination, presence of ticks, use of teat dip and mineral supplements, feeding type, age, parity, housing, blood in the milk, milk leakage, milk taste, and milk yield were found to have the strongest association with mastitis occurrence, while ease of milking has moderate association.

    Conclusion: In the area examined, cases of SCM were found to be higher compared with that of CM, and ceftiofur sodium has been identified as the preferred treatment in both clinical and subclinical forms of caprine mastitis in Beetal goats. Risk factors for mastitis that was identified in this study can form the basis for the creation of an udder health control program specific for dairy goats. We hope our findings could raise awareness of the risk factors and treatment approaches for common mastitis-causing bacterial agents. 

  • 35. Jalloh, Mohamed F.
    et al.
    Sengeh, Paul
    Bunnell, Rebecca E.
    Jalloh, Mohammad B.
    Monasch, Roeland
    Li, Wenshu
    Mermin, Jonathan
    DeLuca, Nickolas
    Brown, Vance
    Nur, Sophia A.
    August, Euna M.
    Ransom, Ray L.
    Namageyo-Funa, Apophia
    Clements, Sara A.
    Dyson, Meredith
    Hageman, Kathy
    Abu Pratt, Samuel
    Nuriddin, Azizeh
    Carroll, Dianna D.
    Hawk, Nicole
    Manning, Craig
    Hersey, Sara
    Marston, Barbara J.
    Kilmarx, Peter H.
    Conteh, Lansana
    Ekström, Anna Mia
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Global Public Health, Karolinska Institutet, Solna, Sweden.
    Redd, John T.
    Nordenstedt, Helena
    Morgan, Oliver
    Evidence of behaviour change during an Ebola virus disease outbreak, Sierra Leone2020In: Bulletin of the World Health Organization, ISSN 0042-9686, E-ISSN 1564-0604, Vol. 98, no 5, p. 330-340Article in journal (Refereed)
    Abstract [en]

    Objective

    To evaluate changes in Ebola-related knowledge, attitudes and prevention practices during the Sierra Leone outbreak between 2014 and 2015.

    Methods

    Four cluster surveys were conducted: two before the outbreak peak (3499 participants) and two after (7104 participants). We assessed the effect of temporal and geographical factors on 16 knowledge, attitude and practice outcomes.

    Findings

    Fourteen of 16 knowledge, attitude and prevention practice outcomes improved across all regions from before to after the outbreak peak. The proportion of respondents willing to: (i) welcome Ebola survivors back into the community increased from 60.0% to 89.4% (adjusted odds ratio, aOR: 6.0; 95% confidence interval, CI: 3.9–9.1); and (ii) wait for a burial team following a relative’s death increased from 86.0% to 95.9% (aOR: 4.4; 95% CI: 3.2–6.0). The proportion avoiding unsafe traditional burials increased from 27.3% to 48.2% (aOR: 3.1; 95% CI: 2.4–4.2) and the proportion believing spiritual healers can treat Ebola decreased from 15.9% to 5.0% (aOR: 0.2; 95% CI: 0.1–0.3). The likelihood respondents would wait for burial teams increased more in high-transmission (aOR: 6.2; 95% CI: 4.2–9.1) than low-transmission (aOR: 2.3; 95% CI: 1.4–3.8) regions. Self-reported avoidance of physical contact with corpses increased in high but not low-transmission regions, aOR: 1.9 (95% CI: 1.4–2.5) and aOR: 0.8 (95% CI: 0.6–1.2), respectively.

    Conclusion

    Ebola knowledge, attitudes and prevention practices improved during the Sierra Leone outbreak, especially in high-transmission regions. Behaviourally-targeted community engagement should be prioritized early during outbreaks.

  • 36.
    Jalloh, Mohamed F.
    et al.
    Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, United States.
    Wallace, A. S.
    Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, United States.
    Bunnell, R. E.
    Division of Global Health Protection, Centers for Disease Control and Prevention, Atlanta, United States.
    Carter, R. J.
    Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, United States.
    Redd, J. T.
    Center for Public Health Preparedness and Response, Centers for Disease Control and Prevention, Atlanta, United States.
    Nur, S. A.
    Division of Global Health Protection, Centers for Disease Control and Prevention, Atlanta, United States.
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Ekström, A. M.
    Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
    Nordenstedt, H.
    Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
    Ebola vaccine? Family first! Evidence from using a brief measure on Ebola vaccine demand in a national household survey during the outbreak in Sierra Leone2020In: Vaccine, ISSN 0264-410X, E-ISSN 1873-2518, Vol. 38, no 22, p. 3854-3861Article in journal (Refereed)
    Abstract [en]

    Background: Vaccination against Ebolavirus is an emerging public health tool during Ebola Virus Disease outbreaks. We examined demand issues related to deployment of Ebolavirus vaccine during the 2014–2015 outbreak in Sierra Leone. Methods: A cluster survey was administered to a population-based sample in December 2014 (N = 3540), before any Ebola vaccine was available to the general public in Sierra Leone. Ebola vaccine demand was captured in this survey by three Likert-scale items that were used to develop a composite score and dichotomized into a binary outcome to define high demand. A multilevel logistic regression model was fitted to assess the associations between perceptions of who should be first to receive an Ebola vaccine and the expression of high demand for an Ebola vaccine. Results: The largest proportion of respondents reported that health workers (35.1%) or their own families (29.5%) should receive the vaccine first if it became available, rather than politicians (13.8%), vaccination teams (9.8%), or people in high risk areas (8.2%). High demand for an Ebola vaccine was expressed by 74.2% of respondents nationally. The odds of expressing high demand were 13 times greater among those who said they or their families should be the first to take the vaccine compared to those who said politicians should be the first recipients (adjusted odds ratio [aOR] 13.0 [95% confidence interval [CI] 7.8–21.6]). The ultra-brief measure of the Ebola vaccine demand demonstrated acceptable scale reliability (Cronbach's α = 0.79) and construct validity (single-factor loadings > 0.50). Conclusion: Perceptions of who should be the first to get the vaccine was associated with high demand for Ebola vaccine around the peak of the outbreak in Sierra Leone. Using an ultra-brief measure of Ebola vaccine demand is a feasible solution in outbreak settings and can help inform development of future rapid assessment tools. 

  • 37.
    Jalloh, Mohamed F.
    et al.
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Global Public Health, Karolinska Institute, Stockholm, Sweden.
    Nur, Sophia A.
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Prybylski, Dimitri
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Nur, Aasli A.
    Department of Sociology, University of Washington, Seattle, Washington, USA.
    Hakim, Avi J.
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Winters, Maike
    Department of Global Public Health, Karolinska Institute, Stockholm, Sweden; Institute for Global Health, Yale University, New Haven, Connecticut, USA.
    Steinhardt, Laura C.
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Gatei, Wangeci
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Omer, Saad B.
    Institute for Global Health, Yale University, New Haven, Connecticut, USA.
    Brewer, Noel T.
    Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA.
    Nordenstedt, Helena
    Department of Global Public Health, Karolinska Institute, Stockholm, Sweden; Department of Internal Medicine and Infectious Diseases, Danderyd University Hospital, Stockholm, Sweden.
    Drivers of COVID-19 policy stringency in 175 countries and territories: COVID-19 cases and deaths, gross domestic products per capita, and health expenditures2022Manuscript (preprint) (Other academic)
    Abstract [en]

    Objective: To understand the associations of COVID-19 cases and deaths with policy stringency globally and regionally.

    Methods: We modeled the marginal effects of new COVID-19 cases and deaths on policy stringency (scored 0–100) in 175 countries and territories, adjusting for gross domestic product (GDP) per capita and health expenditure (% of GDP). Time periods examined were March–August 2020, September 2020– February 2021, and March–August 2021.

    Results: Policy response to new cases and deaths was faster and more stringent early in the COVID-19 pandemic (March–August 2020) compared to subsequent periods. New deaths were more strongly associated with stringent policies than new cases. In an average week, 1 new death per 100,000 people was associated with a stringency increase of 2.1 units in March–August 2020, 1.3 units in September 2020–February 2021, and 0.7 units in March–August 2021. New deaths in Africa and the Western Pacific were associated with more stringency than in other regions. Higher health expenditure was associated with less stringent policies. GDP per capita did not have consistent patterns of associations with stringency.

    Conclusions: Our findings demonstrate the need for enhanced mortality surveillance to ensure policy alignment during health emergencies. Countries that invest less of their GDP in health are inclined to enact stringent policies during health emergencies than countries with more significant health expenditure.

  • 38.
    Jalloh, Mohamed F.
    et al.
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Zeebari, Zangin
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Global Public Health, Karolinska Institute, Stockholm, Sweden.
    Nur, Sophia A.
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Prybylski, Dimitri
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Nur, Aasli A.
    Department of Sociology, University of Washington, Seattle, Washington, USA.
    Hakim, Avi J.
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Winters, Maike
    Department of Global Public Health, Karolinska Institute, Stockholm, Sweden; Institute for Global Health, Yale University, New Haven, Connecticut, USA.
    Steinhardt, Laura C.
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Gatei, Wangeci
    Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Omer, Saad B.
    Institute for Global Health, Yale University, New Haven, Connecticut, USA.
    Brewer, Noel T.
    Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA.
    Nordenstedt, Helena
    Department of Global Public Health, Karolinska Institute, Stockholm, Sweden; Department of Internal Medicine and Infectious Diseases, Danderyd University Hospital, Stockholm, Sweden.
    Drivers of COVID-19 policy stringency in 175 countries and territories: COVID-19 cases and deaths, gross domestic products per capita, and health expenditures2022In: Journal of Global Health, ISSN 2047-2978, E-ISSN 2047-2986, Vol. 12, article id 05049Article in journal (Other academic)
    Abstract [en]

    Background: New data on COVID-19 may influence the stringency of containment policies, but these potential effect are not understood. We aimed to understand the associations of new COVID-19 cases and deaths with policy stringency globally and regionally.

    Methods: We modelled the marginal effects of new COVID-19 cases and deaths on policy stringency (scored 0-100) in 175 countries and territories, adjusting for gross domestic product (GDP) per capita and health expenditure (% of GDP), and public expenditure on health. The time periods examined were March to August 2020, September 2020 to February 2021, and March to August 2021.

    Results: Policy response to new cases and deaths was faster and more stringent early in the COVID-19 pandemic (March to August 2020) compared to subsequent periods. New deaths were more strongly associated with stringent policies than new cases. In an average week, one new death per 100 000 people was associated with a stringency increase of 2.1 units in the March to August 2020 period, 1.3 units in the September 2020 to February 2021 period, and 0.7 units in the March to August 2021 period. New deaths in Africa and the Western Pacific were associated with more stringency than in other regions. Higher health expenditure as a percentage of GDP was associated with less stringent policies. Similarly, higher public expenditure on health by governments was mostly associated with less stringency across all three periods. GDP per capita did not have consistent patterns of associations with stringency.

    Conclusions: The stringency of COVID-19 policies was more strongly associated with new deaths than new cases. Our findings demonstrate the need for enhanced mortality surveillance to ensure policy alignment during health emergencies. Countries that invest less in health or have a lower public expenditure on health may be inclined to enact more stringent policies. This new empirical understanding of COVID-19 policy drivers can help public health officials anticipate and shape policy responses in future health emergencies.

  • 39.
    Johansson, Börje
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Klaesson, Johan
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Wallin, Tina
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Warda, Peter
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Vad betyder högskolan för Region Jönköpings ekonomi?2014Report (Other academic)
  • 40.
    Karlsson, Hyunjoo Kim
    et al.
    Department of Economics and Statistics, The Linnaeus University, Växjö, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Hacker, R. Scott
    Jönköping University, Jönköping International Business School, JIBS, Economics.
    Revisiting the nexus of the financial development and economic development: new international evidence using a wavelet approach2021In: Empirical Economics, ISSN 0377-7332, E-ISSN 1435-8921, Vol. 60, p. 2323-2350Article in journal (Refereed)
    Abstract [en]

    This study investigates Granger causality and instantaneous causality between financial development and economic development for 76 economies of four different income levels. The main novelty of the study is that it fills a gap in existing studies on the relationship between financial development and economic development by employing wavelet analysis, which enables us to study the varying timescale relationships of the variables. Among the findings is that at the scale of 4–8 years, it is more common for financial development and economic development to support each other once a country achieves at least lower-middle-income status.

  • 41.
    Karlsson, Hyunjoo Kim
    et al.
    Department of Economics and Statistics, Linnaeus University, Växjö, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Investigation of the nonlinear behaviour in real exchange rates in developing regions2018In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 25, no 5, p. 335-339Article in journal (Refereed)
    Abstract [en]

    This article examines whether the purchasing power parity (PPP) theory holds or not for the economies in different developing regions located in Africa, Asia and Latin America. In order to investigate this issue, a nonlinear panel unit root test is used to determine if some or all of the real exchange rates in a panel follow a stationary exponential smooth transition autoregressive process. By applying the nonlinear panel unit root test, our results demonstrate an empirical support for the theory of PPP for the economies in developing regions.

  • 42.
    Karlsson, Hyunjoo Kim
    et al.
    Linnaeus Univ, Dept Econ & Stat, POB 451, S-35195 Vaxjo, Sweden..
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Jonkoping Int Business Sch JIBS, Dept Econ Finance & Stat, POB 1026, SE-551 Jonkoping, Sweden..
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Jönköping University, Jönköping International Business School, JIBS, Economics. Jonkoping Int Business Sch JIBS, Dept Econ Finance & Stat, POB 1026, SE-551 Jonkoping, Sweden..
    Unveiling the Time-dependent Dynamics between Oil Prices and Exchange Rates: A Wavelet-based Panel Analysis2020In: Energy Journal, ISSN 0195-6574, E-ISSN 1944-9089, Vol. 41, no 6, p. 87-106Article in journal (Refereed)
    Abstract [en]

    The objective of this paper is to re-examine the relationship between real oil prices and teal effective exchange rates (REER) for major oil-exporting countries with floating exchange rates. We apply the wavelet-based principles of Gallegati et al. (2016) using monthly data for the period 1996 to 2015. In contrast to many previous studies, our results support the theoretically expected positive nexus between the real oil prices and REER for our dataset. This (theoretically-expected) positive relationship is stronger at the larger time scales (that is, at the 4-8 and 8-16 month wavelet scales) compared to the smaller time scales (that is, at the 1-2 and 2-4 month wavelet scales). The findings of this study therefore add to the existing literature, since they disentangle the specific relationship between oil prices and exchange rates at different time scales, which has important policy implications.

  • 43.
    Karlsson, Peter
    et al.
    Department of Economics and Statistics, Linneaus University, Växjö, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics. Department of Economics and Statistics, Linneaus University, Växjö, Sweden.
    Kibria, B. M. Golam
    Department of Mathematics and Statistics, Florida International University, Miami, FL, United States.
    A Liu estimator for the beta regression model and its application to chemical data2020In: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 34, no 10, article id e3300Article in journal (Refereed)
    Abstract [en]

    Beta regression has become a popular tool for performing regression analysis on chemical, environmental, or biological data in which the dependent variable is restricted to the interval [0, 1]. For the first time, in this paper, we propose a Liu estimator for the beta regression model with fixed dispersion parameter that may be used in several realistic situations when the degree of correlation among the regressors differs. First, we show analytically that the new estimator outperforms the maximum likelihood estimator (MLE) using the mean square error (MSE) criteria. Second, using a 'simulation study, we investigate the properties in finite samples of six different suggested estimators of the shrinkage parameter and compare it with the MLE. The simulation results indicate that in the presence of multicollinearity, the Liu estimator outperforms the MLE uniformly. Finally, using an empirical application on chemical data, we show the benefit of the new approach to applied researchers.

  • 44.
    Karlsson, Peter S.
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Point estimators of the Mahalanobis distance in high-dimensional dataManuscript (preprint) (Other academic)
    Abstract [en]

    This paper concerns the problem of estimating the Mahalanobis distance when the dimension of the data matrix is comparable to the sample size. Two different ridge-shrinkage estimators are considered and estimators of related risk functions are derived. The properties of these point estimators are investigated in terms of excess risk and bias relative to the traditional estimator.

  • 45.
    Karlsson, Peter S.
    et al.
    Departments of Economics and Statistics, Linnaeus University, Växjö, Sweden .
    Behrenz, Lars
    Departments of Economics and Statistics, Linnaeus University, Växjö, Sweden .
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Performances of Model Selection Criteria When Variables are Ill Conditioned2019In: Computational Economics, ISSN 0927-7099, E-ISSN 1572-9974, Vol. 54, no 1, p. 77-98Article in journal (Refereed)
    Abstract [en]

    Model selection criteria are often used to find a “proper” model for the data under investigation when building models in cases in which the dependent or explained variables are assumed to be functions of several independent or explanatory variables. For this purpose, researchers have suggested using a large number of such criteria. These criteria have been shown to act differently, under the same or different conditions, when trying to select the “correct” number of explanatory variables to be included in a given model; this, unfortunately, leads to severe problems and confusion for researchers. In this paper, using Monte Carlo methods, we investigate the properties of four of the most common criteria under a number of realistic situations. These criteria are the adjusted coefficient of determination ((Formula presented.)-adj), Akaike’s information criterion (AIC), the Hannan–Quinn information criterion (HQC) and the Bayesian information criterion (BIC). The results from this investigation indicate that the HQC outperforms the BIC, the AIC and the (Formula presented.)-adj under specific circumstances. None of them perform satisfactorily, however, when the degree of multicollinearity is high, the sample sizes are small or when the fit of the model is poor (i.e., there is a low (Formula presented.). In the presence of all these factors, the criteria perform very badly and are not very useful. In these cases, the criteria are often not able to select the true model. 

  • 46.
    Kausar, Tehzeeb
    et al.
    Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.
    Akbar, Atif
    Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.
    Qasim, Muhammad
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Influence diagnostics for the Cox proportional hazards regression model: method, simulation and applications2023In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 93, no 10, p. 1580-1600Article in journal (Refereed)
    Abstract [en]

    This article investigates the performance of several residuals for the Cox proportional hazards regression model to diagnose the influential observations. The standardized and adjusted forms of residuals are proposed for Cox proportional hazards regression model. In addition, Cook's distance is proposed for both standardized and adjusted residuals. The assessment of different residuals for the identification of influential observations is made through the Monte Carlo simulation. A real dataset of bone marrow transplant Leukaemia is analyzed to show the benefit of the proposed methods. Simulation and application results show that the standardized and adjusted residuals based on the Cox-Snell method perform best for the detection of influential points. Furthermore, the standardized, and adjusted Martingale and deviance residuals work better when the sample size is large.

  • 47.
    Khan, M.
    et al.
    Department of Biological Sciences, Quaid I Azam University, Islamabad, Pakistan.
    Omer, Talha
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Ellahi, A.
    Department of Community Medicine, Wah Medical College, National University of Medical Sciences, Rawalpindi, Pakistan.
    Ur Rahman, Z.
    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
    Niaz, R.
    Department of Statistics, Quaid-I-Azam University, Islamabad, Pakistan.
    Ahmad Lone, S.
    Department of Basic Sciences, College of Science and Theoretical Studies, Saudi Electronic University, Riyadh, Saudi Arabia.
    Monitoring and assessment of heavy metal contamination in surface water of selected rivers2023In: Geocarto International, ISSN 1010-6049, E-ISSN 1752-0762, Vol. 38, no 1, article id 2256313Article in journal (Refereed)
    Abstract [en]

    The current research aimed to monitor and assess the heavy metal contamination in the surface water of 53 sampling sites along the selected rivers using principal component analysis and cluster analysis. For this purpose, both physiochemical parameters such as the temperature (T), the potential of hydrogen (pH), total dissolved solids (TDS) and electroconductivity (EC), and heavy metals such as iron (Fe), chromium (Cr), nickel (Ni), cadmium (Cd), lead (Pb) and arsenic (As) are analyzed as potential water contaminants. The average values of pH, TDS, EC and T are found at 7.75, 70.89 mg/L, 139.11 µs/cm and 20.29 °C, respectively, and heavy metals including Cr, Ni, Cd, Pb, As and Fe are observed at 0.04, 0.04, 0.04, 0.03, 0.001 and 0.04 mg/L, respectively. Moreover, it is found that in both rivers hazardous metals, including Cr (100%), Cd (92.30%), Pb (100%), Ni (100%) and Fe (91%), exceed the permissible limits of the WHO.

  • 48.
    Kibria, B. M. Golam
    et al.
    Department of Mathematics and Statistics, Florida International University, Miami, Florida, USA.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    A simulation study of some biasing parameters for the ridge type estimation of Poisson regression2015In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 44, no 4, p. 943-957Article in journal (Refereed)
    Abstract [en]

    This paper proposes several estimators for estimating the ridge parameter k based for Poisson ridge regression (RR) model. These estimators have been evaluated by means of Monte Carlo simulations. As performance criteria, we have calculated the mean squared error (MSE), the mean value and the standard deviation of k. The first criterion is commonly used, while the other two have never been used when analyzing Poisson RR. However, these performance criterion are very informative because, if several estimators have an equal estimated MSE then those with low average value and standard deviation of k should be preferred. Based on the simulated results we may recommend some biasing parameters which may be useful for the practitioners in the field of health, social and physical sciences.

  • 49.
    Kim Karlsson, Hyunjoo
    et al.
    The Linnaeus University, Växjö, Sweden.
    Karlsson, Peter
    Jönköping University, Jönköping International Business School, JIBS, Statistics. The Linnaeus University, Växjö, Sweden .
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Sjölander, Pär
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Wavelet quantile analysis of asymmetric pricing on the Swedish power market2017In: Empirica, ISSN 0340-8744, E-ISSN 1573-6911, Vol. 44, no 2, p. 249-260Article in journal (Refereed)
    Abstract [en]

    In this article we investigate if the Swedish consumer prices for electricity are adjusted equally fast regardless of whether the NordPool power market prices are decreased or increased. Due to relatively moderate variations in the variables, we have applied quantile regression, since it is mainly the large changes (above the median) that essentially tend to have a considerable effect on the consumer prices. Moreover, in order to adjust for stochastic- and deterministic trends, autocorrelation, structural breaks as well as to measure APT effects in the short- and in the medium-run, we apply a wavelet decomposition approach. Our results show evidence that significantly positive asymmetric price transmission (APT) effects exist in this market. More specifically, in the short-run (based on the wavelet decomposition D1 for 1–2 months cycles), we find that that there is a higher propensity to rapidly and systematically increase the consumer prices subsequently to an increase in the NordPool market price, compared with the propensity to decrease their customers prices subsequently to a corresponding drop in the NordPool market prices. However, no significant APT effects were detected in the medium- or in the long-run (i.e. the asymmetric price transmission effects are observed only in the short-run). In summary, we could isolate significant APT effects in the short-run (1–2 months decomposition cycles), and for large changes in the dependent variable (percentiles = 0.9). Therefore, only large changes in the NordPool prices lead to feedback effects in the form of asymmetric price transmission effects. Our evidence supports the notion of firms’ downward stickiness of retail prices for maximizing profit, which are not expected to be found on a fully efficient market. Although our finding shows that the price inefficiency is short-lived, these large temporal inefficiencies are still costly for the consumers. It should be noted that blunt traditional powerless methods do not detect these APT effects, while our wavelet quantile methods are powerful and make a significant contribution in the literature by providing new empirical evidence.

  • 50.
    Locking, Håkan
    et al.
    Department of Economics and Statistics, Linnaeus University, Sweden.
    Månsson, Kristofer
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Shukur, Ghazi
    Jönköping University, Jönköping International Business School, JIBS, Statistics.
    Ridge estimators for probit regression: With an application to labour market data2015In: Bulletin of Economic Research, ISSN 0307-3378, E-ISSN 1467-8586, Vol. 66, no S1, p. S92-S103Article in journal (Refereed)
    Abstract [en]

    In this paper we propose ridge regression estimators for probit models since the commonly applied maximum likelihood (ML) method is sensitive to multicollinearity. An extensive Monte Carlo study is conducted where the performance of the ML method and the probit ridge regression (PRR) is investigated when the data is collinear. In the simulation study we evaluate a number of methods of estimating the ridge parameter k that have recently been developed for use in linear regression analysis. The results from the simulation study show that there is at least one group of the estimators of k that regularly has a lower MSE than the ML method for all different situations that has been evaluated. Finally, we show the benefit of the new method using the classical Dehejia and Wahba (1999) dataset which is based on a labor market experiment.

     

123 1 - 50 of 104
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf