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Congenial Multiple Imputation and Matched Pairs Models for Square Tables
Linnaeus University.
University of Birmingham.
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics. (Statistik)
2013 (English)In: Journal of Business Administration Research, ISSN 1927-9507, Vol. 2, no 1, -8 p.Article in journal (Refereed) Published
Abstract [en]

Experimental studies often measure an individual’s quality of life before and after an intervention, with the data organized into a square table and analyzed using matched pair modeling. However, it is not unusual to find missing data in either round (i.e., before and/or after) of such studies and the use of multiple imputations with matched-pair modeling remains relatively unreported in the applied statistics literature. In this paper we introduce an approach which maintains dependency of responses over time and makes a match between the imputer and the analyst. We use ‘before’ and ‘after’ quality-of-life data from a randomized controlled trial to demonstrate how multiple imputation and matched-pair modeling can be congenially combined, avoiding a possible mismatch of imputation and analyses, and to derive a properly consolidated analysis of the quality-of-life data. We illustrate this strategy with a real-life example of one item from a quality-of-life study that evaluates the effectiveness of patients’ self-management of anticoagulation versus standard care as part of a randomized controlled trial.

Place, publisher, year, edition, pages
2013. Vol. 2, no 1, -8 p.
National Category
Social Sciences
Identifiers
URN: urn:nbn:se:hj:diva-20147DOI: 10.5430/jbar.v2n1p1Local ID: IHHEFSISOAI: oai:DiVA.org:hj-20147DiVA: diva2:580633
Available from: 2012-12-23 Created: 2012-12-23 Last updated: 2014-03-04Bibliographically approved

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  • apa
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