Congenial Multiple Imputation and Matched Pairs Models for Square Tables: An Example of patients’ self-management

Shakir Hussain, Mohamed A Mohammed, Ghazi Shukur

Abstract


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.

 


Full Text: PDF DOI: 10.5430/jbar.v2n1p1

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Journal of Business Administration Research

ISSN 1927-9507 (Print)      ISSN 1927-9515  (Online)

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