Subjects often drop out of longitudinal studies prematurely, yielding unbalanced data with unequal numbers of measures for each subject. A simple and convenient approach to analysis is to develop summary measures for each individual and then regress the summary measures on between-subject covariates
A mixed effects model for the analysis of repeated measures cross-over studies
β Scribed by Mary Putt; Vernon M. Chinchilli
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 164 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0277-6715
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β¦ Synopsis
A mixed effects model is developed for cross-over trials in which the response is measured repeatedly within each time period. Relative to previous work on repeated measures cross-overs, the methodology synthesizes two important features. First, our procedure eliminates preliminary testing for carry-over, defined loosely as the component of a response that is due to treatment in the preceding period. This is achieved by generalizing the methodology to cross-over designs in which preliminary testing for carry-over is unnecessary. We focus largely on 'simple' carry-over, that is, carry-over that lasts for exactly one period and is independent of the treatment administered in the period in which the carry-over occurs. However, we also illustrate a modification of the procedure for a repeated measures cross-over design which uses a more complicated model of carry-over. Second, the model allows both the between- and within-subject variance to differ among treatments. Conditions are described wherein closed-form (CF) solutions to the variance components as well as closed-form hypothesis tests of the treatment differences exist. Flexibility in the model is illustrated with an example in which inference based on the CF likelihood-based estimates of the variance, and estimates formed using an iterative routine (PROC MIXED) are compared.
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