Some statistical issues in the analyses of data from longitudinal studies of elderly chronic care populations

Objective: This article discusses broad statistical issues common to much medical research: intent-to-treat analysis VS. completers analysis; clustered hierarchical and repeated-measures data; missing data and dropouts; and assessment of direct, indirect, and total effects. Traditional approaches and statistical techniques are reviewed and contrasted with modern methods for analysis of medical studies. Method: The concepts are introduced and discussed in general terms; they are illustrated with an example. The example comes from a study of the effect of residence in special care units (SCUs) for demented elderly on the daily function of nursing homes residents. More than 700 residents from 22 nursing facilities, residing in either an SCU or a non-SCU were assessed three times at approximate 6-month intervals. Results: Results from both the application of traditional statistical techniques and modern methods for the analysis of repeated-measures of hierarchical multicenter data are presented, interpreted, and compared. Advantages and shortcomings of these approaches are discussed. Conclusion: This article advocates the use of mixed models and proper causal reasoning and terminology in the analysis and publication of from studies on aging and life course.