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309 – Monte Carlo Methodology
Design Issues in Longitudinal Studies
Christopher Morrell
Loyola University Maryland
Veena Shetty
Medstar Health Research Institute
Edward Lakatta
Laboratory of Cardiovascular Sciences, NIA
In designing a longitudinal study one needs to decide on two critical components: duration of study and frequency of visits. In addition, other issues involving sample size, power, number of observations per subject must be addressed. If the study is meant to be completed within a certain time frame, would it better to have a fixed time between observations (which might allow the study to terminate early if its objectives are met) or to spread out the observations over the entire study period? At some point during the study, it may be of interest to see if additional data points would contribute substantially. Assume that the longitudinal data will be analyzed using a linear mixed-effects model. In this investigation we use the standard errors of estimates of model parameters as the criterion. We seek to address the issues using three approaches. First, subsets of a data set are constructed in a number of ways and the standard errors are examined. Second, using a variety of designs, the covariance matrix of the fixed-effects is computed and the standard errors are examined. Finally, a simulation study is conducted.