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Optimal Time-points in Clinical Trials with Linearly Divergent Treatment Effects by Bjorn Winkens; Hubert J. A. Schouten; Gerard J. P. van Breukelen; Martijn P. F. Berger is a Mathematics article available to read on EtoBox.

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## Abstract In repeated measures studies, equidistant time‐points do not always yield efficient treatment effect estimators. In the present paper, the optimal allocation of time‐points is calculated for a small number of repeated measures, different covariance structures and linearly divergent treatment effects. The gain in efficiency of the treatment effect estimator by using optimally allocated time‐points instead of equidistant time‐points or by adding optimally spaced measures (at the expense of patients) is then computed. The assumed covariance structure is crucial for the results. For a compound symmetric covariance structure, a large gain in efficiency is obtained by adding repeated measures at the end of the study. For a first‐order auto‐regressive covariance structure, highly efficient treatment effect estimators are obtained with only two repeated measures, i.e. at the start and at the end of the study. For a first‐order auto‐regressive covariance structure including measurement error, the gain in efficiency by adding optimally spaced measures depends on the covariance parameter values. The gain in efficiency is similar with or without a random intercept. For a fixed stud

Who reads Optimal Time-points in Clinical Trials with Linearly Divergent Treatment Effects?

Author

Bjorn Winkens; Hubert J. A. Schouten; Gerard J. P. van Breukelen; Martijn P. F. Berger

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0277-6715)

Published

2005

Language

EN

Field

Mathematics (Physical Sciences)