title: Estimating sample size for tests on trends across repeated measurements with missing data based on the interaction term in a mixed model.
abstract: A formula to estimate the required sample size for a study with repeated measurements was constructed based on the test of an interaction term in a mixed model. It covers both random effects and serial correlation and allows for missing data. This formula indicates that the method suggested by Dawson is conservative. A simulation study further verified the accuracy of the formula. Factors that influence the required sample size, such as the number of repeated measurements, the structure of the within-subject correlation, and their interaction, were investigated in detail.
authors.affiliation: Department of Biostatistics, Princess Margaret Hospital, University Health Network, Toronto, Ontario, Canada. qi-long.yi@uhn.on.ca
authors.forename: Qilong
authors.initials: Q
authors.lastname: Yi
authors.forename: Tony
authors.initials: T
authors.lastname: Panzarella
mesh_terms: D015982:Bias; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D010352:Patient Dropouts / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D018401:Sample Size