Sample size and power determination for clustered repeated measurements.
It is common in epidemiological and clinical studies that each subject has repeated measurements on a single common variable, while the subjects are also 'clustered'. To compute sample size or power of a test, we have to consider two types of correlation: correlation among repeated measurements within the same subject, and correlation among subjects in the same cluster. We develop, based on generalized estimating equations, procedures for computing sample size and power with clustered repeated measurements. Explicit formulae are derived for comparing two means, two slopes and two proportions, under several simple correlation structures.
Liu
Aiyi
A
Biostatistics Unit, Lombardi Cancer Center, Georgetown University Medical Center, Washington, DC 20007, USA. liual@gunet.gerogetown.edu
Shih
W J
WJ
Gehan
E
E
D016301:Alveolar Bone Loss / Q000473:pathology; D001943:Breast Neoplasms / Q000235:genetics; D002986:Clinical Trials as Topic / Q000379:methods*; D016000:Cluster Analysis; D005260:Female; D019398:Genes, BRCA1; D024522:Genes, BRCA2; D005817:Genetic Counseling / Q000379:methods; D006801:Humans; D008137:Longitudinal Studies; D010510:Periodontal Diseases / Q000473:pathology; D018401:Sample Size