title: MSurvPow: a FORTRAN program to calculate the sample size and power for cluster-randomized clinical trials with survival outcomes.
abstract: Manatunga and Chen [A.K. Manatunga, S. Chen, Sample size estimation for survival outcomes in cluster-randomized studies with small cluster sizes, Biometrics 56 (2000) 616-621] proposed a method to estimate sample size and power for cluster-randomized studies where the primary outcome variable was survival time. The sample size formula was constructed by considering a bivariate marginal distribution (Clayton-Oakes model) with univariate exponential marginal distributions. In this paper, a user-friendly FORTRAN 90 program was provided to implement this method and a simple example was used to illustrate the features of the program.
authors.affiliation: Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA. feng@wubios.wustl.edu
authors.forename: Feng
authors.initials: F
authors.lastname: Gao
authors.forename: Amita K
authors.initials: AK
authors.lastname: Manatunga
authors.forename: Shande
authors.initials: S
authors.lastname: Chen
mesh_terms: D016000:Cluster Analysis; D006801:Humans; D015233:Models, Statistical; D010361:Patients / Q000523:psychology*; D011381:Programming Languages; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D018401:Sample Size; D012984:Software; D016019:Survival Analysis; D014481:United States