MSurvPow: A FORTRAN program to calculate the sample size and power for cluster-randomized clinical trials with survival outcomes

Feng Gao; Amita K. Manatunga; Shande Chen

doi:10.1016/j.cmpb.2004.11.004

MSurvPow: A FORTRAN program to calculate the sample size and power for cluster-randomized clinical trials with survival outcomes

Feng Gao, Amita K. Manatunga, Shande Chen

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

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.

Original language	English
Pages (from-to)	61-67
Number of pages	7
Journal	Computer Methods and Programs in Biomedicine
Volume	78
Issue number	1
DOIs	https://doi.org/10.1016/j.cmpb.2004.11.004
State	Published - Apr 2005

Keywords

FORTRAN
Multivariate survival data
Power
Sample size

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10.1016/j.cmpb.2004.11.004

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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.",

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note = "Funding Information: This work was supported in part by National Institutes of Health grant M01-RR00039 for A.K. Manatunga.",

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AB - 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.

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KW - Power

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MSurvPow: A FORTRAN program to calculate the sample size and power for cluster-randomized clinical trials with survival outcomes

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