An Efficient Procedure for Calculating Sample Size Through Statistical Simulations. (2nd January 2018)

• Record Type: Journal Article
• Authors: Maruo, Kazushi; Tada, Keisuke; Ishii, Ryota; Gosho, Masahiko
• Is Part Of: Statistics in biopharmaceutical research. Volume 10:Number 1(2018)
• Page Start: 1
• Page End: 8
• Publication Date: 2018-01-02
• Subjects: Clinical trial design -- Finite sample bias -- Probit model; Pharmacy -- Statistical methods -- Periodicals; Pharmaceutical biotechnology -- Statistical methods -- Periodicals; Biopharmaceutics -- Periodicals; Biometry -- Periodicals; Pharmacy -- Statistical methods; Periodicals; 615.190727
• DOI: 10.1080/19466315.2017.1349689
• Languages: English
• ISSNs: 1946-6315

Abstract

ABSTRACT: While planning clinical trials, when simple formulas are unavailable to calculate sample size, statistical simulations are used instead. However, one has to spend much computation time obtaining adequately precise and accurate simulated sample size estimates, especially when there are many scenarios for the planning and/or the specified statistical method is complicated. In this article, we summarize the theoretical aspect of statistical simulation-based sample size calculation. Then, we propose a new simulation procedure for sample size calculation by fitting the probit model to simulation result data. From the theoretical and simulation-based evaluations, it is suggested that the proposed simulation procedure provide more efficient and accurate sample size estimates than ordinary algorithm-based simulation procedure especially when estimated sample sizes are moderate to large, therefore it would help to dramatically reduce the computational time required to conduct clinical trial simulations.