Sample size estimation for GEE method for comparing slopes in repeated measurements data

被引:71
作者
Jung, SH
Ahn, C
机构
[1] Duke Univ, Med Ctr, Dept Biostat & Bioinformat, Durham, NC 27710 USA
[2] Univ Texas, Sch Med, Dept Internal Med, Houston, TX USA
关键词
AR(1); compound symmetry; independent working correlation; independent missing; missing completely at random; monotone missing;
D O I
10.1002/sim.1384
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Sample size calculation is an important component at the design stage of clinical trials. Controlled clinical trials often use a repeated measurement design in which individuals are randomly assigned to treatment groups and followed-up for measurements at intervals across a treatment period of fixed duration. In studies with repeated measurements, one of the popular primary interests is the comparison of the rates of change in a response variable between groups. Statistical models for calculating sample sizes for repeated measurement designs often fail to take into account the impact of missing data correctly. In this paper we propose to use the generalized estimating equation (GEE) method in comparing the rates of change in repeated measurements and introduce closed form formulae for sample size and power that can be calculated using a scientific calculator. Since the sample size formula is based on asymptotic theory, we investigate the performance of the estimated sample size in practical settings through simulations. Copyright (C) 2003 John Wiley Sons, Ltd.
引用
收藏
页码:1305 / 1315
页数:11
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