The impact of ignoring measurement error when estimating sample size for epidemiologic studies

被引:9
作者
Devine, O [1 ]
机构
[1] Ctr Dis Control & Prevent, Atlanta, GA USA
关键词
study design; measurement error; errors in variables; sample size; power;
D O I
10.1177/0163278703255232
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
The author presents two examples illustrating the bias in sample-size estimates that can result from ignoring measurement error among study variables. The first example examines the impact of ignoring misclassification of the study's outcome variable on the accuracy of sample-size estimates. In addition, the author outlines a simple yet effective means of adjusting sample-size estimates to account for outcome misclassification. In the second example, the author illustrates the potential for severe underestimation of required sample size in studies using linear regression to evaluate associations between the outcome of interest and an independent variable subject to classical measurement error The author concludes with a discussion of pertinent literature that might be helpful to study planners interested in adjusting sample-size estimates to account for measurement errors in both outcome and predictor variables.
引用
收藏
页码:315 / 339
页数:25
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