Power calculation for causal inference in social science: sample size and minimum detectable effect determination

被引:13
|
作者
Djimeu, Eric W. [1 ,2 ]
Houndolo, Deo-Gracias [3 ]
机构
[1] Int Initiat Impact Evaluat 3ie, Washington, DC USA
[2] Univ Yaounde II, CEREG, Soa, Cameroon
[3] Int Initiat Impact Evaluat 3ie, New Delhi, India
关键词
Power calculation; experimental design; sample size; minimum detectable effect; individual design; cluster design; TRIALS;
D O I
10.1080/19439342.2016.1244555
中图分类号
F0 [经济学]; F1 [世界各国经济概况、经济史、经济地理]; C [社会科学总论];
学科分类号
0201 ; 020105 ; 03 ; 0303 ;
摘要
This paper presents the statistical concepts used in power calculations for experimental design. It provides detailed definitions of parameters used to perform power calculations, useful rules of thumb and different approaches that can be used when performing power calculations. The authors draw from real-world examples to calculate statistical power for individual and cluster randomised controlled trials. This paper provides formulae for sample size determination and minimum detectable effect (MDE) associated with a given statistical power. The paper is accompanied by the sample size and MDE calculator (c), a free online tool that allows users to work with the formulae presented in Section 4.
引用
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页码:508 / 527
页数:20
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