Sample size calculations for main effects and interactions in case–control studies using Stata's nchi2 and npnchi2 functions
Catherine L. Saunders
Genetic Epidemiology Division
Cancer Research UK Clinical Centre
Leeds, UK
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D. Timothy Bishop
Genetic Epidemiology Division
Cancer Research UK Clinical Centre
Leeds, UK
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Jennifer H. Barrett
Genetic Epidemiology Division
Cancer Research UK Clinical Centre
Leeds, UK
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Abstract. The non-central chi-squared distribution can be used to calculate power for
tests detecting departure from a null hypothesis. Required sample size can
also be calculated because it is proportional to the non-centrality
parameter for the distribution. We demonstrate how these calculations can be
carried out in Stata using the example of calculating power and sample size
for case–control studies of gene–gene and gene–environment
interactions. Do-files are available for these calculations.
View all articles by these authors:
Catherine L. Saunders, D. Timothy Bishop, Jennifer H. Barrett
View all articles with these keywords:
gene–environment interaction, gene–gene interaction, power, sample size, study design, non-central chi^2
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