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Sample size determination for the confidence interval of mean comparison adjusted by multiple covariates

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  • Xiaofeng Liu

Abstract

The current method of determining sample size for confidence intervals does not accommodate multiple covariate adjustment. Under the normality assumption, the effect of multiple covariate adjustment on the standard error of the mean comparison is related to a Hotelling T 2 statistic. Sample size can be calculated to obtain a desired probability of achieving a predetermined width in the confidence interval of the mean comparison with multiple covariate adjustment, given that the confidence interval includes the population parameter. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Xiaofeng Liu, 2013. "Sample size determination for the confidence interval of mean comparison adjusted by multiple covariates," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 155-166, June.
    • Handle: RePEc:spr:stmapp:v:22:y:2013:i:2:p:155-166
    DOI: 10.1007/s10260-012-0212-5
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    References listed on IDEAS

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    1. Rubin, Donald B., 2008. "Comment: The Design and Analysis of Gold Standard Randomized Experiments," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1350-1353.
    2. A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
    3. Michael R. Jiroutek & Keith E. Muller & Lawrence L. Kupper & Paul W. Stewart, 2003. "A New Method for Choosing Sample Size for Confidence Interval–Based Inferences," Biometrics, The International Biometric Society, vol. 59(3), pages 580-590, September.
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    Keywords

    Sample size; Confidence interval; Multiple covariates; 62K99;
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