The Effect of a Covariate on Standard Error and Confidence Interval Width
Xiaofeng Liu
Abstract
Xiaofeng Liu
Abstract
The standard error of covariate-adjusted mean difference is not always smaller than that of the unadjusted mean difference despite the fact that adding a covariate is commonly believed to reduce the unexplained error variance. The covariate mean difference between the contrasted treatment conditions can inflate the standard error of the adjusted mean difference. If the covariate is viewed as randomly varying from one study to another, a minimum sample size can be found to attain a desired probability of reducing the standard error and the confidence interval width for the adjusted mean difference.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The standard error of covariate-adjusted mean difference is not always smaller than that of the unadjusted mean difference despite the fact that adding a covariate is commonly believed to reduce the unexplained error variance. The covariate mean difference between the contrasted treatment conditions can inflate the standard error of the adjusted mean difference. If the covariate is viewed as randomly varying from one study to another, a minimum sample size can be found to attain a desired probability of reducing the standard error and the confidence interval width for the adjusted mean difference.
Key concepts: Covariate, Statistics, Confidence interval, Standard error, Mathematics, Standard deviation, Mean difference, Sample size determination