Sample Size Estimation for Repeated Measures Analysis in Randomized Clinical Trials with Missing Data
In designing longitudinal studies, researchers must determine the number of subjects to randomize based on the power to detect a clinically meaningful treatment difference and a proposed analysis plan. In this paper, we present formulas for sample size estimation and an assessment of statistical power for a two-treatment repeated measures design allowing for subject attrition. These formulas can be used for comparing two treatment groups across time in terms of linear contrasts. Subjects are assumed to drop out of the study at random so that the missing data do not alter the parameters of interest.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 4 (2008)
Issue (Month): 1 (June)
|Contact details of provider:|| Web page: http://www.degruyter.com |
|Order Information:||Web: http://www.degruyter.com/view/j/ijb|
When requesting a correction, please mention this item's handle: RePEc:bpj:ijbist:v:4:y:2008:i:1:n:9. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Golla)
If references are entirely missing, you can add them using this form.