DOI
https://doi.org/10.25772/9Q20-AY57
Defense Date
2012
Document Type
Thesis
Degree Name
Master of Science
Department
Biostatistics
First Advisor
Robert E. Johnson
Second Advisor
Roy T. Sabo
Abstract
It has been shown that pair-matching on an ordered baseline with normally distributed measures reduces the variance of the estimated treatment effect (Park and Johnson, 2006). The main objective of this study is to examine if pair-matching improves the power when the distribution is a mixture of two normal distributions. Multiple scenarios with a combination of different sample sizes and parameters are simulated. The power curves are provided for three cases, with and without matching, as follows: analysis of post-intervention data only, adding baseline as a covariate, and classic pre-post comparison. The study shows that the additional variance reduction provided by pair-matching in the pre-post design is limited for high correlation. When correlation is low, there is a significant power increase. It is shown that the baseline pair-matching improves the power when the two means of a mixture normal distribution are widely spread. The pattern becomes clear for low correlation.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
August 2012