First Advisor

Mundfrom, Daniel

Document Type

Dissertation

Date Created

5-1-2011

Department

College of Education and Behavioral Sciences, Applied Statistics and Research Methods, ASRM Student Work

Abstract

Three multivariate methods for measuring change from pretest to posttest are compared with respect to statistical power over various levels and combinations of effect size, alpha level, sample size, number of dependent variables, number of significantly different dependent variables, correlation between corresponding pretest and posttest scores, and correlation between unrelated pretest and posttest scores. The method utilizing posttests as the dependent variables and pretests as covariates was found to have superior statistical power in the majority of the scenarios examined. However, there were scenarios where the method utilizing change scores as dependent variables and the method utilizing only posttests as the dependent variables displayed greater power. Using results from the Monte Carlo simulations, comparisons are presented that reveal the conditions under which each of the three multivariate methods displayed greater statistical power than the other two. In addition to the immediate implications of the current study, suggested future avenues of research that could expand upon the current findings are discussed.

Abstract Format

html

Keywords

Monte Carlo Simulation; Statistical Power; Repeated Measures; Applied Mathematics; MANCOVA; MANOVA; Mathematics; Change Cores

Extent

102 pages

Local Identifiers

Rogers_unco_0161D_10074

Rights Statement

Copyright is held by author.

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