ERIC Number: ED228316
Record Type: RIE
Publication Date: 1983-Apr
Reference Count: 0
Comparison of Methods of Data Analysis in Nonrandomized Experiments.
Blumberg, Carol Joyce; And Others
Various methods have been suggested for the analysis of data collected in research settings where random assignment of subjects to groups has not occurred. For the purposes of this paper the set of allowable nonrandomized designs is made up of those research designs where data are collected for one or more groups of subjects at two or more time points on some measure of interest. Further, none of the groups need be a control group. The main purpose of the paper is to describe and report the results of a Monte Carlo simulation study that was carried out to determine which of several data analysis methods developed by either Blumberg and Porter or Olejnik yields the best point estimates of treatment effects under various constraints. When growth on the measure of interest is linear over time, Blumberg and Porter's methods provide the best estimates. When growth is exponential over time, the results are mixed: under some constraints Olejnik's method is best, but usually Blumberg and Porter's methods provide the best estimates. (Author)
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: N/A
Authoring Institution: N/A
Identifiers: Monte Carlo Studies; Nonrandom Selection
Note: Paper presented at the Annual Meeting of the American Educational Research Association (67th, Montreal, Quebec, April 11-15, 1983). Research supported in part by a grant from the University of Delaware Research Foundation.