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ERIC Number: ED565165
Record Type: Non-Journal
Publication Date: 2013-Feb-17
Pages: 13
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Comparing Performance of Propensity Scores Techniques and Ordinary Least Square Methods in Estimating Treatment Effects: A Monte Carlo Simulation Study
Apaloo, Francis
Online Submission
A key issue in quasi-experimental studies and also with many evaluations which required a treatment effects (i.e. a control or experimental group) design is selection bias (Shadish el at 2002). Selection bias refers to the selection of individuals, groups or data for analysis such that proper randomization is not achieved, thereby ensuring that the sample obtained is not representative of the population intended to be analyzed (Shadish el 2002). There are many ways in which selection bias threatens the validity of study conclusions. One is internal validity, which refers to the causal link between independent variables (which, for example, describe the participants or features of the service they receive) and dependent variables (particularly the outcome of the program). Here we are concerned with whether the program or intervention is the cause responsible for the observed effects rather than extraneous factor.
Publication Type: Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A