Date of Award

4-2013

Degree Name

Doctor of Philosophy

Department

Educational Leadership, Research and Technology

First Advisor

Dr. Brooks Applegate

Second Advisor

Dr. Joseph Kretovics

Third Advisor

Dr. Warren E. Lacefield

Keywords

Monte Carlo simulation, matching, propensity score, exact matching, education, social sciences

Abstract

Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized designs. In such situations, subject matching provides an alternative design approach for conducting causal inference studies. This study examined various design conditions hypothesized to affect matching procedures’ bias recovery ability.

See attachment for full abstract.

Access Setting

Dissertation-Open Access

201304_Itangata_M_Abstract.pdf (136 kB)
Abstract

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