Can Propensity Score Analysis Approximate Randomized Experiments Using Pretest and Demographic Information in Pre-K Intervention Research?

Abstract

Background: It is unclear whether propensity score analysis (PSA) based on pretest and demographic covariates will meet the ignorability assumption for replicating the results of randomized experiments. Purpose: This study applies within-study comparisons to assess whether pre-Kindergarten (pre-K) treatment effects on achievement outcomes estimated using PSA based on a pretest and demographic covariates can approximate those found in a randomized experiment. Methods: Data—Four studies with samples of pre-K children each provided data on two math achievement outcome measures with baseline pretests and child demographic variables that included race, gender, age, language spoken at home, and mother’s highest education. Research Design and Data Analysis—A randomized study of a pre-K math curriculum provided benchmark estimates of effects on achievement measures. Comparison samples from other pre-K studies were then substituted for the original randomized control and the effects were reestimated using PSA. The correspondence was evaluated using multiple criteria. Results and Conclusions: The effect estimates using PSA were in the same direction as the benchmark estimates, had similar but not identical statistical significance, and did not differ from the benchmarks at statistically significant levels. However, the magnitude of the effect sizes differed and displayed both absolute and relative bias larger than required to show statistical equivalence with formal tests, but those results were not definitive because of the limited statistical power. We conclude that treatment effect estimates based on a single pretest and demographic covariates in PSA correspond to those from a randomized experiment on the most general criteria for equivalence.