Pretest Measures of the Study Outcome and the Elimination of Selection Bias: Evidence from Three Within Study Comparisons

被引:0
作者
Kelly Hallberg
Thomas D. Cook
Peter M. Steiner
M. H. Clark
机构
[1] University of Chicago,
[2] Mathematica Policy Research,undefined
[3] Northwestern University,undefined
[4] University of Wisconsin,undefined
[5] University of Central Florida,undefined
来源
Prevention Science | 2018年 / 19卷
关键词
Within-study comparison; Propensity score matching; Randomized experiment; Causal inference;
D O I
暂无
中图分类号
学科分类号
摘要
This paper examines how pretest measures of a study outcome reduce selection bias in observational studies in education. The theoretical rationale for privileging pretests in bias control is that they are often highly correlated with the outcome, and in many contexts, they are also highly correlated with the selection process. To examine the pretest’s role in bias reduction, we use the data from two within study comparisons and an especially strong quasi-experiment, each with an educational intervention that seeks to improve achievement. In each study, the pretest measures are consistently highly correlated with post-intervention measures of themselves, but the studies vary the correlation between the pretest and the process of selection into treatment. Across the three datasets with two outcomes each, there are three cases where this correlation is low and three where it is high. A single wave of pretest always reduces bias across the six instances examined, and it eliminates bias in three of them. Adding a second pretest wave eliminates bias in two more instances. However, the pattern of bias elimination does not follow the predicted pattern—that more bias reduction ensues as a function of how highly the pretest is correlated with selection. The findings show that bias is more complexly related to the pretest’s correlation with selection than we hypothesized, and we seek to explain why.
引用
收藏
页码:274 / 283
页数:9
相关论文
共 29 条
[1]  
Bifulco R(2012)Can nonrandomized estimates replicate estimates based on random assignment in evaluations of school choice? A within-study comparison Journal of Policy Analysis and Management 31 729-751
[2]  
Campbell DT(1957)Factors relevant to the validity of experiments in social setting Psychological Bulletin 54 297-312
[3]  
Cook TD(2008)Three conditions under which observational studies produce the same results as experiments Journal of Policy Analysis and Management 27 724-750
[4]  
Shadish WJ(2011)A practical way for computing approximate upper and lower correlation bounds The American Statistician 65 2-91
[5]  
Wong VC(2003)Nonexperimental versus experimental estimates of earnings impacts The Annals of the American Academy 589 63-224
[6]  
Demirtas H(2005)Effects of kindergarten retention policy on children’s cognitive growth in reading and mathematics Education Evaluation and Policy Analysis 27 205-910
[7]  
Hedeker D(2006)Evaluation kindergarten retention: A case study for causal inference for multilevel observational data Journal of the American Statistical Association 101 901-635
[8]  
Glazerman S(1975)The research evidence on the effects of grade retention Review of Educational Research 45 613-499
[9]  
Levy D(2013)The impact of Indiana’s interim assessments on methematics and reading Educational Evaluation and Policy Analysis 35 481-20
[10]  
Myers D(1986)Evaluating the econometric evalautions of training programs with experimental data Annual Economic Review 76 604-55