Eelworms, Bullet Holes, and Geraldine Ferraro: Some Problems With Statistical Adjustment and Some Solutions
- 1 June 1989
- journal article
- Published by American Educational Research Association (AERA) in Journal of Educational Statistics
- Vol. 14 (2) , 121-140
- https://doi.org/10.3102/10769986014002121
Abstract
There is no safety in numbers. When data are gathered from a sample in which the selection criteria are unknown, many problems can befall the unwary investigator. In this paper we explore some of these problems and discuss some solutions. Our principle example is drawn from data from students who choose to take the College Board’s Scholastic Aptitude Test (SAT). We explore methods of covariance adjustment as well as more explicitly model-based adjustment methods. Among the latter we discuss Heckman’s Selection Model, Rubin’s Mixture Model, and Tukey’s Simplified Selection Model.Keywords
This publication has 25 references indexed in Scilit:
- How accurately can we assess changes in minority performance on the SAT?American Psychologist, 1988
- Statistics and Causal InferenceJournal of the American Statistical Association, 1986
- SAT SCORES AND AMERICAN STATES: SEEKING FOR USEFUL MEANINGJournal of Educational Measurement, 1985
- Discussion of "on State Education Statistics": A Difficulty with Regression Analyses of Regional Test Score AveragesJournal of Educational Statistics, 1985
- On "State Education Statistics"Journal of Educational Statistics, 1985
- Abraham Wald's Work on Aircraft SurvivabilityJournal of the American Statistical Association, 1984
- From Association to Causation in Observational Studies: The Role of Tests of Strongly Ignorable Treatment AssignmentJournal of the American Statistical Association, 1984
- The central role of the propensity score in observational studies for causal effectsBiometrika, 1983
- Statistics of the Kinsey ReportJournal of the American Statistical Association, 1949