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Powell, Marvin G.; Hull, Darrell M.; Beaujean, A. Alexander – Journal of Experimental Education, 2020
Randomized controlled trials are not always feasible in educational research, so researchers must use alternative methods to study treatment effects. Propensity score matching is one such method for observational studies that has shown considerable growth in popularity since it was first introduced in the early 1980s. This paper outlines the…
Descriptors: Probability, Scores, Observation, Educational Research
Ho, Andrew D.; Reardon, Sean F. – Grantee Submission, 2012
Test scores are commonly reported in a small number of ordered categories. Examples of such reporting include state accountability testing, Advanced Placement tests, and English proficiency tests. This paper introduces and evaluates methods for estimating achievement gaps on a familiar standard-deviation-unit metric using data from these ordered…
Descriptors: Achievement Gap, Scores, Computation, Classification
Ho, Andrew D.; Reardon, Sean F. – Journal of Educational and Behavioral Statistics, 2012
Test scores are commonly reported in a small number of ordered categories. Examples of such reporting include state accountability testing, Advanced Placement tests, and English proficiency tests. This article introduces and evaluates methods for estimating achievement gaps on a familiar standard-deviation-unit metric using data from these ordered…
Descriptors: Achievement Gap, Scores, Computation, Classification
Leech, Nancy L.; Onwuegbuzie, Anthony J. – 2002
This paper advocates the use of nonparametric statistics. First, the consequence of using parametric inferential techniques under nonnormality is described. Second, the advantages of using nonparametric techniques are presented. The third purpose is to demonstrate empirically how infrequently nonparametric statistics appear in studies, even those…
Descriptors: Classification, Computer Software, Educational Research, Effect Size
McDermott, Paul A.; Watkins, Marley W. – 1979
A computer program named Program STANDARD is presented and demonstrated. This program calculates the statistical significance of the overall agreement of the categorical assignments. The program is based on Light's statistic, G, for describing the conjoint agreement of many observers with correct or standard set of classifications on nominal…
Descriptors: Classification, Computer Programs, Goodness of Fit, Nonparametric Statistics