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Corinne Huggins-Manley; Anthony W. Raborn; Peggy K. Jones; Ted Myers – Journal of Educational Measurement, 2024
The purpose of this study is to develop a nonparametric DIF method that (a) compares focal groups directly to the composite group that will be used to develop the reported test score scale, and (b) allows practitioners to explore for DIF related to focal groups stemming from multicategorical variables that constitute a small proportion of the…
Descriptors: Nonparametric Statistics, Test Bias, Scores, Statistical Significance
Jeffry White – Journal of Educational Research and Practice, 2024
Violations of normality and homogeneity are common in educational data. When this occurs, the use of parametric statistics may be inappropriate. A generalized form of nonparametric analyses based on the Puri and Sen L statistic provides an alternative approach. Using a chi-square distribution, this technique is easy to apply and has significant…
Descriptors: Nonparametric Statistics, Learning Analytics, Evaluation Methods, Guidance
Kim, Yongnam; Steiner, Peter – Educational Psychologist, 2016
When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…
Descriptors: Quasiexperimental Design, Causal Models, Statistical Inference, Randomized Controlled Trials
Wyse, Adam E.; Seo, Dong Gi – Practical Assessment, Research & Evaluation, 2014
This article provides a brief overview and comparison of three conditional growth percentile methods; student growth percentiles, percentile rank residuals, and a nonparametric matching method. These approaches seek to describe student growth in terms of the relative percentile ranking of a student in relationship to students that had the same…
Descriptors: Academic Achievement, Achievement Gains, Evaluation Methods, Statistical Analysis
Tendeiro, Jorge N.; Meijer, Rob R. – Journal of Educational Measurement, 2014
In recent guidelines for fair educational testing it is advised to check the validity of individual test scores through the use of person-fit statistics. For practitioners it is unclear on the basis of the existing literature which statistic to use. An overview of relatively simple existing nonparametric approaches to identify atypical response…
Descriptors: Educational Assessment, Test Validity, Scores, Statistical Analysis
Socha, Alan; DeMars, Christine E.; Zilberberg, Anna; Phan, Ha – International Journal of Testing, 2015
The Mantel-Haenszel (MH) procedure is commonly used to detect items that function differentially for groups of examinees from various demographic and linguistic backgrounds--for example, in international assessments. As in some other DIF methods, the total score is used to match examinees on ability. In thin matching, each of the total score…
Descriptors: Test Items, Educational Testing, Evaluation Methods, Ability Grouping

MacKay, Gilbert; And Others – Educational Research, 1996
Suggests problems in calculating standard scores in Goal Attainment Scaling; first, because it is not dealing with interval data; and second, because of difficulties in estimating degrees of relationship among individuals' scores. Proposes nonparametric methods of handling data. (SK)
Descriptors: Evaluation Methods, Nonparametric Statistics, Rating Scales, Scores
Hessen, David J. – Psychometrika, 2005
In the present paper, a new family of item response theory (IRT) models for dichotomous item scores is proposed. Two basic assumptions define the most general model of this family. The first assumption is local independence of the item scores given a unidimensional latent trait. The second assumption is that the odds-ratios for all item-pairs are…
Descriptors: Item Response Theory, Scores, Test Items, Models
Penfield, Randall D. – Applied Psychological Measurement, 2005
Differential item functioning (DIF) is an important consideration in assessing the validity of test scores (Camilli & Shepard, 1994). A variety of statistical procedures have been developed to assess DIF in tests of dichotomous (Hills, 1989; Millsap & Everson, 1993) and polytomous (Penfield & Lam, 2000; Potenza & Dorans, 1995) items. Some of these…
Descriptors: Test Bias, Item Analysis, Psychological Studies, Evaluation Methods