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Direct linkNam, Yeji; Hong, Sehee – Educational and Psychological Measurement, 2021
This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased parameter estimates: relaxing the within-class normality…
Descriptors: Probability, Models, Statistical Analysis, Statistical Distributions
Peer reviewedSchroger, Erich; And Others – Educational and Psychological Measurement, 1993
Minkowski distances are used to indicate similarity of two vectors in an N-dimensional space. How to compute the probability function, the expectation, and the variance for Minkowski distances and the special cases City-block distance and Euclidean distance. Critical values for tests of significance are presented in tables. (SLD)
Descriptors: Equations (Mathematics), Probability, Statistical Distributions, Statistical Significance
Peer reviewedAiken, Lewis R.; Aiken, Timothy A. – Educational and Psychological Measurement, 1986
Three exact probability tests, counterparts of t tests for single sample, independent samples, and dependent samples, are described for data obtained from ratings on "m" scales by a single rater or on a single scale by "n" raters. (LMO)
Descriptors: Nonparametric Statistics, Probability, Rating Scales, Statistical Distributions
Peer reviewedFowler, Robert L. – Educational and Psychological Measurement, 1984
This study compared two approximations for normalizing noncentral F distributions: one based on the square root of the chi-square distribution (SRA), the other derived from a cube root of the chi-square distribution (CRA). The CRA was superior, and generally provided an excellent approximation for noncentral F. (Author/BW)
Descriptors: Estimation (Mathematics), Hypothesis Testing, Mathematical Formulas, Probability
Peer reviewedEdgington, Eugene S.; Haller, Otto – Educational and Psychological Measurement, 1984
This paper explains how to combine probabilities from discrete distributions, such as probability distributions for nonparametric tests. (Author/BW)
Descriptors: Computer Software, Data Analysis, Hypothesis Testing, Mathematical Formulas
