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Marmolejo-Ramos, Fernando; Cousineau, Denis – Educational and Psychological Measurement, 2017
The number of articles showing dissatisfaction with the null hypothesis statistical testing (NHST) framework has been progressively increasing over the years. Alternatives to NHST have been proposed and the Bayesian approach seems to have achieved the highest amount of visibility. In this last part of the special issue, a few alternative…
Descriptors: Hypothesis Testing, Bayesian Statistics, Evaluation Methods, Statistical Inference
Raykov, Tenko; Marcoulides, George A.; Akaeze, Hope O. – Educational and Psychological Measurement, 2017
This note is concerned with examining the relationship between within-group and between-group variances in two-level nested designs. A latent variable modeling approach is outlined that permits point and interval estimation of their ratio and allows their comparison in a multilevel study. The procedure can also be used to test various hypotheses…
Descriptors: Comparative Analysis, Models, Statistical Analysis, Hierarchical Linear Modeling
Grice, James W.; Yepez, Maria; Wilson, Nicole L.; Shoda, Yuichi – Educational and Psychological Measurement, 2017
An alternative to null hypothesis significance testing is presented and discussed. This approach, referred to as observation-oriented modeling, is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. In terms of analysis, this novel approach complements traditional methods…
Descriptors: Hypothesis Testing, Models, Observation, Statistical Inference
Jamil, Tahira; Marsman, Maarten; Ly, Alexander; Morey, Richard D.; Wagenmakers, Eric-Jan – Educational and Psychological Measurement, 2017
In 1881, Donald MacAlister posed a problem in the "Educational Times" that remains relevant today. The problem centers on the statistical evidence for the effectiveness of a treatment based on a comparison between two proportions. A brief historical sketch is followed by a discussion of two default Bayesian solutions, one based on a…
Descriptors: Bayesian Statistics, Evidence, Comparative Analysis, Problem Solving
Li, Feiming; Cohen, Allan; Bottge, Brian; Templin, Jonathan – Educational and Psychological Measurement, 2016
Latent transition analysis (LTA) was initially developed to provide a means of measuring change in dynamic latent variables. In this article, we illustrate the use of a cognitive diagnostic model, the DINA model, as the measurement model in a LTA, thereby demonstrating a means of analyzing change in cognitive skills over time. An example is…
Descriptors: Statistical Analysis, Change, Thinking Skills, Measurement
Raykov, Tenko; Marcoulides, George A.; Lee, Chun-Lung; Chang, Chi – Educational and Psychological Measurement, 2013
This note is concerned with a latent variable modeling approach for the study of differential item functioning in a multigroup setting. A multiple-testing procedure that can be used to evaluate group differences in response probabilities on individual items is discussed. The method is readily employed when the aim is also to locate possible…
Descriptors: Test Bias, Statistical Analysis, Models, Hypothesis Testing
Hirschfeld, Robert R.; Thomas, Christopher H.; McNatt, D. Brian – Educational and Psychological Measurement, 2008
The authors explored implications of individuals' self-deception (a trait) for their self-reported intrinsic and extrinsic motivational dispositions and their actual learning performance. In doing so, a higher order structural model was developed and tested in which intrinsic and extrinsic motivational dispositions were underlying factors that…
Descriptors: Deception, Predictor Variables, Motivation, Incentives
Wilcox, Rand R. – Educational and Psychological Measurement, 2006
Consider the nonparametric regression model Y = m(X)+ [tau](X)[epsilon], where X and [epsilon] are independent random variables, [epsilon] has a median of zero and variance [sigma][squared], [tau] is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated…
Descriptors: Nonparametric Statistics, Mathematical Models, Regression (Statistics), Probability

Huck, Schuyler W.; Malgady, Robert G. – Educational and Psychological Measurement, 1978
The computation of F ratios from cell means and standard deviations is shown for a two-way analysis of variance. (JKS)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Mathematical Models

Gaebelein, Jacquelyn W.; Soderquist, David R. – Educational and Psychological Measurement, 1978
Procedures to estimate the magnitude of a treatment effect are examined for analysis of variance (ANOVA) designs which have repeated-measures. In particular, it is argued that the estimate of utility (strength of effect) for a within-subjects variable should be adjusted to reflect the underlying ANOVA model. (Author/JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Research Design
Correcting for Heterogeneity of Covariance for Repeated Measures Designs of the Analysis of Variance

Stoloff, Peter H. – Educational and Psychological Measurement, 1970
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Statistical Significance

Hancock, Gregory R. – Educational and Psychological Measurement, 1997
Methods are offered for conducting hypothesis testing associated with disattenuated validity coefficients to overcome limitations of some other suggested approaches. Through using classical test theory's notion of reliability in the form of structured path models, such hypothesis testing may be done with hierarchically related structural equation…
Descriptors: Correlation, Hypothesis Testing, Reliability, Scores

Lienert, G. A.; Krauth, J. – Educational and Psychological Measurement, 1975
Configural frequency analysis (CFA), a new method for identifying types, is illustrated numerically. Relations to latent class analysis and to factor analysis are discussed. It is suggested to use CFA as a type-defining method instead of factor analysis if the variables are linked not only by first but also by higher-order associations. (RC)
Descriptors: Classification, Factor Analysis, Hypothesis Testing, Mathematical Models

Rogosa, David – Educational and Psychological Measurement, 1981
The form of the Johnson-Neyman region of significance is shown to be determined by the statistic for testing the null hypothesis that the population within-group regressions are parallel. Results are obtained for both simultaneous and nonsimultaneous regions of significance. (Author)
Descriptors: Hypothesis Testing, Mathematical Models, Predictor Variables, Regression (Statistics)

Vegelius, Jan – Educational and Psychological Measurement, 1981
The G index is a measure of the similarity between individuals over dichotomous items. Some tests for the G-index are described. For each case an example is included. (Author/GK)
Descriptors: Hypothesis Testing, Mathematical Formulas, Mathematical Models, Nonparametric Statistics