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Woods, Carol M. – Multivariate Behavioral Research, 2009
Gamma-family measures are bivariate ordinal correlation measures that form a family because they all reduce to Goodman and Kruskal's gamma in the absence of ties (1954). For several gamma-family indices, more than one variance estimator has been introduced. In previous research, the "consistent" variance estimator described by Cliff and…
Descriptors: Intervals, Computation, Evaluation, Simulation
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Wilcox, Rand R. – Multivariate Behavioral Research, 2003
Conducted simulations to explore methods for comparing bivariate distributions corresponding to two independent groups, all of which are based on Tukey's "depth," a generalization of the notion of ranks to multivariate data. Discusses steps needed to control Type I error. (SLD)
Descriptors: Hypothesis Testing, Multivariate Analysis, Simulation, Statistical Distributions
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Ferrando, Pere J.; Lorenzo-Seva, Urbano – Multivariate Behavioral Research, 1999
Describes the implementation of a standard Pearson chi-square statistic to test the null hypothesis of bivariate normality for latent variables in the Type I censored model. Assesses the behavior of the statistic through simulation and illustrates the statistic through an empirical example. Discusses limitations of the test. (Author/SLD)
Descriptors: Chi Square, Evaluation Methods, Hypothesis Testing, Multivariate Analysis
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Dolan, Conor V.; Molenaar, Peter C. M. – Multivariate Behavioral Research, 1994
In multigroup covariance structure analysis with structured means, the traditional latent selection model is formulated as a special case of phenotypic selection. Illustrations with real and simulated data demonstrate how one can test specific hypotheses concerning selection on latent variables. (SLD)
Descriptors: Analysis of Covariance, Group Membership, Hypothesis Testing, Selection
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Revelle, William; Rocklin, Thomas – Multivariate Behavioral Research, 1979
A new procedure for determining the optimal number of interpretable factors to extract from a correlation matrix is introduced and compared to more conventional procedures. The new method evaluates the magnitude of the very simple structure index of goodness of fit for factor solutions of increasing rank. (Author/CTM)
Descriptors: Factor Analysis, Goodness of Fit, Hypothesis Testing, Research Design
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Wilcox, Rand R. – Multivariate Behavioral Research, 1995
Five methods for testing the hypothesis of independence between two sets of variates were compared through simulation. Results indicate that two new methods, based on robust measures reflecting the linear association between two random variables, provide reasonably accurate control over Type I errors. Drawbacks to rank-based methods are discussed.…
Descriptors: Analysis of Covariance, Comparative Analysis, Hypothesis Testing, Robustness (Statistics)
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Emons, Wilco H. M.; Sijtsma, Klaas; Meijer, Rob R. – Multivariate Behavioral Research, 2004
The person-response function (PRF) relates the probability of an individual's correct answer to the difficulty of items measuring the same latent trait. Local deviations of the observed PRF from the expected PRF indicate person misfit. We discuss two new approaches to investigate person fit. The first approach uses kernel smoothing to estimate…
Descriptors: Probability, Simulation, Item Response Theory, Test Items