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Showing 1 to 15 of 70 results Save | Export
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Velicer, Wayne F.; Brick, Leslie Ann D.; Fava, Joseph L.; Prochaska, James O. – Multivariate Behavioral Research, 2013
Testing Theory-based Quantitative Predictions (TTQP) represents an alternative to traditional Null Hypothesis Significance Testing (NHST) procedures and is more appropriate for theory testing. The theory generates explicit effect size predictions and these effect size estimates, with related confidence intervals, are used to test the predictions.…
Descriptors: Smoking, Statistical Significance, Confidence Testing, Effect Size
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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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Malone, Patrick S.; Lamis, Dorian A.; Masyn, Katherine E.; Northrup, Thomas F. – Multivariate Behavioral Research, 2010
The gateway drug model is a popular conceptualization of a progression most substance users are hypothesized to follow as they try different legal and illegal drugs. Most forms of the gateway hypothesis are that "softer" drugs lead to "harder," illicit drugs. However, the gateway hypothesis has been notably difficult to…
Descriptors: Drug Use, Models, Statistical Analysis, Computer Software
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Ryu, Ehri; West, Stephen G.; Sousa, Karen H. – Multivariate Behavioral Research, 2009
We extended Wilson and Cleary's (1995) health-related quality of life model to examine the relationships among symptom status (Symptoms), functional health (Disability), and quality of life (QOL). Using a community sample (N = 956) of male HIV positive patients, we tested a mediation model in which the relationship between Symptoms and QOL is…
Descriptors: Quality of Life, Questionnaires, Patients, Symptoms (Individual Disorders)
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Krishnamoorthy, K.; Xia, Yanping – Multivariate Behavioral Research, 2008
The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…
Descriptors: Statistical Analysis, Intervals, Sample Size, Testing
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Gottfredson, Nisha C.; Panter, A. T.; Daye, Charles E.; Allen, Walter F.; Wightman, Linda F. – Multivariate Behavioral Research, 2009
Controversy surrounding the use of race-conscious admissions can be partially resolved with improved empirical knowledge of the effects of racial diversity in educational settings. We use a national sample of law students nested in 64 law schools to test the complex and largely untested theory regarding the effects of educational diversity on…
Descriptors: Law Students, Race, Law Schools, Structural Equation Models
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Preacher, Kristopher J.; Rucker, Derek D.; Hayes, Andrew F. – Multivariate Behavioral Research, 2007
This article provides researchers with a guide to properly construe and conduct analyses of conditional indirect effects, commonly known as moderated mediation effects. We disentangle conflicting definitions of moderated mediation and describe approaches for estimating and testing a variety of hypotheses involving conditional indirect effects. We…
Descriptors: Teaching Methods, Student Interests, Researchers, Intervals
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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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Kaplan, David – Multivariate Behavioral Research, 1999
Proposes an extension of the propensity score adjustment method to the analysis of group differences on latent variable models. Uses multiple indicators-multiple causes (MIMIC) structural equation modeling to test hypotheses about treatment group differences. Discusses the role of factorial invariance as it relates to this approach. (SLD)
Descriptors: Groups, Hypothesis Testing, Scores, Structural Equation Models
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Steiger, James H. – Multivariate Behavioral Research, 1980
The goodness-of-fit of correlational pattern hypotheses has traditionally been assessed either with a likelihood ratio statistic or with a quadratic form statistic. Several alternative statistics, based on the use of the Fisher r-to-z transform, are proposed and assessed in a Monte Carlo experiment. (Author/JKS)
Descriptors: Correlation, Data Analysis, Hypothesis Testing, Longitudinal Studies
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Eiting, Mindert H.; Mellenbergh, Gideon J. – Multivariate Behavioral Research, 1981
A commentary is made on a previously published article concerning testing the equivalence of covariance matrices. An error in the previous article (by the same authors) is pointed out and the consequences of the error are discussed. (JKS)
Descriptors: Analysis of Covariance, Data Analysis, Hypothesis Testing, Matrices
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Jones, Russell A.; And Others – Multivariate Behavioral Research, 1989
The stability of dimensions extracted from a body of free response data was studied using 1,523 expressions of concern and questions raised by 271 elderly persons and analyzed by 2 groups of experimenters. The structures of resulting multidimensional configurations obtained by the 2 groups were identical. (SLD)
Descriptors: Data Analysis, Hypothesis Testing, Multidimensional Scaling, Older Adults
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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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Jackson, Douglas N.; Morf, Martin E. – Multivariate Behavioral Research, 1974
A method is proposed and illustrated for estimating the degree to which a factor rotation to a hypothesized target represents an improvement over rotation to a random target. (Author)
Descriptors: Factor Analysis, Goodness of Fit, Hypothesis Testing, Matrices
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Mendoza, Jorge L.; And Others – Multivariate Behavioral Research, 1978
Four testing procedures for establishing the number of non-zero population roots in canonical analysis are investigated. Results of a Monte Carlo study indicate that three well-established procedures were effective, and a new procedure designed to correct a supposed flaw in the other procedures was ineffective. (JKS)
Descriptors: Correlation, Hypothesis Testing, Monte Carlo Methods, Multivariate Analysis
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