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Olvera Astivia, Oscar Lorenzo; Kroc, Edward; Zumbo, Bruno D. – Educational and Psychological Measurement, 2020
Simulations concerning the distributional assumptions of coefficient alpha are contradictory. To provide a more principled theoretical framework, this article relies on the Fréchet-Hoeffding bounds, in order to showcase that the distribution of the items play a role on the estimation of correlations and covariances. More specifically, these bounds…
Descriptors: Test Items, Test Reliability, Computation, Correlation
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Shear, Benjamin R.; Zumbo, Bruno D. – Educational and Psychological Measurement, 2013
Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…
Descriptors: Error of Measurement, Multiple Regression Analysis, Data Analysis, Computer Simulation
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Liu, Yan; Zumbo, Bruno D. – Educational and Psychological Measurement, 2012
There is a lack of research on the effects of outliers on the decisions about the number of factors to retain in an exploratory factor analysis, especially for outliers arising from unintended and unknowingly included subpopulations. The purpose of the present research was to investigate how outliers from an unintended and unknowingly included…
Descriptors: Factor Analysis, Factor Structure, Evaluation Research, Evaluation Methods
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Liu, Yan; Zumbo, Bruno D.; Wu, Amery D. – Educational and Psychological Measurement, 2012
Previous studies have rarely examined the impact of outliers on the decisions about the number of factors to extract in an exploratory factor analysis. The few studies that have investigated this issue have arrived at contradictory conclusions regarding whether outliers inflated or deflated the number of factors extracted. By systematically…
Descriptors: Factor Analysis, Data, Simulation, Monte Carlo Methods
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Richardson, Chris G.; Ratner, Pamela A.; Zumbo, Bruno D. – Educational and Psychological Measurement, 2007
The purpose of this investigation was to test the age-related measurement invariance and temporal stability of the 13-item version of Antonovsky's Sense of Coherence Scale (SOC). Multigroup structural equation modeling of longitudinal data from the Canadian National Population Health Survey was used to examine the measurement invariance across 3…
Descriptors: Foreign Countries, Measures (Individuals), Rhetoric, Structural Equation Models
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Zumbo, Bruno D.; Pope, Gregory A.; Watson, Jackie E.; Hubley, Anita M. – Educational and Psychological Measurement, 1997
E. Roskam's (1985) conjecture that steeper item characteristic curve (ICC) "a" parameters (slopes) (and higher item total correlations in classical test theory) would be found with more concretely worded test items was tested with results from 925 young adults on the Eysenck Personality Questionnaire (H. Eysenck and S. Eysenck, 1975).…
Descriptors: Correlation, Personality Assessment, Personality Measures, Test Interpretation
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Zimmerman, Donald W.; Zumbo, Bruno D. – Educational and Psychological Measurement, 1993
A computer simulation compared significance tests of correlation coefficients calculated from initial scores, from ranks assigned by the Spearman method, and from three kinds of modified ranks. Implications of findings for the idea that rank correlation is a nonparametric correlation method are discussed. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Correlation, Nonparametric Statistics
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Rupp, Andre A.; Zumbo, Bruno D. – Educational and Psychological Measurement, 2004
Based on seminal work by Lord and Hambleton, Swaminathan, and Rogers, this article is an analytical, graphical, and conceptual reminder that item response theory (IRT) parameter invariance only holds for perfect model fit in multiple populations or across multiple conditions and is thus an ideal state. In practice, one attempts to quantify the…
Descriptors: Correlation, Item Response Theory, Statistical Analysis, Evaluation Methods