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Green, Samuel B.; Thompson, Marilyn S.; Levy, Roy; Lo, Wen-Juo – Educational and Psychological Measurement, 2015
Traditional parallel analysis (T-PA) estimates the number of factors by sequentially comparing sample eigenvalues with eigenvalues for randomly generated data. Revised parallel analysis (R-PA) sequentially compares the "k"th eigenvalue for sample data to the "k"th eigenvalue for generated data sets, conditioned on"k"-…
Descriptors: Factor Analysis, Error of Measurement, Accuracy, Hypothesis Testing
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Stutz, Franziska; Schaffner, Ellen; Schiefele, Ulrich – Journal of Research in Reading, 2017
In order to initiate more research on the role of reading motivation during the initial stages of learning to comprehend texts, we developed the "Reading Motivation Questionnaire for Elementary Students" (RMQ-E). The sample comprised 1497 elementary students in Grades 1-3. By means of exploratory and confirmatory factor analyses, three…
Descriptors: Questionnaires, Reading Motivation, Elementary School Students, Test Validity
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Schmitt, Thomas A.; Sass, Daniel A. – Educational and Psychological Measurement, 2011
Exploratory factor analysis (EFA) has long been used in the social sciences to depict the relationships between variables/items and latent traits. Researchers face many choices when using EFA, including the choice of rotation criterion, which can be difficult given that few research articles have discussed and/or demonstrated their differences.…
Descriptors: Hypothesis Testing, Factor Analysis, Correlation, Criteria
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Schochet, Peter Z. – Evaluation Review, 2009
In social policy evaluations, the multiple testing problem occurs due to the many hypothesis tests that are typically conducted across multiple outcomes and subgroups, which can lead to spurious impact findings. This article discusses a framework for addressing this problem that balances Types I and II errors. The framework involves specifying…
Descriptors: Policy, Evaluation, Testing Problems, Hypothesis Testing
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Sterba, Sonya K.; Copeland, William; Egger, Helen L.; Costello, E. Jane; Erkanli, Alaattin; Angold, Adrian – Journal of Child Psychology and Psychiatry, 2010
Background: The differentiation hypothesis posits that the underlying liability distribution for psychopathology is of low dimensionality in young children, inflating diagnostic comorbidity rates, but increases in dimensionality with age as latent syndromes become less correlated. This hypothesis has not been adequately tested with longitudinal…
Descriptors: Attention Deficit Hyperactivity Disorder, Psychopathology, Depression (Psychology), Separation Anxiety
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Steiger, James H. – Structural Equation Modeling, 2000
Discusses two criticisms raised by L. Hayduk and D. Glaser of the most commonly used point estimate of the Root Mean Square Error (RMSEA) and points out misconceptions in their discussion. Although there are apparent flaws in their arguments, the RMSEA is open to question for several other reasons. (SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Factor Analysis, Hypothesis Testing
Kristof, Walter – 1972
We are concerned with the hypothesis that two variables have a perfect disattenuated correlation, hence measure the same trait except for errors of measurement. This hypothesis is equivalent to saying, within the adopted model, that true scores of two psychological tests satisfy a linear relation. A statistical test of this hypothesis is derived…
Descriptors: Correlation, Error of Measurement, Factor Analysis, Hypothesis Testing
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Park, Joo Ho; Rojewski, Jay W. – Career and Technical Education Research, 2006
Multiple-group confirmatory factor analysis was used to investigate factorial invariance between vocational and academic teacher groups on a measure of the learning organization concept. Participants were 488 full-time teachers of public trade industry-technical and business schools located within Seoul, South Korea. Statistically significant…
Descriptors: Foreign Countries, Vocational High Schools, Factor Analysis, Factor Structure
Penfield, Douglas A. – 1972
Thirty-four papers on educational statistics which were presented at the 1971 AERA Conference are summarized. Six major interest areas are covered: (a) general information; (b) non-parametric methods; (c) errors of measurement and correlation techniques; (d) regression theory; (e) univariate and multivariate analysis; (f) factor analysis. (MS)
Descriptors: Analysis of Variance, Bayesian Statistics, Behavioral Science Research, Computers