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Peer reviewedRamseyer, Gary C. – Journal of Experimental Education, 1979
A procedure is discussed for testing the significance of the difference in two correlated correlation coefficients, using Fisher's Z-Transformation. The procedure is applicable to a wide range of problems involving tests between dependent correlations and has documented mathematical support when its power curves are examined. (MH)
Descriptors: Correlation, Hypothesis Testing, Statistical Analysis, Statistical Significance
Peer reviewedLasky, Robert E. – Child Development, 1979
Attempts to differentiate the serial habituation hypothesis from the regression to the mean hypothesis as explanations for the reduction of visual fixations in the form perception of four-month-old infants. Results support a regression to the mean interpretation of the data. (JMB)
Descriptors: Hypothesis Testing, Infants, Visual Perception, Visual Stimuli
Peer reviewedFordyce, Michael W. – Educational and Psychological Measurement, 1977
A flexible Fortran program for computing one way analysis of variance is described. Requiring minimal core space, the program provides a variety of useful group statistics, all summary statistics for the analysis, and all mean comparisons for a priori or a posteriori testing. (Author/JKS)
Descriptors: Analysis of Variance, Computer Programs, Hypothesis Testing
Peer reviewedFordyce, Michael W. – Educational and Psychological Measurement, 1977
A flexible Fortran program for computing a complete analysis of covariance is described. Requiring minimal core space, the program provides all group and overall summary statistics for the analysis, a test of homogeneity of regression, and all posttest mean comparisons for a priori or a posteriori testing. (Author/JKS)
Descriptors: Analysis of Covariance, Computer Programs, Hypothesis Testing
Peer reviewedBedeian, Arthur G.; Armenakis, Achilles A. – Educational and Psychological Measurement, 1977
This paper provides a mathematical algorithm for Fisher's exact probability test which is adaptable to contingency tables greater than two by two, and which provides the user with an index of predictive association designed for crosstabulations of nominal level variables. (Author/JKS)
Descriptors: Computer Programs, Expectancy Tables, Hypothesis Testing, Probability
Peer reviewedKlockars, Alan J.; Hancock, Gregory – Journal of Educational and Behavioral Statistics, 1997
The use of finite intersection tests (FIT) to unify methods for simultaneous inference and to test orthogonal contrasts is discussed. Multiple comparison procedures that combine FIT with sequential hypothesis testing are illustrated, and a simulation strategy is presented to generate values needed for FIT methods. (SLD)
Descriptors: Comparative Analysis, Hypothesis Testing, Simulation, Statistical Inference
Peer reviewedWilcox, 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
Peer reviewedFeldt, Leonard S. – Applied Measurement in Education, 1990
Sampling theory for the intraclass reliability coefficient, a Spearman-Brown extrapolation of alpha to a single measurement for each examinee, is less recognized and less cited than that of coefficient alpha. Techniques for constructing confidence intervals and testing hypotheses for the intraclass coefficient are presented. (SLD)
Descriptors: Hypothesis Testing, Measurement Techniques, Reliability, Sampling
Peer reviewedLi, Jianmin; And Others – Applied Psychological Measurement, 1992
This computer program computes the adjusted alpha level using the original Bonferroni procedure and four modified Bonferroni procedures. It is written in Statistical Analysis System (SAS) macro language. Input and output features are described. (SLD)
Descriptors: Computer Software, Computer Software Evaluation, Hypothesis Testing
Peer reviewedKaplan, 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
Peer reviewedMyors, Brett – Journal of Vocational Behavior, 1996
A method based on Spearman rank-order correlation coefficients was applied to the hypothesized ranks among correlations in Holland's hexagon of vocational interests. The procedure was easy to compute and apply and was amenable to comparing the fit in several matrices and to conducting meta-analysis. (SK)
Descriptors: Hypothesis Testing, Models, Test Validity, Vocational Interests
Peer reviewedCoward, Sean W.; Stevens, Catherine J. – Psychological Record, 2004
In developing a theoretical framework for the field of ecological acoustics, Gaver (1993b) distinguished between the experience of musical listening (perceiving sounds) and everyday listening (perceiving sources of sounds). Within the everyday listening experience, Gaver (1993a) proposed that the frequency of an object results from, and therefore…
Descriptors: Acoustics, Listening, Auditory Perception, Experiments
Raykov, Tenko – Structural Equation Modeling, 2005
A didactic discussion of covariance structure modeling in longitudinal studies with missing data is presented. Use of the full-information maximum likelihood method is considered for model fitting, parameter estimation, and hypothesis testing purposes, particularly when interested in patterns of temporal change as well as its covariates and…
Descriptors: Longitudinal Studies, Hypothesis Testing, Maximum Likelihood Statistics
Colangelo, Annette; Buchanan, Lori; Westbury, Chris – Brain and Cognition, 2004
Deep dyslexia is an acquired reading disorder that involves the production of semantic errors and the inability to read aloud nonwords successfully. Several explanations for this reading impairment posit multiple loci of damage to account for the various error types produced in deep dyslexia. In contrast, the failure of inhibition hypothesis…
Descriptors: Dyslexia, Semantics, Error Patterns, Inhibition
Hawke, Jesse L.; Wadsworth, Sally J.; Olson, Richard K.; DeFries, John C. – Reading and Writing: An Interdisciplinary Journal, 2007
To test the hypothesis that the etiology of reading difficulties may differ for males and females in more severely impaired samples, reading performance data from monozygotic (MZ), same-sex dizygotic (DZ[subscript ss]), and opposite-sex dizygotic (DZ[subscript os]) twin pairs were analyzed using a model-fitting implementation of the DeFries-Fulker…
Descriptors: Severity (of Disability), Environmental Influences, Etiology, Genetics

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