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Direct linkLeth-Steensen, Craig; Gallitto, Elena – Educational and Psychological Measurement, 2016
A large number of approaches have been proposed for estimating and testing the significance of indirect effects in mediation models. In this study, four sets of Monte Carlo simulations involving full latent variable structural equation models were run in order to contrast the effectiveness of the currently popular bias-corrected bootstrapping…
Descriptors: Mediation Theory, Structural Equation Models, Monte Carlo Methods, Simulation
Peer reviewedKeselman, H. J.; And Others – Educational and Psychological Measurement, 1976
Compares the harmonic mean and Kramer unequal group forms of the Tukey test for various: (a) degrees of disparate group sizes, (b) numbers of groups, and (c) nominal significant levels. (RC)
Descriptors: Comparative Analysis, Probability, Sampling, Statistical Significance
Peer reviewedLutz, J. Gary – Educational and Psychological Measurement, 1974
Descriptors: Computer Programs, Hypothesis Testing, Sampling, Statistical Significance
Peer reviewedAlf, Edward; Abrahams, Norman – Educational and Psychological Measurement, 1971
Descriptors: Correlation, Sampling, Statistical Analysis, Statistical Significance
Peer reviewedShaffer, Juliet Popper; Gillo, Martin W. – Educational and Psychological Measurement, 1974
Descriptors: Analysis of Variance, Research Methodology, Sampling, Statistical Significance
Peer reviewedBerry, Kenneth J.; Mielke, Paul W., Jr. – Educational and Psychological Measurement, 1986
An algorithm and associated FORTRAN-77 computer subroutine are described for computing Goodman and Kruskal's tau-b statistic along with the associated nonasymptotic probability value under the null hypothesis tau=O. (Author)
Descriptors: Algorithms, Computer Software, Programing Languages, Sampling
Peer reviewedFriedman, Herbert – Educational and Psychological Measurement, 1982
A concise table is presented based on a general measure of magnitude of effect which allows direct determinations of statistical power over a practical range of values and alpha levels. The table also facilitates the setting of the research sample size needed to provide a given degree of power. (Author/CM)
Descriptors: Hypothesis Testing, Power (Statistics), Research Design, Sampling
Peer reviewedMorse, David T. – Educational and Psychological Measurement, 1998
Describes MINSIZE, an MS-DOS computer program that permits the user to determine the minimum sample size needed for the results of a given analysis to be statistically significant. Program applications for statistical significance tests are presented and illustrated. (SLD)
Descriptors: Computer Software, Effect Size, Sample Size, Sampling
Peer reviewedVitaliano, Peter P.; Halperin, Silas – Educational and Psychological Measurement, 1975
Descriptors: Computer Programs, Hypothesis Testing, Matrices, Sampling
Peer reviewedCohen, Jacob – Educational and Psychological Measurement, 1970
Descriptors: Hypothesis Testing, Predictive Measurement, Probability, Sampling
Peer reviewedMontanelli, Richard G., Jr. – Educational and Psychological Measurement, 1974
Descriptors: Factor Analysis, Goodness of Fit, Hypothesis Testing, Reliability
Peer reviewedElster, Richard S.; Dunnette, Marvin D. – Educational and Psychological Measurement, 1971
Descriptors: Hypothesis Testing, Measurement Techniques, Probability, Sampling
Peer reviewedKirk, Roger E. – Educational and Psychological Measurement, 1996
Practical significance is concerned with whether a research result is useful in the real world. The use of procedures to supplement the null hypothesis significance test in four journals of the American Psychological Association is examined, and an approach to assessing practical significance is presented. (SLD)
Descriptors: Educational Research, Hypothesis Testing, Research Utilization, Sampling
Peer reviewedLawlis, G. Frank; Sweney, Arthur B. – Educational and Psychological Measurement, 1975
A method of applying the discriminant function to correlated samples was discussed for the researcher interested in utilizing multivariate statistics to pre-post data. By finding the linear combination that maximizes differences in the groups, the t-statistic can be computed for correlated samples. (Author)
Descriptors: Correlation, Discriminant Analysis, Hypothesis Testing, Longitudinal Studies
Peer reviewedGross, Alan L. – Educational and Psychological Measurement, 1975
Describes the MANOVA (multivariate analysis of variance) Computer Program for ascertaining whether k groups differ significantly from one another on p dependent variables. (Author/RC)
Descriptors: Analysis of Variance, Computer Programs, Groups, Hypothesis Testing
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