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Steiger, James H.; Browne, Michael W. – Psychometrika, 1984
A general procedure is provided for comparing correlation coefficients between optimal linear composites. It allows computationally efficient significance tests on independent or dependent multiple correlations, partial correlations, and canonical correlations, with or without the assumption of multivariate normality. Evidence from Monte Carlo…
Descriptors: Correlation, Hypothesis Testing, Monte Carlo Methods, Statistical Distributions

Saner, Hilary – Psychometrika, 1994
The use of p-values in combining results of studies often involves studies that are potentially aberrant. This paper proposes a combined test that permits trimming some of the extreme p-values. The trimmed statistic is based on an inverse cumulative normal transformation of the ordered p-values. (SLD)
Descriptors: Effect Size, Meta Analysis, Research Methodology, Sample Size

Kolen, Michael J.; Jarjoura, David – Psychometrika, 1987
A cubic spline method for smoothing equipercentile equating relationships under the common item nonequivalent populations design is described. Statistical techniques based on bootstrap estimation are presented for choosing an equating method/degree of smoothing. Smoothing decreases the estimate of random error but results in an increase in…
Descriptors: Analysis of Variance, Equated Scores, Error of Measurement, Estimation (Mathematics)