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Fowler, Robert L. – Educational and Psychological Measurement, 1984
This study compared two approximations for normalizing noncentral F distributions: one based on the square root of the chi-square distribution (SRA), the other derived from a cube root of the chi-square distribution (CRA). The CRA was superior, and generally provided an excellent approximation for noncentral F. (Author/BW)
Descriptors: Estimation (Mathematics), Hypothesis Testing, Mathematical Formulas, Probability
Peer reviewed Peer reviewed
Palachek, Albert D.; Schucany, William R. – Psychometrika, 1984
The use of U-statistics based on rank correlation coefficients in estimating the strength of concordance among a group of rankers is examined for cases where the null hypothesis of random rankings is not tenable. (Author/BW)
Descriptors: Correlation, Estimation (Mathematics), Hypothesis Testing, Interrater Reliability
Peer reviewed Peer reviewed
Becker, Betsy Jane – Journal of Educational Statistics, 1991
The observed probability "p" is the social scientist's primary tool for evaluating the outcome of statistical hypothesis tests. The small-sample accuracy of nonnull asymptotic distributions of several functions of "p" was studied. Implications for use of the approximations are discussed. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Hypothesis Testing, Mathematical Models
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Wilcox, Rand R. – Psychometrika, 1993
Modifications are proposed to the recently developed method of comparing one-step M-estimators of location corresponding to two independent groups that provides good control over the probability of Type I error even for unequal sample size, unequal variances, and different shaped distributions. Simulation results reveal cautions required. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
Lunneborg, Clifford E. – 1983
The wide availability of large amounts of inexpensive computing power has encouraged statisticians to explore many approaches to a basis for inference. This paper presents one such "computer-intensive" approach: the bootstrap of Bradley Efron. This methodology fits between the cases where it is assumed that the form of the distribution…
Descriptors: Analysis of Variance, Error of Measurement, Estimation (Mathematics), Hypothesis Testing