NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 7 results Save | Export
Two-Sample, Bivariate Hypothesis Testing Methods Based on Tukey's Depth.
Peer reviewed Peer reviewed
Wilcox, 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
A Bootstrap Modification of the Alexander-Govern ANOVA Method, Plus Comments on Comparing Trimmed Means.
Peer reviewed Peer reviewed
Wilcox, Rand R. – Educational and Psychological Measurement, 1997
Some results on how the Alexander-Govern heteroscedastic analysis of variance (ANOVA) procedure (R. Alexander and D. Govern, 1994) performs under nonnormality are presented. This method can provide poor control of Type I errors in some cases, and in some situations power decreases as differences among the means get large. (SLD)
Descriptors: Analysis of Variance, Error of Measurement, Power (Statistics), Statistical Distributions
A One-Way Random Effects Model for Trimmed Means.
Peer reviewed Peer reviewed
Wilcox, Rand R. – Psychometrika, 1994
A generalization of the usual random-effects model based on trimmed means is proposed. The resulting test of no differences among J randomly sampled groups has advantages in terms of Type I errors and can yield gains in power when distributions have heavy tails and outliers. (SLD)
Descriptors: Analysis of Variance, Equations (Mathematics), Models, Power (Statistics)
Approximating the Probability of Selecting the Best Treatment with a Heteroscedastic Procedure When the First Stage Has Unequal Sample Sizes.
Peer reviewed Peer reviewed
Wilcox, Rand R. – Journal of Educational Statistics, 1983
The problem of determining which of several populations has the largest mean is considered. The procedure described by Dudewicz and Dalal is extended to the case of unequal sample sizes. (JKS)
Descriptors: Analysis of Variance, Nonparametric Statistics, Probability, Reliability
Comparing One-Step M-Estimators of Location Corresponding to Two Independent Groups.
Peer reviewed Peer reviewed
Wilcox, Rand R. – Psychometrika, 1992
A method of comparing one-step M-estimates of location for heavy tailed distributions is proposed and investigated. Simulations indicate that the new procedure provides good control over Type I errors and has more power than do some other methods for dealing with heavy tailed distributions. (SLD)
Descriptors: Comparative Analysis, Estimation (Mathematics), Experimental Groups, Mathematical Models
Comparing One-Step M-Estimators of Location When There Are More than Two Groups.
Peer reviewed Peer reviewed
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)
Comparing Medians: A Monte Carlo Study.
Peer reviewed Peer reviewed
Wilcox, Rand R.; Charlin, Ventura L. – Journal of Educational Statistics, 1986
This paper investigates three methods for comparing medians rather than means in studying two independent treatment groups. The method that gave the best results is based on a normal approximation of the distribution of the sample median where the variance is estimated using results reported by Maritz and Jarrett. (Author/JAZ)
Descriptors: Comparative Analysis, Computer Simulation, Computer Software, Equations (Mathematics)