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Rand R. Wilcox

Affiliations: 
Psychology University of Southern California, Los Angeles, CA, United States 
Area:
Statistics, Psychometrics Psychology
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"Rand Wilcox"
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Matthew D. Multach grad student 2016- USC (PsychTree)
Pei-Chen Wu grad student 2002 USC
A. Nayena Blankson grad student 2007 USC
Tan H. Ng grad student 2008 USC
Veronica M. Stuart grad student 2008 USC
Christianne J. Lane grad student 2009 USC
T. S. Tian grad student 2009 USC

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Publications

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Wilcox RR. (2020) Inferences about which of J dependent groups has the largest robust measure of location. The British Journal of Mathematical and Statistical Psychology
Wilcox R. (2020) Bivariate Analogs of the Wilcoxon–Mann–Whitney Test and the Patel–Hoel Method for Interactions Journal of Modern Applied Statistical Methods. 18: 2-14
Wilcox R. (2019) Logistic Regression: An Inferential Method for Identifying the Best Predictors Journal of Modern Applied Statistical Methods. 17
Wilcox R. (2019) Robust ANCOVA, Curvature, and the Curse of Dimensionality Journal of Modern Applied Statistical Methods. 17
Wilcox RR. (2018) Robust regression: Testing global hypotheses about the slopes when there is multicollinearity or heteroscedasticity. The British Journal of Mathematical and Statistical Psychology
Wilcox R, Peterson TJ, McNitt-Gray JL. (2018) Data Analyses When Sample Sizes Are Small: Modern Advances for Dealing With Outliers, Skewed Distributions, and Heteroscedasticity. Journal of Applied Biomechanics. 1-4
Wilcox R. (2018) Inferences Based on Robust Regression Estimators When There Is Multicolinearity Advances in Social Sciences Research Journal. 5
Multach M, Wilcox R. (2017) Some Results on a Wilcoxon--Mann--Whitney Approach to Interactions in a Two-Way ANOVA Design. Advances in Social Sciences Research Journal. 4
Estévez-Pérez G, Andrade JM, Wilcox RR. (2016) Bootstrap Approach To Compare the Slopes of Two Calibrations When Few Standards Are Available. Analytical Chemistry. 88: 2289-95
Wilcox RR. (2016) Robust regression: an inferential method for determining which independent variables are most important Journal of Applied Statistics. 45: 100-111
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