Research Topics
| H J KeselmanSummaryAffiliation: University of Manitoba Country: Canada Publications
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Detail Information
Publications
Testing treatment effects in repeated measures designs: trimmed means and bootstrappingH J Keselman
Department of Psychology, University of Manitoba, Winnipeg, Canada
Br J Math Stat Psychol 53:175-91. 2000..Neither approach particularly benefited from adopting bootstrapped critical values. Recommendations are provided to researchers regarding when each approach is best...
The analysis of repeated measures designs: a reviewH J Keselman
Department of Psychology, University of Manitoba, 190 Dysart Road, Winnipeg, Manitoba, Canada R3T 2N2
Br J Math Stat Psychol 54:1-20. 2001..Additional topics discussed include analyses for missing data and tests of linear contrasts...
The new and improved two-sample T testH J Keselman
University of Manitoba, Winnipeg, Manitoba, Canada
Psychol Sci 15:47-51. 2004..We find that a transformation for skewness combined with a bootstrap method improves Type I error control and probability coverage even if sample sizes are small...
A generally robust approach to hypothesis testing in independent and correlated groups designsH J Keselman
Department of Psychology, University of Manitoba, Winnipeg, Manitoba, Canada
Psychophysiology 40:586-96. 2003..We also illustrate, with examples from the psychophysiological literature, the use of a new computer program to obtain numerical results for these solutions...
A comparative study of robust tests for spread: asymmetric trimming strategiesH J Keselman
University of Manitoba, Winnipeg, Manitoba, Canada
Br J Math Stat Psychol 61:235-53. 2008....
A generally robust approach for testing hypotheses and setting confidence intervals for effect sizesH J Keselman
Department of Psychology, University of Manitoba, 190 Dysart Road, Winnipeg, Manitoba, Canada
Psychol Methods 13:110-29. 2008..In an online supplement, the authors use several examples to illustrate the application of an SAS program to implement these statistical methods...
Adaptive robust estimation and testingH J Keselman
Department of Psychology, University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2
Br J Math Stat Psychol 60:267-93. 2007..With regard to the power to detect non-null treatment effects, we found that the choice among the methods depended on the degree of non-normality and variance heterogeneity. Recommendations are offered...
Many tests of significance: new methods for controlling type I errorsH J Keselman
Department of Psychology, University of Manitoba, Winnipeg, Manitoba, Canada
Psychol Methods 16:420-31. 2011..05. We demonstrate with two published data sets how more hypotheses can be rejected with k-FWER methods compared to FWER control...
Robust tests for the multivariate Behrens-Fisher problemLisa M Lix
Department of Community Health Sciences, Faculty of Medicine, University of Manitoba, 408 727 McDermot Avenue, Winnipeg, Man, R3E 3P5, Canada
Comput Methods Programs Biomed 77:129-39. 2005..Recommendations are provided on the specific data-analytic conditions under which these tests should be adopted...
Effect of non-normality on test statistics for one-way independent groups designsRobert A Cribbie
Department of Psychology, York University, Toronto, Canada
Br J Math Stat Psychol 65:56-73. 2012..The results indicated that the tests based on trimmed means offer the best Type I error control and power when variances are unequal and at least some of the distribution shapes are non-normal...
Pairwise multiple comparison test procedures: an update for clinical child and adolescent psychologistsH J Keselman
Department of Psychology, University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2
J Clin Child Adolesc Psychol 33:623-45. 2004..The newer methods are intended to provide additional sensitivity to detect treatment group differences and provide tests that are robust to the effects of variance heterogeneity, nonnormality, or both...
An examination of the robustness of the empirical Bayes and other approaches for testing main and interaction effects in repeated measures designsH J Keselman
Department of Psychology, University of Manitoba, Winnipeg, Canada
Br J Math Stat Psychol 53:51-67. 2000..On the other hand, the Huynh and Keselman et al. procedures were generally robust to these same pairings of covariance matrices and group sizes...
Pairwise multiple comparisons: a model comparison approach versus stepwise proceduresRobert A Cribbie
Department of Psychology, York University, Toronto, Canada
Br J Math Stat Psychol 56:167-82. 2003..The protected version of the model selection approach selected the true model a significantly greater proportion of times than the stepwise procedures and, in most cases, was not affected by variance heterogeneity and non-normality...
Controlling the rate of Type I error over a large set of statistical testsH J Keselman
Department of Psychology, University of Manitoba, Winnipeg, Canada
Br J Math Stat Psychol 55:27-39. 2002..05 value. Accordingly, we recommend the Benjamini and Hochberg (1995, 2000) methods of Type I error control when the number of tests in the family is large...
An alternative to Cohen's standardized mean difference effect size: a robust parameter and confidence interval in the two independent groups caseJames Algina
Department of Educational Psychology, University of Florida, Gainesville, FL 32611 7047, USA
Psychol Methods 10:317-28. 2005..Over the range of distributions and effect sizes investigated in the study, coverage probability was better for the percentile bootstrap confidence interval...
Repeated measures one-way ANOVA based on a modified one-step M-estimatorRand R Wilcox
Department of Psychology, University of Southern California, Los Angeles, CA 90089, USA
Br J Math Stat Psychol 56:15-25. 2003..Methods based on a simple modification of a one-step M-estimator that address the problems with trimmed means are examined. Several omnibus tests are compared, one of which performed well in simulations, even with a sample size of 11...
Multivariate tests of means in independent groups designs. Effects of covariance heterogeneity and nonnormalityLisa M Lix
University of Manitoba
Eval Health Prof 27:45-69. 2004..A numeric example illustrates the statistical concepts that are presented and a computer program to implement these robust solutions is introduced...
Comparing measures of the 'typical' score across treatment groupsAbdul R Othman
Universiti Sains Malaysia, Malaysia
Br J Math Stat Psychol 57:215-34. 2004....
Modern robust data analysis methods: measures of central tendencyRand R Wilcox
Department of Psychology, University of Southern California, Los Angeles 90089 1061, USA
Psychol Methods 8:254-74. 2003..Some suggestions are made about how to proceed when using modern methods...
