Publications & preprints

Nonparametric Tests for Interaction in Two-Way ANOVA with Balanced Replications

Bao Khue Tran, Amy S. Wagaman, Andrew Nguyen, David Jacobson, Bradley Hartlaub

2024 misc

Abstract

Nonparametric procedures are more powerful for detecting interaction in two-way ANOVA when the data are non-normal. In this paper, we compute null critical values for the aligned rank-based tests (APCSSA/APCSSM) where the levels of the factors are between 2 and 6. We compare the performance of these new procedures with the ANOVA F-test for interaction, the adjusted rank transform test (ART), Conover's rank transform procedure (RT), and a rank-based ANOVA test (raov) using Monte Carlo simulations. The new procedures APCSSA/APCSSM are comparable with existing competitors in all settings. Even though there is no single dominant test in detecting interaction effects for non-normal data, nonparametric procedure APCSSM is the most highly recommended procedure for Cauchy errors settings.

Talks

A Statistical Framework for Data Streams talk
  • Confirmation of Candidature Talk, UNSW Statistics Seminar Series April 26, 2026
Where is Markov heading? A Markov Chain’s Stationary Distribution poster
  • Senior Mathematics & Statistics Poster Symposium, Gambier, OH December 3, 2024
Comparing Nonparametric Tests for Interaction in Two-way ANOVA with Balanced Replications talkposter
  • Electronic Undergraduate Statistics Research Conference (eUSR) November 28, 2024 Talk
  • Summer Science Scholars Research Showcase, Gambier, OH October 13, 2023 Poster
  • WIMIN (Women in Mathematics in New England) Conference 2023, Northampton, MA September 23, 2023 Talk

Conferences

Grants & awards

Further details