N = 1 Designs: The Failure of ANOVA-Based Tests

↵TOOTHAKER, LARRY E. Professor, Department of Psychology, University of Oklahoma, Norman, OK 73019.Specializations: Randomization tests, individual comparisons, robustness.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Guardrail end accident analysis (FHWA-OK-92-09) 2190

This study documented attributes associated with guardrail end accidents on Oklahoma Department of Transportation (ODOT) roadways. The database which the researchers studied included accidents at a variety of guardrail end types, but most ends were either exposed or turned-down. The s everity of exposed and of turned-down guardrail end accidents in relation to lateral location of the guardrail, to vehicle rolling and vaulting, and to vehicle weight was investigated. Each acc ident report was read carefully to obtain relevant information for analyses. The results showed that on divided roads, vehicles struck median guardrail ends as often as right-side ends. On undivided roadways, right-side ends were struck 60% of the time. Fatalities or incapacitating injuries occurred in 1/6 of the end accidents. The vehicle vaulted or rolled in about 1/4 of the guardrail end accidents. The research indicated that turned-down guardrail end accidents had more vehicle rolling and/or vaulting than did exposed end accidents. Driver inattention was a factor in 1/3 of all guardrail end accidents. The majority of guardrail end accidents on the state system occurred on a small portion of the system, namely the higher volume roadways. The researchers sugge sted that accident reporting methods be enhanced, and that rumble strips be tested as a means to reduce guardrail end strike accidents. If newer, more expensive end treatments were installed, locating the new guardrail ends on a small portion of the system could address a maj ority of the end accident sites.Final Report, November 1991-December 1992N

On “The Analysis of Ranked Data Derived from Completely Randomized Factorial Designs”

Extensions of the Kruskal-Wallis procedure for a factorial design are reviewed and researched under various degrees and kinds of nonnullity. It was found that the distributions of these test statistics are a Function of effects other than those being tested except under the completely null situation and their use is discouraged.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Comparison of Tukey's T-Method and Scheffé's S-Method for Various Numbers of All Possible Differences of Averages Contrasts Under Violation of Assumptions

Empirical .05 and .01 rates of Type I error were compared for the Tukey and Scheffé multiple comparison techniques. The experimentwise error rate was defined over five sets of the all possible 25 differences of averages contrasts. The robustness of the Tukey and Scheffé statistics was not only related to the type of assumption violation, but also to the sets containing different numbers of contrasts. The Tukey method could be judged as robust a statistic as the Scheffé method.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Nonparametric Competitors to the Two-Way ANOVA

↵LARRY E. TOOTHAKER is David Ross Boyd Professor of Psychology at the University of Oklahoma, Norman, OK 73019. He specializes in robustness of ANOVA, including repeated measures designs, multiple comparison procedures, and nonparametrics.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

An Empirical Comparison of the Anova F-Test, Normal Scores Test and Kruskal-Wallis Test Under Violation of Assumptions

The present research compares the ANOVA F-test, the Kruskal-Wallis test, and the normal scores test in terms of empirical alpha and empirical power with samples from the normal distribution and two exponential distributions. Empirical evidence supports the use of the ANOVA F-test even under violation of assumptions when testing hypotheses about means. If the researcher is willing to test hypotheses about medians, the Kruskal-Wallis test was found to be competitive to the F-test. However, in the cases investigated, the normal scores test was not consistently better than the F-test or the Kruskal-Wallis test and could not be recommended on the basis of this research.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline