1968
DOI: 10.2307/2284037
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Robustness of the F-Test to Errors of Both Kinds and the Correlation Between the Numerator and Denominator of the F-Ratio

Abstract: JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship.In this study of robustness the insensitivity of the F-test between means to its underlying assumptions (normally distributed populations with equal variances) is investigated. Using two nonnormal distributions (exponential and lognormal), it is… Show more

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Cited by 86 publications
(74 citation statements)
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“…Given the robust nature of the repeated measures ANOVA to violations of normality under the central limit theorem (Donaldson, 1968; Norman, 2010), we performed a repeated measures ANOVA with time (T1–T5) as within-subject variables and SCL-90 as the dependent variable. We also performed a non-parametric test (Friedman) to see whether its results confirmed the outcome of the repeated measures ANOVA.…”
Section: Resultsmentioning
confidence: 99%
“…Given the robust nature of the repeated measures ANOVA to violations of normality under the central limit theorem (Donaldson, 1968; Norman, 2010), we performed a repeated measures ANOVA with time (T1–T5) as within-subject variables and SCL-90 as the dependent variable. We also performed a non-parametric test (Friedman) to see whether its results confirmed the outcome of the repeated measures ANOVA.…”
Section: Resultsmentioning
confidence: 99%
“…In experimental research, in which the predictors in the linear model represent groups of people in different treatment conditions, the 'overall fit of the model' becomes a test of whether group means differ. Early work suggested that F controls the Type I error rate under conditions of skew when group sizes are equal (Donaldson, 1968;Glass, Peckham, & Sanders, 1972). However, more recent investigations revealed that differences in skewness, non-normality and heteroscedasticity interact in complicated ways that impact power (Wilcox, 2017).…”
Section: Misconceptions About Robustnessmentioning
confidence: 99%
“…To estimate the influence that inequality of model means and the observational mean have on the validity of 176 using equation 3, we use equation 2.1 from Donaldson (1968), with the observational database taken as the "parent" …”
mentioning
confidence: 99%