Smooth Tests for Normality in ANOVA

33 Pages Posted: 11 Oct 2021

See all articles by Haoyu Wei

Haoyu Wei

Peking University - Guanghua School of Management

Xiaojun Song

Peking University - Guanghua School of Management

Date Written: October 10, 2021

Abstract

The normality assumption for errors in the Analysis of Variance (ANOVA) is common when using ANOVA models. But there are few people to test this normality assumption before using ANOVA models, and the existent literature also rarely mentions this problem. In this article, we propose an easy-to-use method to testing the normality assumption in ANOVA models by using smooth tests. The test statistic we propose has asymptotic chi-square distribution and our tests are always consistent in various different types of ANOVA models. Discussion about how to choose the dimension of the smooth model (the number of the basis functions) are also included in this article. Several simulation experiments show the superiority of our method.

Keywords: ANOVA, estimation effect, smooth tests.

JEL Classification: C12; C14; C15

Suggested Citation

Wei, Haoyu and Song, Xiaojun, Smooth Tests for Normality in ANOVA (October 10, 2021). Available at SSRN: https://ssrn.com/abstract=3939957 or http://dx.doi.org/10.2139/ssrn.3939957

Haoyu Wei (Contact Author)

Peking University - Guanghua School of Management ( email )

Peking University
Beijing, Beijing 100871
China

Xiaojun Song

Peking University - Guanghua School of Management ( email )

Peking University
Beijing, Beijing 100871
China

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