A novel method for testing normality in a mixed model of a nested classification

DOI10.1016/J.CSDA.2005.11.014zbMath1157.62397OpenAlexW1966300531MaRDI QIDQ1010457

Peir Feng Wei, Yi-Ting Hwang

Publication date: 6 April 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2005.11.014

zbMATH Keywords

transformationsimulationsrandom effect modelnormality testShapiro-Wilk testskewness test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Monte Carlo methods (65C05)

Related Items (3)

Goodness-of-fit tests in mixed models ⋮ Testing normality in mixed models using a transformation method ⋮ Adaptive fitting of linear mixed-effects models with correlated random effects

Uses Software

• AS 128

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The conditional probability integral transformation and applications to obtain composite chi-square goodness-of-fit tests
• Some Large-Sample Tests for Nonnormality in the Linear Regression Model
• Algorithm AS 128: Approximating the Covariance Matrix of Normal Order Statistics
• Power studies of tests for uniformity, II
• An Extension of Shapiro and Wilk's W Test for Normality to Large Samples
• Empirical Bayes Estimation in Finite Population Sampling
• Error Normality Testing in a Model of Two‐Way Nested Classification
• Normality Testing in a Mixed Model of a Two‐way Nested Classification
• Omnibus test of normality using the Q statistic
• An analysis of variance test for normality (complete samples)
• An omnibus test of normality for moderate and large size samples

This page was built for publication: A novel method for testing normality in a mixed model of a nested classification