Title
An algorithm for estimating Box-Cox transformation parameter in ANOVA.
Abstract
In this study, we construct a feasible region, in which we maximize the likelihood function, by using Shapiro-Wilk and Bartlett's test statistics to obtain Box-Cox power transformation parameter for solving the issues of non-normality and/or heterogeneity of variances in analysis of variance (ANOVA). Simulation studies illustrate that the proposed approach is more successful in attaining normality and variance stabilization, and is at least as good as the usual maximum likelihood estimation (MLE) in estimating the transformation parameter for different conditions. Our proposed method is illustrated on two real-life datasets. Moreover, the proposed algorithm is released under R package AID under the name of "boxcoxfr" for implementation.
Year
DOI
Venue
2017
10.1080/03610918.2016.1204458
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
Keywords
Field
DocType
Data transformation,Homogeneity test,Normality test,Searching algorithms,Statistical software
Econometrics,Normality test,Likelihood function,Power transform,Algorithm,ANOVA on ranks,Feasible region,Brown–Forsythe test,Statistics,Variance-stabilizing transformation,Mathematics,Statistical hypothesis testing
Journal
Volume
Issue
ISSN
46
8
0361-0918
Citations 
PageRank 
References 
0
0.34
2
Authors
2
Name
Order
Citations
PageRank
Osman Dag101.69
Özlem İlk284.47