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Data transformation, Type I error rate and power
Author(s) -
Rasmussen Jeffrey Lee
Publication year - 1989
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1989.tb00910.x
Subject(s) - type i and type ii errors , transformation (genetics) , statistics , data transformation , sample size determination , monte carlo method , statistical power , variance (accounting) , a priori and a posteriori , mathematics , power (physics) , sample (material) , econometrics , computer science , data mining , physics , biochemistry , chemistry , philosophy , accounting , epistemology , chromatography , quantum mechanics , business , data warehouse , gene
Research has shown that when an appropriate data transformation is known a priori , then it can lead to a substantial increase in power of analysis of variance while maintaining an appropriate Type I error rate. It was unknown, however, whether data transformation selected on sample characteristics would yield accurate Type I error rates and increased power. The present Monte Carlo study demonstrates that correct data transformation values could be selected on samples as small as four per group, that legitimate approaches do not inflate the nominal significance levels and that power could be increased by sample‐based transformations.