Count data in biology-Data transformation or model reformation?

ABSTRACT: Statistical analyses are an integral component of scientific research, and for decades, biologists have applied transformations to data to meet the normal error assumptions for F and t tests. Over the years, there has been a movement from data transformation toward model reformation-the use of non-normal error structures within the framework of the generalized linear model (GLM). The principal advantage of model reformation is that parameters are estimated on the original, rather than the transformed scale. However, data transformation has been shown to give better control over type I error, for simulated data with known error structures. We conducted a literature review of statistical textbooks directed toward biologists and of journal articles published in the primary liter

SUBMITTER: St-Pierre AP 

PROVIDER: S-EPMC5869353 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature