ArticleBehavior genetics2009
Rank-based inverse normal transformations are increasingly used, but are they merited?
Article in Behavior genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 163 papers, 1 of them a synthesis that pooled it.
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Who cites it
163 citing papers in PubMed, 1 synthesis or guideline pooled it, 333 citations in OpenAlex.
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- Evaluation of Statistical Methods for Clustered Eye Data with Skewed Distribution.Ophthalmology science · 2026Article
103 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Many complex traits studied in genetics have markedly non-normal distributions. This often implies that the assumption of normally distributed residuals has been violated. Recently, inverse normal transformations (INTs) have gained popularity among genetics researchers and are implemented as an option in several software packages. Despite this increasing use, we are unaware of extensive simulations or mathematical proofs showing that INTs have desirable statistical properties in the context of genetic studies. We show that INTs do not necessarily maintain proper Type 1 error control and can also reduce statistical power in some circumstances. Many alternatives to INTs exist. Therefore, we contend that there is a lack of justification for performing parametric statistical procedures on INTs with the exceptions of simple designs with moderate to large sample sizes, which makes permutation testing computationally infeasible and where maximum likelihood testing is used. Rigorous research evaluating the utility of INTs seems warranted.
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