ArticleBirth defects research2020
Analysis of proportional data in reproductive and developmental toxicity studies: Comparison of sensitivities of logit transformation, arcsine square root transformation, and nonparametric analysis.
Article in Birth defects research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
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- Developmental Toxicity of Disinfection Byproducts in F344 Rats: Effects on Pregnancy Maintenance and Eye Development.Birth defects research · 2025Article
- Effects of low-level laser therapy on impaired mobility in dogs with naturally occurring osteoarthritis.Veterinary medicine and science · 2023Article
- Impacts of dietary supplementation of bamboo vinegar and charcoal powder on growth performance, intestinal morphology, and gut microflora of large-scale loachJournal of oceanology and limnology · 2023Article
- Analysis of incidence data in developmental toxicity studies: Statistical tests to account for litter effects in fetal defect data.Birth defects research · 2023Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundIn developmental and reproductive toxicity studies, analysis of litter-based binary endpoints (e.g., incidence of malformed fetuses) is complex in that littermates often are not entirely independent of one another. It is well established that the litter, not the individual fetus, is the proper independent experimental unit in statistical analysis. Accordingly, analysis is often based on the proportion affected per litter and the litter proportions are analyzed as continuous data. Because these proportional data generally do not meet assumptions of symmetry or normality, data are typically analyzed by nonparametric methods, arcsine square root transformation, or logit transformation.
methodsWe conducted power calculations to compare different approaches (nonparametric, arcsine square root-transformed, logit-transformed, untransformed) for analyzing litter-based proportional data. A reproductive toxicity study with a control and one treated group provided data for two endpoints: prenatal loss, and fertility by in utero insemination (IUI). Type 1 error and power were estimated by 10,000 simulations based on two-sample one-tailed t tests with varying numbers of litters per group. To further compare the different approaches, we conducted additional analyses with shifted mean proportions to produce illustrative scenarios.
resultsAnalyses based on logit-transformed proportions had greater power than those based on untransformed or arcsine square root-transformed proportions, or nonparametric procedures.
conclusionThe logit transformation is preferred to the other approaches considered when making inferences concerning litter-based proportional endpoints, particularly with skewed distributions. The improved performance of the logit transformation becomes increasingly pronounced as the response proportions are increasingly close to the boundaries of the parameter space.
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