Evidence map›Paper›PMID 39639860›Full record

ArticleJournal of young investigators2022

Statistical Analysis of Rodent Body Weight Data is Robust to Departures from Normality in Historical National Toxicology Program Studies Dated 1980-2013.

Alyssa M Taylor-LaPole, Helen C Cunny, Keith R Shockley

Abstract read
In one paragraph

Article in Journal of young investigators, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Aquatic Advancements: Refining and Validating a Zebrafish Survival Blood Collection Technique.Journal of the American Association for Laboratory Animal Science : JAALAS · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alyssa M Taylor-LaPoleVirginia Wesleyan University, Virginia Beach, VA, 23455, USA.
Helen C CunnyOffice of Program Operations, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, 27709, USA.
Keith R ShockleyBiostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA.

Funding

Intramural NIH HHS Z99 ES999999
6 · The paper itself

Abstract

Parametric statistical tests used to assess body weight changes in rodent experiments assume a normal distribution, and the actual distribution of the rodent body weights is often assumed to be approximately normal. In order for statistical tests to be deemed appropriate without routinely confirming the normal distribution for rodent body weight data, the tests must be powerful enough to detect meaningful changes even when a population deviates from a normal distribution. Here, we present a novel analysis to assess the normality of rodent body weight data for control animals in 1,386 National Toxicology Program (NTP) studies and determined how robust a set of procedures are to detect departures from normality. The distributions of terminal body weight measurements from 90 day and chronic NTP studies were evaluated for normality using graphical and statistical testing methods. The percent of studies with terminal body weights that were not normally distributed in normality tests was typically higher in 90-day studies for Fischer 344/N (F344/N) rats and B6C3F1/N (B6C3F1) mice than Harlan Sprague-Dawley (HSD) rats across all routes of administration evaluated (feed, drinking water, gavage or inhalation). Through simulation studies, the t-test indicated adequate power to detect a difference in body weights in male B6C3F1 mice and F344/N rats in 90-day studies, even under a skew normal distribution. According to these results, common parametric tests display enough power to accurately detect body weight differences from populations not following a normal distribution, confirming the general notion that the study designs are appropriately powered. In addition to providing adequate power, the False Positive Rate (FPR) was controlled around 5% in all simulations. These results suggest that parametric tests are robust enough to give reliable results of body weight analysis in NTP studies where this is an important endpoint. Therefore, parametric testing approaches are appropriate to detect body weight changes in NTP studies when body weight distributions do not deviate too far from normality. Future steps will look at the distributions of non-terminal body weights in chronic studies, organ weights, and other species and strains of rodents.

Identifiers

PMID39639860
PMCPMC11618651

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.