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

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.