# Pair‐Feeding Study Designs Can Create Biases and Inflate Type I Error Rates: A Simulation Study

## TL;DR

Pair-feeding study designs can lead to incorrect conclusions due to inflated error rates, but adjusting for food intake in analysis can fix this issue.

## Contribution

This study quantifies how pair-feeding can inflate type I error rates and shows that adjusting for food intake mitigates this bias.

## Key findings

- Both individual and group pair-feeding increased type I error rates from 0.12 to 0.71 in unadjusted models.
- Adjusting for food intake in statistical analysis reduced error rates to the expected 0.05 level.
- Pair-feeding can lead to false positive results if food intake is not accounted for in the analysis.

## Abstract

Pair‐feeding is a study design element where one group's food intake is provided to another group to assess whether a treatment effect is independent of food intake. Investigators often assume equivalent food intake across experimental conditions and exclude it from the statistical analysis. However, the impact of this practice on type I error (T1Er) rates has not been quantified.

We conducted a Monte Carlo simulation in which animals were assigned baseline weights and food intakes, then randomized to non‐pair‐fed or pair‐fed groups. Daily food intake for both groups was initially drawn from the baseline food intake distribution. For pair‐fed animals, food intake was truncated if it exceeded the previous day's intake of the matched non‐pair‐fed animal (individual pair‐feeding) or the group's average (group pair‐feeding). Weight changes were calculated as a function of food intake, and final weight change was analyzed with and without adjusting for mean food intake.

Both individual and group pair‐feeding inflated T1Er rates ranging from 0.12 to 0.71 in unadjusted models. However, adjustment for food intake reduced error rates to around 0.05.

Under some circumstances, pair‐feeding designs can inflate T1Er rates. Investigators can mitigate this inflation by adjusting the analyses for food intake.