# A Test for Differential Ascertainment in Case-Control Studies with Application to Child Maltreatment

## TL;DR

This paper introduces a statistical test to detect differential ascertainment in case-control studies, addressing bias in odds ratio estimation caused by multiple data sources, with an application to child maltreatment death data.

## Contribution

It presents a novel method to test for differential ascertainment and demonstrates how to correct bias in odds ratio calculations in case-control studies with multiple data sources.

## Key findings

- Detected differential ascertainment by race in child maltreatment death data.
- Showed that ignoring differential ascertainment leads to biased odds ratios.
- Provided a correction method to improve estimate accuracy.

## Abstract

We propose a method to test for the presence of differential ascertainment in case-control studies, when data are collected by multiple sources. We show that, when differential ascertainment is present, the use of only the observed cases leads to severe bias in the computation of the odds ratio. We can alleviate the effect of such bias using the estimates that our method of testing for differential ascertainment naturally provides. We apply it to a dataset obtained from the National Violent Death Reporting System, with the goal of checking for the presence of differential ascertainment by race in the count of deaths caused by child maltreatment.