Effects of survey design features on response rates: a meta-analytical approach using the example of crime surveys

TL;DR

This study uses meta-analysis to examine how different survey design features influence response rates in crime surveys, providing insights for designing more effective surveys.

Contribution

It offers a systematic analysis of survey design features' effects on response rates using meta-regression on German crime surveys from 2001-2021.

Findings

Certain survey design features significantly impact response rates.

Professional survey administration correlates with higher response rates.

The developed model can predict response rates based on design choices.

Abstract

When conducting a survey, many choices regarding survey design features have to be made. These choices affect the response rate of a survey. This paper analyzes the individual effects of these survey design features on the response rate. For this purpose, data from a systematic review of crime surveys conducted in Germany between 2001--2021 were used. First, a meta-analysis of proportions is used to estimate the summary response rate. Second, a meta-regression was fitted, modeling the relationship between the observed response rates and survey-design features, such as the study year, target population, coverage area, data collection mode, and institute. The developed model informs about the influence of certain survey design features and can predict the expected response rate when (re-) designing a survey. This study highlights that a thoughtful survey design and professional survey administration can result in high response rates.