Worst Case Resistance Testing: A Nonresponse Bias Solution for Today's Behavioral Research Realities

TL;DR

This paper introduces worst-case resistance testing (WCRT), a novel nonresponse bias assessment method using meta-analytical techniques, to evaluate how nonrespondents could impact behavioral research results.

Contribution

It develops a general WCRT method with variants for means and correlations, enabling precise nonresponse risk assessment in diverse data collection scenarios.

Findings

WCRT can identify nonresponse risks effectively.

The method complements wave analysis for bias detection.

Application on a behavioral survey demonstrates practical utility.

Abstract

This study proposes a method of nonresponse assessment based on meta-analytical file-drawer techniques, also known as worst-case resistance testing (WCRT), and suitable for a wide range of data collection scenarios. A general method is devised to estimate the number of significantly different nonrespondents it would take to significantly alter the results of an analysis. Estimates of nonrespondents can be plotted against effect sizes using "n-curves", with similar interpretation to p-curves or power curves. Variants of the general method are derived for tests of means and correlations. A sample using a well-established survey instrument from previous behavioral research is used to test the method. The results suggest that employing worst-case resistance testing can be used on its own or in conjunction with wave analysis to precisely flag nonresponse risks.