Statistical Power in Experimental Audit Studies: Cautions and Calculations for Matched Tests With Nominal Outcomes

• NCJ Number: 249088
• Journal: Sociological Methods Research Volume: 45 Issue: 2 Dated: May 2016 Pages: 260-303
• Author(s): Mike Vuolo; Christopher Uggen; Sarah Lageson
• Date Published: May 2016
• Length: 44 pages
• Grant Number(s): 2007-IJ-CX-0042
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored)

Annotation

This article presents sample size and power calculations for McNemar's test using empirical data from an audit study on misdemeanor arrest records and employability, and formulas and examples are then provided for cases involving more than two treatments (Cochran's Q test) and nominal outcomes (Stuart-Maxwell test). Recommendations concerning power and sample size are provided for researchers designing and presenting matched audit studies.

Abstract

Given their capacity to identify causal relationships, experimental audit studies have grown increasingly popular in the social sciences. Typically, investigators send fictitious auditors who differ by a key factor (e.g., race) to particular experimental units (e.g., employers) and then compare treatment and control groups on a dichotomous outcome (e.g., hiring). In such scenarios, an important design consideration is the power to detect a certain magnitude difference between the groups. But power calculations are not straightforward in standard matched tests for dichotomous outcomes. Given the paired nature of the data, the number of pairs in the concordant cells (when neither or both auditor receives a positive response) contributes to the power, which is lower as the sum of the discordant proportions approaches one. Because these quantities are difficult to determine a priori, researchers must exercise particular care in experimental design. This article provides guidance on this issue. (Publisher abstract modified)