A Bayesian Approach to Mixed Group Validation of Performance Validity Tests

31 Pages Posted: 15 Aug 2014 Last revised: 24 Apr 2015

See all articles by Douglas Mossman

Douglas Mossman

University of Cincinnati College of Medicine

William Miller

Henry Ford Health System

Elliot Lee

University of Wisconsin - Madison - School of Medicine and Public Health

Roger Gervais

University of Alberta - Neurobehavioural Associates

Kathleen Hart

Xavier University

Dustin Wygant

Eastern Kentucky University - Department of Psychology

Date Written: November 10, 2014

Abstract

Mental health professionals often use structured assessment tools to help detect individuals who are feigning or exaggerating symptoms. Yet estimating the accuracy of these tools is problematic because no “gold standard” establishes whether someone is malingering or not. Several investigators have recommended using mixed-group validation (MGV) to estimate the accuracy of malingering measures, but simulation studies show that typical implementations of MGV may yield vague, biased, or logically impossible results.

This article describes a Bayesian approach to MGV that addresses and avoids these limitations. After explaining the concepts that underlie our approach, we use previously published data on the Test of Memory Malingering (TOMM; Tombaugh, 1996) to illustrate how our method works. Our findings concerning the TOMM’s accuracy, which include insights about covariates such as study population and litigation status, are consistent with results that appear in previous publications. Unlike most investigations of the TOMM’s accuracy, this article’s findings neither rely on possibly flawed assumptions about subjects’ intentions nor assume that experimental simulators can duplicate the behavior of real-world evaluees. Our conceptual approach may prove helpful in evaluating the accuracy of many assessment tools used in clinical contexts and psycholegal determinations.

Keywords: mixed group validation, Bayesian estimation, WinBUGS, diagnostic accuracy, TOMM

JEL Classification: C11

Suggested Citation

Mossman, Douglas and Miller, William and Lee, Elliot and Gervais, Roger and Hart, Kathleen and Wygant, Dustin, A Bayesian Approach to Mixed Group Validation of Performance Validity Tests (November 10, 2014). Available at SSRN: https://ssrn.com/abstract=2479976 or http://dx.doi.org/10.2139/ssrn.2479976

Douglas Mossman (Contact Author)

University of Cincinnati College of Medicine ( email )

260 Stetson Street, Suite 3200
P. O. Box 670559
Cincinnati, OH 45219
United States
513-558-4423 (Phone)

William Miller

Henry Ford Health System ( email )

Detroit, MI 48202-3450
United States

Elliot Lee

University of Wisconsin - Madison - School of Medicine and Public Health ( email )

Madison, WI 53711
United States

Roger Gervais

University of Alberta - Neurobehavioural Associates

Alberta
Canada

Kathleen Hart

Xavier University ( email )

Cincinnati, OH 45207
United States

Dustin Wygant

Eastern Kentucky University - Department of Psychology

Combs 317
Richmond, KY 40475
United States

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