Development of discriminant functions to detect dissimulation for the Millon Clinical Multiaxial Inventory (3rd edition)

Abstract

This study investigated the ability of the MCMI-III to discriminate student dissimulators from psychiatric inpatients by re-analyzing data previously obtained by the authors. The sample consisted of 181 psychiatric inpatients and 218 college undergraduates. Students were randomized to either a fake-bad (FB) or standard instruction (SI) condition. Discriminant analyses were used to determine whether combining Scales X, Y, and Z with the clinical scales could improve the ability of the MCMI-III to identify dissimulators beyond using single scale cutoff scores. Two functions were developed. Function A yielded a positive predictive power (PPP) of 72%, a negative predictive power (NPP) of 75%, and an overall hit rate (HR) of 76%. Function B provided a PPP of 71%, a NPP of 80%, and a HR of 77%. The algorithms improved the ability of the MCMI-III correctly to identify dissimulators over any single scale cutoff score. The benefits and limitations of the discriminant functions are discussed.

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