4.1 Article

Parallel psychometric and cognitive modeling analyses of the Penn Face Memory Test in the Army Study to Assess Risk and Resilience in Servicemembers

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出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/13803395.2012.762974

关键词

Psychometric modeling; Item response theory; Cognitive modeling; Penn Face Memory Test; Army Study to Assess Risk and Resilience in Servicemembers

资金

  1. Department of the Army
  2. U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Mental Health (NIH/NIMH) [U01MH087981]

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Objective: The psychometric properties of the Penn Face Memory Test (PFMT) were investigated in a large sample (4,236 participants) of U.S. Army Soldiers undergoing computerized neurocognitive testing. Data were drawn from the initial phase of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS), a large-scale study directed towards identifying risk and resilience factors for suicidal behavior and other stress-related disorders in Army Soldiers. In this paper, we report parallel psychometric and cognitive modeling analyses of the PFMT to determine whether ability estimates derived from the measure are precise and valid indicators of memory in the Army STARRS sample. Method: Single-sample cross-validation methodology combined with exploratory factor and multidimensional item response theory techniques were used to explore the latent structure of the PFMT. To help resolve rotational indeterminacy of the exploratory solution, latent constructs were aligned with parameter estimates derived from an unequal-variance signal detection model. Results: Analyses suggest that the PFMT measures two distinct latent constructs, one associated with memory strength and one associated with response bias, and that test scores are generally precise indicators of ability for the majority of Army STARRS participants. Conclusions: These findings support the use of the PFMT as a measure of major constructs related to recognition memory and have implications for further cognitivepsychometric model development.

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