Multivariate models provide an effective psychometric solution to the variability in classification accuracy of D-KEFS Stroop performance validity cutoffs-Reference-Cited by-同舟云学术

Multivariate models provide an effective psychometric solution to the variability in classification accuracy of D-KEFS Stroop performance validity cutoffs

Published:2022-08-10 Issue:3 Volume:37 Page:617-649
ISSN:1385-4046
Container-title:The Clinical Neuropsychologist
language:en
Short-container-title:The Clinical Neuropsychologist

Author:

Cutler Laura¹,Greenacre Matthew²,Abeare Christopher A.¹,Sirianni Christina D.³,Roth Robert⁴,Erdodi Laszlo A.¹^ORCID

Affiliation:

1. Department of Psychology, Neuropsychology Track, University of Windsor, Windsor, Ontario, Canada

2. Schulich School of Medicine, Western University, London, Ontario, Canada

3. School of Social Work, University of Windsor, Windsor, Ontario, Canada

4. Department of Psychiatry, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA

Publisher

Informa UK Limited

Subject

Psychiatry and Mental health,Arts and Humanities (miscellaneous),Clinical Psychology,Developmental and Educational Psychology,Neuropsychology and Physiological Psychology

Link

https://www.tandfonline.com/doi/pdf/10.1080/13854046.2022.2073914

Reference156 articles.

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4. Development of embedded performance validity indicators in the NIH Toolbox Cognitive Battery.

5. Introducing a forced choice recognition trial to the Hopkins Verbal Learning Test – Revised

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