Journal article
A correlated traits, correlated methods model for thin-slice child personality assessment
Psychological assessment, Vol.31(4), pp.545-556
04/2019
DOI: 10.1037/pas0000635
PMID: 30869957
Abstract
Recent research has illustrated the utility and accuracy of a thin-slice (TS) approach to child personality assessment, whereby unacquainted observers provide personality ratings of children after exposure to brief behavioral episodes. The current study sought to expand on this approach by exploring formal multitrait-multimethod (MTMM) models for child TS data comprising ratings from a comprehensive set of TS situations. Results using data from a sample of 326 community children 9-10 years of age indicated that a correlated traits, correlated methods (CTCM) model can be used to represent individual differences in children's behavior as manifest across different situations. Indicator variables derived from a CTCM differentially correlated with traditional parental ratings of behavior, moreover, and provide predictive and incremental validity regarding child competencies and behavior. Results illustrate the utility of a TS approach in the assessment of childhood personality and inform understanding of issues encountered in applying different MTMM models to these types of empirical data. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Details
- Title: Subtitle
- A correlated traits, correlated methods model for thin-slice child personality assessment
- Creators
- Jennifer L Tackett - Department of PsychologyJonas W B Lang - Department of Personnel Management, Work and Organizational PsychologyKristian E Markon - Department of PsychologyKathrin Herzhoff - Department of Psychology
- Resource Type
- Journal article
- Publication Details
- Psychological assessment, Vol.31(4), pp.545-556
- DOI
- 10.1037/pas0000635
- PMID
- 30869957
- NLM abbreviation
- Psychol Assess
- ISSN
- 1040-3590
- eISSN
- 1939-134X
- Grant note
- Sciences and Humanities Research Council of Canada
- Language
- English
- Date published
- 04/2019
- Academic Unit
- Psychological and Brain Sciences
- Record Identifier
- 9984627236902771
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