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Modeling trait and state variation using multilevel factor analysis with PANAS daily diary data.

ABSTRACT: This study used daily diary data to model trait and state Positive Affect (PA) and Negative Affect (NA) using the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). Data were collected from 364 college students over five days. Intraclass correlation coefficients suggested approximately equal amounts of variability at the trait and state levels. Multilevel factor analysis revealed that the model specifying two correlated factors (PA, NA) and correlated uniqueness terms among redundant items provided the best fit. Trait and state PA and NA were generally associated with stress, anxiety, depression, and three types of self-esteem (performance, academic, social). The coefficients describing these relationships differed somewhat, suggesting that trait and state measurement may have different predictive utility.

SUBMITTER: Merz EL

PROVIDER: S-EPMC3079913 | biostudies-other | 2011 Feb

REPOSITORIES: biostudies-other

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Modeling trait and state variation using multilevel factor analysis with PANAS daily diary data.

Merz Erin L EL Roesch Scott C SC

Journal of research in personality 20110201 1

This study used daily diary data to model trait and state Positive Affect (PA) and Negative Affect (NA) using the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). Data were collected from 364 college students over five days. Intraclass correlation coefficients suggested approximately equal amounts of variability at the trait and state levels. Multilevel factor analysis revealed that the model specifying two correlated factors (PA, NA) and correlated uniqueness term ...[more]

PMID: 21516166

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