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Comparison of factor analysis models applied to the NCANDA neuropsychological test battery

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Listed:
  • Kevin M Cummins
  • Eileen V Pitpitan
  • Ty Brumback
  • Tyler M Moore
  • Ryan S Trim
  • Duncan B Clark
  • Sandra A Brown
  • Susan F Tapert

Abstract

The factor structure of neuropsychological functioning among a large sample (N = 831) of American youth (ages 12–21 at baseline) was investigated in order to identify an optimal model. Candidate models were selected based on their potential to provide service to the study of adolescent development and the effects of heavy episodic alcohol consumption. Data on neuropsychological functioning were obtained from the NCANDA study. This is a longitudinal community study of the effects of alcohol exposure on neurodevelopment. Three conceptually motivated and one empirically motivated factor analysis model of neuropsychological domains were compared based on penalized-likelihood selection criteria and model fit statistics. Two conceptually-motivated models were found to have adequate fit and pattern invariance to function as a measurement model for the Penn Computerized Neurocognitive Battery (Penn CNB) anchored neuropsychological battery in NCANDA. Corroboration of previous factor analysis models was obtained, in addition to the identification of an alternative factor model that has higher discriminant capacity for neuropsychological domains hypothesized to be most sensitive to alcohol exposure in human adolescents. The findings support the use of a factor model developed originally for the Penn CNB and a model developed specifically for the NCANDA project. The NCANDA 8-Factor Model has conceptual and empirical advantages that were identified in the current and prior studies. These advantages are particularly valuable when applied in alcohol research settings.

Suggested Citation

  • Kevin M Cummins & Eileen V Pitpitan & Ty Brumback & Tyler M Moore & Ryan S Trim & Duncan B Clark & Sandra A Brown & Susan F Tapert, 2022. "Comparison of factor analysis models applied to the NCANDA neuropsychological test battery," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-22, February.
  • Handle: RePEc:plo:pone00:0263174
    DOI: 10.1371/journal.pone.0263174
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    References listed on IDEAS

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    2. Sylvain Weber, 2010. "bacon: An effective way to detect outliers in multivariate data using Stata (and Mata)," Stata Journal, StataCorp LP, vol. 10(3), pages 331-338, September.
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