Effects of sample size and distributional assumptions on competing models of the factor structure of the PANSS and BPRS.
Int J Methods Psychiatr Res
; 26(4)2017 12.
Article
em En
| MEDLINE
| ID: mdl-27910162
ABSTRACT
Factor analytic work on the Positive and Negative Syndrome Scale (PANSS) and Brief Psychiatric Rating Scale (BPRS) has yielded varied and conflicting results. The current study explored potential causes of these discrepancies. Prior research has been limited by small sample sizes and an incorrect assumption that the items are normally distributed when in practice responses are highly skewed ordinal variables. Using simulation methodology, we examined the effects of sample size, (in)correctly specifying item distributions, collapsing rarely endorsed response categories, and four factor analytic models. The first is the model of Van Dorn et al., developed using a large integrated data set, specified the item distributions as multinomial, and used cross-validation. The remaining models were developed specifying item distributions as normal the commonly used pentagonal model of White et al.; the model of Van der Gaag et al. developed using extensive cross-validation methods; and the model of Shafer developed through meta-analysis. Our simulation results indicated that incorrectly assuming normality led to biases in model fit and factor structure, especially for small sample size. Collapsing rarely used response options had negligible effects.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Escalas de Graduação Psiquiátrica
/
Distribuições Estatísticas
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Modelos Estatísticos
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Tamanho da Amostra
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Transtornos Mentais
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Int J Methods Psychiatr Res
Assunto da revista:
PSIQUIATRIA
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Estados Unidos