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Cálculo e Interpretación de la Fiabilidad Máxima en Modelos Bifactoriales

Sijia Li1, Victoria Savalei1

  • 1Department of Psychology, University of British Columbia, Vancouver, Canada.

Multivariate behavioral research
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PubMed
Resumen
Este resumen es generado por máquina.

Los investigadores a menudo hacen un mal uso de la fiabilidad máxima para modelos bifactoriales. Se proporcionan nuevas ecuaciones, pero los compuestos óptimos (OLC) y subcompuestos (OLSC) no son fiables para los factores de grupo, mostrando una escasa fiabilidad y problemas de interpretación.

Palabras clave:
modelo bifactorialcoeficiente Hanálisis factorial confirmatoriofiabilidad máximapuntuaciones factoriales de regresión

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Área de la Ciencia:

  • Psicometría
  • Psicología

Sus antecedentes:

  • Los modelos bifactoriales confirmatorios son comunes en psicología para constructos multidimensionales.
  • La fiabilidad máxima evalúa qué tan bien un compuesto lineal óptimo (OLC) representa una variable latente.

Objetivo del estudio:

  • Corregir la generalización inexacta del coeficiente H para modelos bifactoriales.
  • Presentar ecuaciones precisas para la fiabilidad máxima utilizando OLC y subcompuestos óptimos (OLSC).

Principales métodos:

  • Derivación de nuevas ecuaciones para la fiabilidad máxima en modelos bifactoriales.
  • Aplicación de las ecuaciones a datos simulados y reales.
  • Comparación de OLC y OLSC con otros coeficientes de fiabilidad.

Principales resultados:

  • Los OLC y OLSC no son fiables para los factores de grupo con menos de 100 indicadores.
  • Los OLC y OLSC recibieron frecuentemente pesos negativos en las simulaciones.
  • Los índices de fiabilidad máxima aún pueden evaluar la calidad del modelo bifactorial.

Conclusiones:

  • Se recomienda no utilizar OLC u OLSC como sustitutos de los factores de grupo debido a la escasa fiabilidad y los desafíos de interpretación.
  • Se destaca la importancia de cálculos precisos de fiabilidad máxima para modelos bifactoriales.