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Juyoung Jung1, Ariel M Aloe1

  • 1Educational Measurement and Statistics University of Iowa Iowa City Iowa USA.

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Ver abstracta en PubMed

Resumen
Este resumen es generado por máquina.

Este estudio introduce diferencias medias estandarizadas armonizadas (HSMD) para abordar las distorsiones en los metanálisis causadas por la variabilidad de la muestra. Los HSMD ofrecen un nuevo análisis de sensibilidad para una estimación más confiable del tamaño del efecto y conclusiones metaanalíticas sólidas.

Palabras clave:
coeficiente de variaciónArmonización de los datosTamaño del efectoMetanálisisDiferencias medias estandarizadas

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Área de la Ciencia:

  • Estadísticas biológicas
  • Metodología de la investigación médica

Sus antecedentes:

  • Las diferencias medias estandarizadas (SMD), como la d de Cohen y la g de Hedges, son comunes en los metanálisis, pero son sensibles a la variabilidad dentro del estudio.
  • Esta sensibilidad puede distorsionar las estimaciones del tamaño del efecto individual e impactar en los hallazgos metaanalíticos generales.

Objetivo del estudio:

  • Introducir diferencias medias estandarizadas armonizadas (HSMD) como un nuevo marco de análisis de sensibilidad.
  • Evaluar y abordar las distorsiones en los tamaños de efecto del metanálisis causadas por la variabilidad de la muestra dentro del estudio.
  • Mejorar la exhaustividad de la síntesis metaanalítica.

Principales métodos:

  • Armonizar la variabilidad relativa dentro de los estudios utilizando el coeficiente de variación (CV) para establecer puntos de referencia empíricos.
  • Se recalcularán las DME bajo supuestos de variabilidad coherentes.
  • Aplicar el marco HSMD a los datos metaanalíticos para evaluar la influencia de las desviaciones estándar específicas del estudio.

    • Principales resultados:

    • Demostrar en qué medida los tamaños de los efectos originales y los resultados agrupados están influenciados por la variabilidad inicial de la estandarización.
    • Cuantificar el impacto de la variabilidad dentro del estudio en los resultados metaanalíticos.
    • Mostrar la capacidad del marco para incorporar estudios que carecen de métricas de variabilidad reportadas.

    Conclusiones:

    • Los HSMD proporcionan un método sólido para evaluar la sensibilidad a la variabilidad dentro del estudio en los metanálisis.
    • Este nuevo marco mejora la fiabilidad de la estimación del tamaño del efecto y las conclusiones metaanalíticas.
    • El enfoque HSMD mejora la síntesis metaanalítica al acomodar diversos datos del estudio.