Potencia estadística y cálculo del tamaño del efecto en G*Power: complementos a las pruebas de significación estadística y su aplicación en psicología.
DOI:
https://doi.org/10.22199/S07187475.2014.0002.00006Palabras clave:
Inferencia estadística, potencia estadística, tamaño del efecto, Statistical inference, statistical power analysis, effect size,Resumen
El uso de pruebas de significación estadística es una estrategia que se encuentra muy arraigada en la investigación psicológica. Sin embargo, se han sobrevalorado las bondades de dichas pruebas al considerarlas como un indicador suficiente de la veracidad de una hipótesis, omitiendo la cuantificación de las diferencias encontradas. Así, las conclusiones resultan erróneas al homologar diferencia significativa con diferencia “grande”, “importante” o “relevante”. Dada la creciente importancia de los indicadores del tamaño del efecto y la potencia estadística, en este artículo desarrollamos un breve marco conceptual del análisis estadístico de la potencia y el tamaño del efecto, así como ejemplos prácticos de su cálculo utilizando el programa G*Power 3.1.6, para estimular y facilitar su inclusión en futuras publicaciones.
The use of statistical significance test is deeply rooted in psychological research. However, it has been on estimating the benefits of such tests considering itself a sufficient indicator of the accuracy of a hypothesis. It has tended to ignore the quantification of the differences found and has tended to draw the wrong conclusions to approve significant difference with "large", “important” or "relevant" difference. Given the increasing importance of indicators of effect size and statistical power, in this article we provide a brief conceptual framework of the statistical analysis of the power and effect size and practical examples of its calculation using the program G * Power 3.1.6 to help alleviate the lack of many researchers of how to perform such analyzes
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