Análisis intra: Sesión de la extinción del condicionamiento pavloviano de miedo usando regresión robusta

• Autores: Jaime R. Robles, Cristina Vargas Irwin
• Localización: Suma Psicológica, ISSN-e 0121-4381, Vol. 17, Nº. 1, 2010, págs. 23-34
• Idioma: español
• Títulos paralelos:
  • Within: Session of the extinction of pavlovian fear-conditioning using robust regression
• Enlaces
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• Resumen
  • español

    El análisis de datos de extinción en experimentos de miedo condicionado ha involucrado, tradicionalmente, el uso de modelos lineales estándar, primordialmente ANOVA de diferencias entre grupos de sujetos sometidos a diferentes protocolos de extinción, manipulaciones farmacológicas o algún otro tratamiento.

    Aún cuando algunos estudios reportan diferencias individuales en indicadores como tasas de supresión o porcentajes de congelamiento, esas diferencias no son incluidas en el análisis estadístico. Los patrones de respuesta intra-sujeto son entonces promediados usando ventanas temporales de baja resolución, las cuales pueden ignorar esta dinámica del desempeño individual. Este trabajo ilustra un procedimiento analítico alternativo que consta de 2 pasos: estimación de la tendencia para los datos intra-sesión y el análisis de las diferencias entre-grupo usando la tendencia como variable de respuesta. Este procedimiento se pone a prueba usando datos reales de extinción de miedo condicionado, comparando estimaciones de tendencia robusta vía Mínimos Cuadrados Medianos con Mínimos Cuadrados Ordinarios, y comparando las diferencias de grupo usando la pendiente robusta versus la mediana del porcentaje de congelamiento como variable dependiente.

  • English

    Traditionally , the analysis of extinction data in fear conditioning experiments has involved the use of standard linear models, mostly ANOVA of between-group differences of subjects that have undergone different extinction protocols, pharmacological manipulations or some other treatment. Although some studies report individual differences in quantities such as suppression rates or freezing percentages, these differences are not included in the statistical modeling. Withinsubject response patterns are then averaged using coarse-grain time windows which can overlook these individual performance dynamics. Here we illustrate an alternative analytical procedure consisting of 2 steps: the estimation of a trend for within-session data and analysis of group differences in trend as main outcome.

    This procedure is tested on real fear-conditioning extinction data, comparing trend estimates via Ordinary Least Squares (OLS) and robust Least Median of Squares (LMS) regression estimates, as well as comparing between-group differences and analyzing mean freezing percentage versus LMS slopes as outcomes.

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