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Priors de potencia para modelos de variables latentes bajo tamaños de muestra pequeños
Lihan Chen1, Milica Miočević1, Carl F Falk1
1Department of Psychology, McGill University, Montreal, Qubec, Canada.
Los priors informativos mejoran el análisis bayesiano para modelos de variables latentes con muestras pequeñas. El prior de peso de Mahalanobis (MW) mejoró la convergencia, pero funcionó mal en condiciones de no intercambiabilidad, a diferencia de los priors débilmente informativos.
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