Inheritance of Properties of Normal and Non-Normal Distributions After Transformation of Scores to Ranks
This study investigated how population parameters representing heterogeneity of variance, skewness, kurtosis, bimodality, and outlier-proneness, drawn from normal and eleven non-normal distributions, also characterized the ranks corresponding to independent samples of scores. When the parameters of population distributions from which samples were drawn were different, the ranks corresponding to the same pairs of samples of scores inherited similar differences. This finding explains some known results concerning Type I error probabilities [...]
LPCM-Win 1.0: Program to analyze logistic linear model of the Rasch family
LPCM-Win 1.0 recoge las aportaciones derivadas de la investigación de Fisher [...]
Effects of measurement error in structural equation models with and without latent variables
Se estudia el efecto que presenta el error de medida aleatorio [...]
Differential Item Functioning and bias in the adaptation of two verbal tests
En este trabajo se subrayan las fases a las que [...]
Reaction Time and Cognitive Psychology: Two procedures to avoid sample size bias
Los investigadores en psicología cognitiva suelen emplear cierto número de [...]
