Robustness of confirmatory factor analysis fit indices to outliers

 

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Autor: Rojas-Torres, Luis
Formato: artículo original
Estado:Versión publicada
Fecha de Publicación:2020
Descripción:The goal of this work is to evaluate the robustness of several Confirmatory Factor Analysis fit indices (SRMR, RMSEA, TLI, CFI and GFI) to the precense of outliers. For this purpose, it was planed a simulation study with   3 × 4 × 2 conditions: sample size (100, 200 and 500), outliers percentage (0%, 1%, 5% and 10%) and number of variables with outliers (1 and 2). The baseline data sets (0% of outliers) by sample size were simulated from a distribution which fit to a CFA with three factors correlated. Data bases with outliers were created from substitution of observations in baseline data sets. Later, in every data base was estimated a CFA with three factors correlated. It was obtained that all indices with classical cutoffs were robust to outliers with sample sizes of 200 and 500. With 100 observations, it was obtained that fit indexes were robust to outliers, butconsidering cutoffs adjusted by the factorial structure and the sample size.
País:Portal de Revistas UCR
Institución:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
Lenguaje:Español
OAI Identifier:oai:portal.ucr.ac.cr:article/33677
Acceso en línea:https://revistas.ucr.ac.cr/index.php/matematica/article/view/33677
Access Level:acceso abierto
Palabra clave:outliers
confirmatory factor analysis
robustness
simulations study
Monte Carlo error
Valores extremos
análisis factorial confirmatorio
robustez
estudio de simulación
error Monte Carlo