Revista de Matemática: Teoría y Aplicaciones ISSN Impreso: 1409-2433 ISSN electrónico: 2215-3373

OAI: https://revistas.ucr.ac.cr/index.php/matematica/oai
Robustness of confirmatory factor analysis fit indices to outliers
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Keywords

outliers
confirmatory factor analysis
robustness
simulations study
Monte Carlo error
Valores extremos
análisis factorial confirmatorio
robustez
estudio de simulación
error Monte Carlo

How to Cite

Rojas-Torres, L. (2020). Robustness of confirmatory factor analysis fit indices to outliers. Revista De Matemática: Teoría Y Aplicaciones, 27(2), 383–404. https://doi.org/10.15517/rmta.v27i2.33677

Abstract

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, but
considering cutoffs adjusted by the factorial structure and the sample size.

https://doi.org/10.15517/rmta.v27i2.33677
PDF (Español (España))
PS (Español (España))
DVI (Español (España))

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