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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Desimal: Jurnal Matematika Zero : Jurnal Sains, Matematika, dan Terapan AXIOM : Jurnal Pendidikan dan Matematika InPrime: Indonesian Journal Of Pure And Applied Mathematics Jurnal Eurekamatika Innovative: Journal Of Social Science Research
Nina Fitriyati
UIN Syarif Hidayatullah Jakarta
Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Education Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Physics Public Health Social Sciences Other

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Journal : CAUCHY: Jurnal Matematika Murni dan Aplikasi

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A Monte Carlo Simulation Study to Assess Estimation Methods in CFA on Ordinal Data Nina Fitriyati; Madona Yunita Wijaya
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 7, No 3 (2022): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i3.14434

Abstract

Likert-type scale data are ordinal data and are commonly used to measure latent constructs in the educational, social, and behavioral sciences. The ordinal observed variables are often treated as continuous variables in factor analysis, which may cause misleading statistical inferences. Two robust estimators, i.e., unweighted least square (ULS) and diagonally weighted least square (DWLS) have been developed to deal with ordinal data in confirmatory factor analysis (CFA). Using synthetic data generated in a Monte Carlo experiment, we study the behavior of these methods (DWLS and ULS) and compare their performance with normal theory-based ML and GLS (generalized least square) under different levels of experimental conditions. The simulation results indicate that both DWLS and ULS yield consistently accurate parameter estimates across all conditions considered in this study. The Likert data can be treated as a continuous variable under ML or GLS when using at least five Likert scale points to produce trivial bias. However, these methods generally fail to provide a satisfactory fit. Empirical studies in the field of psychological measurement data are reported to present how theoretical and statistical instances have to be taken into consideration when ordinal data are used in the CFA model.Keywords: confirmatory factor analysis, diagonally weighted least square, generalized least square, Likert data, maximum likelihood.
Co-Authors Azzahra Benita Devi Ila Octaviyani Dhea Urfani Zulkifli Dhea Urfina Zulkifli Dino Agustin Putra Irene, Yanne Irma Fauziah KHAERUDIN SALEH Mahmudi Mahmudi Maysun Maysun Nindita Nadilia Rustam Rustam Tamara Amelia Emaras Wijaya, Madona Yunita Yulinda Eliskar Zharifah Zharifah