Developing Multidimensional Likert Scales Using Item Factor Analysis: The Case of Four-point Items  

Oleh:

Asun, Rodrigo ; Rdz-Navarro, Karina ; Alvarado, Jesus M

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Sociological Methods & Research (SMR) vol. 45 no. 01 (Feb. 2016), page 109-133.
Topik: Likeert scales; item factor; analysis polychoric correlation; four-point items; classical factor analysis

Ketersediaan

Perpustakaan PKPM Nomor Panggil: S28 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This study compares the performance of two approaches in analysing four-point Likert rating scales with a factorial model: the classical factor analysis (FA) and the item factor analysis (IFA). For FA, maximum likelihood and weighted least squares estimations using Pearson correlation matrices among items are comapred. For IFA, diagonally weighted least squares and unweighted least squares estimations using items polychoric correlation matrices are compared. Two hundred and ten conditions were stimulated in a Monte Carlo study considering: one to three factor structures (either, independent and correlated in two levels), medium or low quality of items,three differnt levels of item asymmetry and five sample size. Results showed that IFA procedures achieve equivalent and accurate parameter estimates; in contras, FA procedures yielded biased parameter estimates. Therefore, we do not recommend classical FA under the conditions considered. Minimum requirements for achieving accurate results using IFA procedures are discussed.

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