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This is a Quantitative Study study.

October 9, 2025Chinese/English Journal of Educational Measurement and EvaluationOpen Access

Treatments of Ordinal Scales in Latent Profile Analyses: A Comparison with Monte Carlo Simulations

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Authors

CYChongming YangBrigham Young University JOJoseph A. OlsenBrigham Young University CCCaleb CarlyleDuke University

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Implication

This analysis compares different ordinal scale treatments in latent profile analysis, suggesting factor scores yield better class proportions. Results indicate Bayesian estimation enhances accuracy.

Key Points

LPA of factor scores shows slight advantages in capturing class proportions and univariate differences.
Monte Carlo simulations were used to analyze treatments of ordinal scales across varying sample sizes.
Weighted and unweighted means, as well as sums of ordinal scales, may not perform as well as factor scoring.
Efficient LPA approaches should adapt based on sample size and response options for better accuracy.

Cite This Study

Yang et al. (2025) studied this question.

synapsesocial.com/papers/68e70db790569dd607ee67b6 https://doi.org/10.59863/civh2487

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Implication

This analysis compares different ordinal scale treatments in latent profile analysis, suggesting factor scores yield better class proportions. Results indicate Bayesian estimation enhances accuracy.

Treatments of Ordinal Scales in Latent Profile Analyses: A Comparison with Monte Carlo Simulations

Discussion

Member takes

Implication

Key Points

Cite This Study

Treatments of Ordinal Scales in Latent Profile Analyses: A Comparison with Monte Carlo Simulations

Discussion

Member takes

Implication

Key Points

Cite This Study

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