Cited by 1,204Psychometric Methodologies and TestingBayesian Methods and Mixture ModelsStatistical Methods and Applications

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Practitioner’s Guide to Latent Class Analysis: Methodological Considerations and Common Pitfalls

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Sinha, Pratik, Calfee, Carolyn S., Delucchi, Kevin L.·2021·Critical Care Medicine

DOI 10.1097/ccm.0000000000004710PMC PMC7746621

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Abstract

Latent class analysis is a probabilistic modeling algorithm that allows clustering of data and statistical inference. There has been a recent upsurge in the application of latent class analysis in the fields of critical care, respiratory medicine, and beyond. In this review, we present a brief overview of the principles behind latent class analysis. Furthermore, in a stepwise manner, we outline the key processes necessary to perform latent class analysis including some of the challenges and pitfalls faced at each of these steps. The review provides a one-stop shop for investigators seeking to apply latent class analysis to their data.

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Authors: Sinha, P., Calfee, C. S., & Delucchi, K. L.
Affiliations: University of California, San Francisco (US)
ORCID: Sinha, Pratik
Calfee, Carolyn S.
Delucchi, Kevin L.
Venue: Critical Care Medicine
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2020-11-09
Volume: 49
Issue: 1
Pages: e63-e79
ISSN: 0090-3493 (ISSN-L)
DOI: 10.1097/ccm.0000000000004710
PMC: PMC7746621
OpenAlex: W3102547229
Cited by: 1,204
References: 56
Citations by year: 2026: 386 · 2025: 382 · 2024: 290 · 2023: 98 · 2022: 35 · 2021: 13
FWCI: 7.14
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Critical Care Medicine (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
eScholarship (California Digital Library) (submittedVersion)
Funders: National Heart, Lung, and Blood Institute (R35HL140026)
National Institute of General Medical Sciences (T32GM008440)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords: latent class analysis, clustering, stochastic modeling, statistical inference, intensive care, respiratory medicine, methodological pitfalls, data analysis pipeline
MeSH terms: Latent Class Analysis, Data Interpretation, Statistical, Humans, Statistics as Topic

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Practitioner’s Guide to Latent Class Analysis: Methodological Considerations and Common Pitfalls

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