Analytical, Diagnostic and Therapeutic Techniques, and Equipment

Latent Class Analysis

A statistical algorithm used to analyze clusters of observed variables by constructing categorical unobserved or latent segment based on weighted analysis and the average probabilities. Such latent classes are used to infer variables whose relationships are not directly observed. In biomedical research, it is often used to categorize data that allows the determination of symptom clusters.

National Library of MedicineMedical Subject Headings2026

Structured Summary

Abstract

A statistical algorithm used to analyze clusters of observed variables by constructing categorical unobserved or latent segment based on weighted analysis and the average probabilities. Such latent classes are used to infer variables whose relationships are not directly observed. In biomedical research, it is often used to categorize data that allows the determination of symptom clusters.

MeSH Record

Classification

Broader headings

Related Concepts

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MeSH Record

Synonyms

12 entry terms
  • Latent Variable Modeling
  • Latent Class Analyses
  • Latent Variable Modelings
  • Modeling, Latent Variable
  • Variable Modeling, Latent
  • Latent Class Model
  • Probabilistic Latent Semantic Analysis
  • Structural Equation Modeling
  • Latent Class Models
  • Model, Latent Class
  • Modeling, Structural Equation
  • Structural Equation Modelings

MeSH Record

History Note

2019

MeSH Record

Previous Indexing

  • Statistics as Topic (2017-2018)

MeSH Hierarchy

Tree Numbers

  1. E05.318w.740w.250w.338w
  2. G17w.035w.625w
  3. L01w.224w.050w.687w
  4. N05.715w.360.750w.200w.375w
  5. N06.850w.520w.830w.250w.338w

AMA Style

References

  1. National Library of Medicine. Latent Class Analysis. Medical Subject Headings (MeSH). 2026. Unique ID D000077272. http://id.nlm.nih.gov/mesh/2026/D000077272
  2. Latent Class Analysis. In: Wikipedia. https://en.wikipedia.org/wiki/Latent_class_model
  3. Latent Class Analysis. In: Wikidata. https://www.wikidata.org/wiki/Q1806878