Identifying subgroups: Part 1: Patterns among cross-sectional data

Eur J Cardiovasc Nurs. 2020 Apr;19(4):359-365. doi: 10.1177/1474515120911323. Epub 2020 Mar 3.

Abstract

Non-experimental designs are common in nursing and allied health research wherein study participants often represent more than a single population or interest. Hence, methods used to identify subgroups and explore heterogeneity have become popular. Latent class mixture modeling is a versatile and person-centered analytic strategy that allows us to study questions about subgroups within samples. In this article, a worked example of latent class mixture modeling is presented to help expose researchers to the nuances of this analytic strategy.

Keywords: Latent class mixture modeling; latent models; structural equation modeling; subgroup analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Cardiovascular Nursing*
  • Cross-Sectional Studies
  • Female
  • Guidelines as Topic*
  • Humans
  • Latent Class Analysis*
  • Male
  • Middle Aged
  • Models, Statistical*
  • Nursing Research / standards*
  • Research Design / standards*