A Systematic Review of Latent Variable Mixture Modeling Research in Social Work Journals

ABSTRACT

Purpose: Latent variable mixture modeling (LVMM) estimates possible classes, profiles, or trajectories within a sample and then identifies individuals with similar patterns. This systematic review examines the use of person-centered LVMM analyses published in social work journals.

Methods: We screened 478 articles and obtained a final sample of 32 studies meeting inclusion criteria.

Results: Studies using LVMM were published between 2004 and 2017 with a majority appearing after 2012. Latent class analysis was used in most studies followed by latent profile analysis and longitudinal variants of LVMM. Samples sizes ranged from 199 to 1,002,122 (median = 533). Less than half of the identified studies met model fit reporting standards.

Discussion: This systematic review demonstrates the usefulness and growing popularity of LVMM studies within social work journals. Social Work researchers are encouraged to employ person-centered methods to explore unobserved groups or trajectories within cross-sectional and longitudinal data.

KEYWORDS:

• Latent class analysis
• latent variable mixture modeling
• systematic review