Recommended Reading for Latent Class Models

Introduction to LCA and LTA

Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. New York: Wiley.

Lanza, S. T., Bray, B. C., & Collins, L. M. (2013). An introduction to latent class and latent transition analysis. In J. A. Schinka, W. F. Velicer, & I. B. Weiner (Eds.),Handbook of psychology (2nd ed.,Vol. 2, pp. 691-716). Hoboken, NJ: Wiley.

Lanza, S. T., & Collins, L. M. (2008). A new SAS procedure for latent transition analysis: Transitions in dating and sexual risk behavior. Developmental Psychology, 44(2), 446-456. PMCID: PMC2846549

Lanza, S. T., Collins, L. M., Lemmon, D. R., & Schafer, J. L. (2007). PROC LCA: A SAS procedure for latent class analysis. Structural Equation Modeling, 14(4), 671-694. PMCID: PMC2785099 View article

Lanza, S. T., Rhoades, B. L., Greenberg, M. T., Cox, M. J., & The Family Life Project Key Investigators (2011). Modeling multiple risks during infancy: Contributions of a person-centered approach. Infant Behavior and Development, 34(3), 390-406. PMCID: PMC3134117  View abstract

Applications of LCA

Cleveland, M. J., Collins, L. M., Lanza, S. T., Greenberg, M. T., & Feinberg, M. E. (2010). Does individual risk moderate the effect of contextual-level protective factors? A latent class analysis of substance use. Journal of Prevention and Intervention in the Community, 38(3), 213-228. PMCID: PMC2898733  View article

Cooper, B. R., & Lanza, S. T. (2014). Who benefits most from Head Start? Using latent class moderation to exaimne differential treatment effects. Child Development. Advance online publication. doi: 10.1111/cdev.12278

Evans-Polce, R. E., Lanza, S. T., & Maggs, J. L. (2016). Heterogeneity of alcohol, tobacco, and other substance use behaviors in US college students: A latent class analysis. Addictive Behaviors, 53, 80-85.

Lanza, S. T., Cooper, B. R., & Bray, B. C. (2014). Population heterogeneity in the salience of multiple risk factors for adolescent delinquency. Journal of Adolescent Health, 54, 319-325. doi: 10.1016/j.jadohealth.2013.09.007 PMCID: PMC3943167 (abstract)

Linden-Carmichael, A. N., Lanza, S. T., Dziak, J. J., & Bray, B. C. (2017). Contemporary Alcohol Use Patterns among a National Sample of U.S. Adult Drinkers. Journal Of Addictive Diseases

Patrick, M. E., Bray, B. C., & Berglund, P. A. (2016). Reasons for marijuana use among young adults and long-term associations with marijuana use and problems. Journal Of Studies On Alcohol And Drugs77(6), 881-888.

Vasilenko, S. A., Kugler, K. C., Butera, N. M. & Lanza, S. T. (2014). Patterns of adolescent sexual behavior predicting young adult sexually transmitted infections: A latent class analysis approach. Archives of Sexual Behavior. doi: 10.1007/s10508-014-0258-6 PMCID: PMC4107199​

Applications of LTA

Bray, B. C., Lee, G. P., Liu, W., Storr, C. L., Ialongo, N. S., & Martins, S. S. (2014). Transitions in gambling participation during late adolescence and young adulthood. Journal of Adolescent Health, 55(2), 188-194. doi: 10.1016/j.jadohealth.2014.02.001 PMCID: PMC4108554

Bray, B. C., Smith, R. A., Piper, M. E., Roberts, L. J., & Baker, T. B. (2016). Transitions in Smokers’ Social Networks After Quit Attempts: A Latent Transition Analysis. Nicotine & Tobacco Research18(12), 2243-2251.

Cleveland, M. J., Lanza, S. T., Ray, A. E., Turrisi, R., & Mallett, K. M. (2012). Transitions in first-year college student drinking behaviors: Does drinking latent class membership moderate the effects of parent- and peer-based intervention components? Psychology of Addictive Behaviors, 26, 440-450. PMCID: PMC3413757

Lanza, S. T., Patrick, M. E., & Maggs, J. L. (2010). Latent transition analysis: Benefits of a latent variable approach to modeling transitions in substance use.Journal of Drug Issues, 40(1), 93-120. PMCID: PMC2909684

Patrick, M. E., Collins, L. M., Smith, E., Caldwell, L., Flisher, A., & Wegner, L. (2009). A prospective longitudinal model of substance use onset among South African adolescents. Substance Use & Misuse, 44(5), 647-662. PMCID: PMC2796627

LCA with a distal outcome

Bakk, Z., & Vermunt, J. K. (2016). Robustness of stepwise latent class modeling with continuous distal outcomes. Structural Equation Modeling, 23, 20-31. doi: 10.1080/10705511.2014.955104t

Bray, B. C., Lanza. S. T., & Tan, X. (2015). Eliminating bias in classify-analyze approaches for latent class analysis.Structural Equation Modeling: A Multidisciplinary Journal22(1), 1-11. doi: 10.1080/10705511.2014.935265 PMCID: PMC4299667

Dziak, J. J., Bray, B. C., Zhang, J. – T., Zhang, M., & Lanza, S. T. (2016). Comparing the performance of improved classify-analyze approaches in latent profile analysis. Methodology: European Journal Of Research Methods For The Behavioral And Social Sciences, 12, 107-116.

Lanza, S. T., Tan, X., & Bray, B. C. (2013). Latent class analysis with distal outcomes: A flexible model-based approach. Structural Equation Modeling: A Multidisciplinary Journal, 20, 1-26.

Lanza, S. T. & Rhoades, B. L. (2013). Latent class analysis: An alternative perspective on subgroup analysis in prevention and treatment. Prevention Science, 14, 157-168. PMCID: PMC3173585

Causal inference with LCA

Butera, N. M., Lanza, S. T., & Coffman, D. L. (2013). A framework for estimating causal effects in latent class analysis: Is there a causal link between early sex and subsequent profiles of delinquency? Prevention Science. doi: 10.1007/s11121-013-0417-3 PMCID: PMC3888479

Lanza, S. T., Coffman, D. L., & Xu, S. (2013). Causal inference in latent class analysis. Structural Equation Modeling, 20(3), 361-383.

Lanza, S. T., Schuler, M. S., & Bray, B. C. (2016). Latent class analysis with causal inference: The effect of adolescent depression on young adult substance abuse profiles. In Causality and Statistics (pp. 385-404). Hoboken, NJ: Wiley.

Schuler, M. S., Leoutsakos, J. S., & Stuart, E. A. (2014). Addressing confounding when estimating the effects of latent classes on a distal outcome. Health Services Outcomes and Research Methodology14(4), 232-254.

Statistical power in LCA

Dziak, J. J., Lanza, S. T., & Tan, X. (2014). Effect size, statistical power and sample size requirements for the bootstrap likelihood ratio test in latent class analysis. Structural Equation Modeling, 21, 534-552.

Associative latent transition analysis

Bray, B. C., Foti, R. J., Thompson, N. J., & Wills, S. F. (2014). Disentangling the effects of self leader perceptions and ideal leader prototypes on leader judgments using loglinear modeling with latent variables. Human Performance, 27, 393-415. PMC Exempt – Not NIH Funded

Bray, B. C., Lanza, S. T., & Collins, L. M. (2010). Modeling relations among discrete developmental processes: A general approach to associative latent transition analysis. Structural Equation Modeling: A Multidisciplinary Journal, 17(4), 541-569. doi: 10.1080/10705511.2010.510043 PMCID: PMC3094019 (abstract)