Applied Research Topics

LCA and LTA in Alcohol, Tobacco, Other Drug, and Gambling Research

LCA and LTA in Drug Abuse Use Research

The Methodology Center has contributed to important theoretical frameworks for the etiology of drug abuse. For example, we have proposed and applied a methodological framework based on latent class analysis (LCA) and its longitudinal extension, latent transition analysis (LTA), for testing the gateway hypothesis of drug use onset (Maldonado & Lanza, 2010). A major contribution to applied work on drug abuse is the identification of latent classes characterized by particular patterns of drug use; in other words, we use LCA as a measurement model for drug abuse behavior.

References & recommended reading

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 Health55(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 Research, 18(12), 2243-2251. http://doi.org/10.1093/ntr/ntw173

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

Maldonado, M. M., & Lanza, S. T. (2010). A framework to examine gateway relations in drug use: An application of latent transition analysis. Journal of Drug Issues, 40, 901-924. PMCID: PMC3400537 

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 Drugs, 77(6), 881-888.

LCA in Risk Factor Research

LCA in Risk Factors Research

The Methodology Center has applied LCA to model multiple risk factors to demonstrate the importance of taking a more holistic approach in order to draw prevention implications.

References & recommended reading

Cleland, C., Lanza, S. T., Vasilenko, S. A., & Gwadz, M. (2017). Syndemic risk classes and substance use problems among adults in high-risk urban areas: A latent class analysis. Frontiers In Public Health.

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, 213-228. PMCID: PMC2898733

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. PMCID: PMC3943167

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

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 

Lanza, S. T., Rhoades, B. L., Nix, R. L., Greenberg, M. T., & the Conduct Problems Prevention Research Group (2010). Modeling the interplay of multilevel risk factors for future academic and behavior problems: A person-centered approach. Development and Psychopathology, 22, 313-335. PMCID: PMC3005302

LCA and LTA in Intervention Research

The Methodology Center has applied LCA and LTA to evaluate the way interventions work differently for different subgroups of people.

References & recommended reading

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

Cooper, B. R., & Lanza, S. T. (2014). Who benefits most from Head Start? Using latent class moderation to exaimne differential treatment effects. Child Development, 85, 2317-2338.

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

LCA and LTA in HIV Research

LCA and LTA in HIV Research

The Methodology Center has applied LCA and LTA to understand subgroups of people who are at risk for HIV infection. For example, we have examined sexual risk behavior among adolescents and adults (Lanza, Kugler, & Mathur, 2011). We have also tested the role played by social networks in HIV risk among a high-risk population in Namibia (Smith & Lanza, 2011).

References & recommended reading

Lanza, S. T, Kugler, K. C., & Mathur, C. (2011). Differential effects for sexual risk behavior: An application of finite mixture regression. The Open Family Studies Journal, 4, (Suppl. 1-M9), 81-88. PMCID: PMC3487167

Rice, C. E., Turner, A. N., & Lanza, S. T. (2017). Sexual behavior latent classes among men who have sex with men: Associations with sexually transmitted infections. The Journal Of Sex Research, 54, 776-783. http://doi.org/10.1080/00224499.2016.1211599

Smith, R. A., & Lanza, S. T. (2011). Testing theoretical network classes and HIV-related correlates with latent class analysis. AIDS Care, 23, 1274-1281. PMCID: PMC3181093

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 PMICD: PMC4107199