Linda M. Collins

 Linda Collins

Distinguished Professor, Human Development and Family Studies and Statistics; Director, Methodology Center

Contact Information

435 Health & Human Development Building
State College PA 16801


(fax) 814-863-0000


B.A., 1977, Psychology, University of Connecticut
Ph.D., 1983, Quantitative Psychology, University of Southern California

Research Interests

I am interested in most aspects of research methods. Lately I have been most interested in experimental and non-experimental design, particularly for building, optimizing and evaluating behavioral interventions. I also have a long-standing interest in models for longitudinal data, particularly latent transition analysis, and other latent class models.

Current Projects and Collaborators

I am working on two related projects to bring ideas from engineering to bear on optimization of behavioral interventions. My collaborators on these projects are Daniel E. Rivera (Arizona State University), Runze Li, Inbal Nahum-Shani (University of Michigan), John Dziak, and Susan Murphy. I also collaborate frequently with Stephanie Lanza on research related to latent class and latent transition analysis.


Research methods; experimental and non-experimental design, particularly for building and evaluating behavioral interventions; models for longitudinal data; latent class analysis.

Selected Publications

Collins, L. M., Dziak, J. D., Kugler, K. C., & Trail, J. B. (in press). Factorial experiments: Efficient tools for evaluation of intervention components. American Journal of Preventive Medicine.

Pellegrini, C. A., Hoffman, S. A., Collins, L. M., & Spring, B. (2014). Optimization of remotely delivered intensive lifestyle treatment for obesity using the Multiphase Optimization Strategy: Opt-IN study protocol. Contemporary clinical trials.

Wyrick, D. L., Rulison, K. L., Fearnow -Kenney, M., Milroy, J. J., & Collins, L. M. (2014). Moving beyond the treatment package approach to developing behavioral interventions: Addressing questions that arose during an application of the multiphase optimization strategy (MOST). Translational Behavioral Medicine. Advance online publication. doi: 10.1007/s13142-013-0247-7

Collins, L. M., Nahum-Shani, I., & Almirall, D. (2014). Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART). Clinical Trials. doi: 10.1177/1740774514536795

Timms, K. P., Rivera, D. E., Collins, L. M., & Piper, M. E. (2014). Continuous-time system identification of a smoking cessation intervention. International Journal of Control. Advance online publication. doi:10.1080/00207179.2013.874080

Timms, K. P., Rivera, D. E., Collins, L. M., & Piper, M. E. (2014). A dynamical systems approach to understand self-regulation in smoking cessation behavior change. Nicotine and Tobacco Research, 16, S159-S168. doi: 10.1093/ntr/ntt149 PMCID: PMC3977628

ollins, L. M. (2013). Optimizing family interventions: The Multiphase Optimization Strategy (MOST). In McHale, S. McHale, P. Amato, P., & A. Booth, A. (Eds.). Emerging methods in family research. New York: Springer.

Lippold, M. A., Greenberg, M. T., & Collins, L. M. (2013). Youths’ substance use and changes in parental knowledge-related behaviors during middle school: A person-oriented approach. Journal of Youth and Adolescence. Advance online publication. doi: 10.1007/s10964-013-0010-x PMCID: PMC3938985

Collins, L., Trail, J., Kugler, K., Baker, T., Piper, M., & Mermelstein, R. (2013). Evaluating individual intervention components: making decisions based on the results of a factorial screening experiment. Translational Behavioral Medicine. Advance online publication. doi: 10.1007/s13142-013-0239-7 NIHMSID: NIHMS544386

Collins, L. M., MacKinnon, D. P., & Reeve, B. (2013). Commentary: Some methodological considerations in theory-based health behavior research. Health Psychology, 32, 586-591. PMCID: PMC3832141

Curriculum Vitae

Linda Collins vitae

Center Affiliations

  • Methodology Center

Strategic Themes

  • Domains of Health and Behavior
  • Methodology