Linda Collins
Professor of Social and Behavioral Sciences
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Professional overview
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Linda M. Collins is Professor of Global Public Health in the Department of Social and Behavioral Sciences, with a secondary appointment in the Department of Biostatistics. She earned her B.A. in Psychology at the University of Connecticut and her Ph.D. in Quantitative Psychology at the University of Southern California.
Collins’ research interests are focused on the development, dissemination, and application of the multiphase optimization strategy (MOST), a framework for the optimization of behavioral, biobehavioral, and social-structural interventions. The objective of MOST is to improve intervention effectiveness, efficiency, economy, and scalability. She is currently collaborating on research applying MOST in the areas of smoking cessation, the prevention of excessive drinking and risky sex in college students, and HIV services.
Collins’ research has been funded by the National Institute on Drug Abuse, the National Institute on Alcohol Abuse and Alcoholism, and the National Science Foundation, among others. She has given more than 150 presentations on MOST around the world, and her publications have appeared in journals in the fields of behavioral science, quantitative methodology, medicine, and engineering.
Collins has held tenured faculty positions at the University of Southern California and at Penn State University, where she was Distinguished Professor of Human Development and Family Studies and Director of The Methodology Center. She is a Fellow of the American Psychological Association, the Association for Psychological Science, the Society of Behavioral Medicine, and is a past president of the Society of Multivariate Experimental Psychology and the Society for Prevention Research.
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Education
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BA, Psychology, University of Connecticut, Storrs, CTPhD, Quantitative Psychology, University of Southern California, Los Angeles, CA
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Honors and awards
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Fulbright Specialist, National University of Ireland Galway (2018)Pauline Schmitt Russell Distinguished Career Award, Pennsylvania State University’s College of Health and Human Development (2017)Evan G. and Helen G. Pattishall Outstanding Research Achievement Award, Pennsylvania State University’s College of Health and Human Development (2011)President’s Award, Society for Prevention Research (2004)Faculty Scholar Medal for the Social and Behavioral Sciences, Pennsylvania State University (2000)Psychology Department Teacher of the Year, University of Southern California (1992)Psychology Department Mentorship Award, University of Southern California (1991)Society of Multivariate Experimental Psychology Award for Distinguished Early Career Contributions to Multivariate Behavioral Research (1991)
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Areas of research and study
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Behavioral ScienceCost EffectivenessCost-effective Health Programs and PoliciesDissemination and Implementation of Evidence-based Programs
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Publications
Publications
Group Comparability: A Multiattribute Utility Measurement Approach to the Use of Random Assignment with Small Numbers of Aggregated Units
AbstractGraham, J. W., Flay, B. R., Anderson Johnson, C., Hansen, W. B., & Collins, L. M. (n.d.).Publication year
1984Journal title
Evaluation ReviewVolume
8Issue
2Page(s)
247-260AbstractIt is not always possible, especially in large-scale evaluation research, to ensure that random assignment will produce groups that are comparable on any number of potentially important factors. Typically, gaining comparability has been achieved only at the expense of random assignment. A method is presented that allows multivariate comparability while making only minimal restrictions on randomization. The procedure is demonstrated in the context of assigning 63 aggregated units (schools) to 28 experimental and control conditions. Good comparability of groups for all primary main effects and interactions was venfied for 15 individual variables.Patterns of Crime in a Birth Cohort
AbstractCollins, L. M., Cliff, N., Cudeck, R. A., McCormick, D. J., & Zatkin, J. L. (n.d.).Publication year
1983Journal title
Multivariate Behavioral ResearchVolume
18Issue
3Page(s)
235-257AbstractMost attempts at developing typologies of criminal behavior have not involved empirical research. This paper describes an exploratory empirical approach to identifying patterns in criminal behavior. Two data-reduction techniques, factor analysis and cluster analysis, are applied to the official arrest records of a Danish birth cohort of 28,879 men. Four factors emerged from the factor analysis: GENERAL CRIME, TRAFFIC OFFENSES, WHITE-COLLAR CRIME, and SEX OFFENSES. The cluster analysis revealed GENERAL CRIME and TRAFFIC OFFENSES clusters. A substantial number of offenses are shown by both analyses to be independent of any pattern. The results show good split-sample cross-validation and for the most part are robust across the two analytic approaches.