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Health and Developmental Methods Lab (Grimm)

Keywords: Longitudinal data analysis, data mining, structural equation modeling, mixture modeling

Lab Research Area:

The Health and Developmental Methods Lab seeks to develop and evaluate methods and statistical models used to capture key characteristics of individual change processes, the determinants of longitudinal change process, and the determinants of between-person differences in the individual change process. Recently, we have focused on the development and application of data mining methods that combine machine learning algorithms with latent variable models. We have published papers on measurement invariance, latent growth models, linear and nonlinear mixed-effects models, growth mixture models, latent class models, linear dynamic models, integrative data analysis, structural equation models, data mining techniques, and exploratory approaches to studying individual change. The majority of our applications are focused on health, cognition, and achievement outcomes.

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Lab Director and Principal Investigator

Kevin J. Grimm, Ph.D., Professor of Psychology

I'm a Professor in the Department of Psychology at Arizona State University.  I received my B.A. in Mathematics and Psychology with a concentration in Education from Gettysburg College in 2000, my M.A. and Ph.D. in Psychology at the University of Virginia in Charlottesville, VA (2001-2006). At the University of Virginia I studied structural equation modeling and longitudinal data analysis with Jack McArdle and John Nesselroade. After completing my Ph.D., I worked with Bob Pianta as a research associate in the Center for the Advanced Study of Teaching and Learning at the University of Virginia. I then became an Assistant Professor in the Department of Psychology at the University of California, Davis in 2007, and was promoted to Associate Professor in 2011. In 2014, I joined the Department of Psychology at Arizona State University and in 2016 was promoted to Full Professor.

 

Graduate Students

Kimberly Fine

Kim is a fourth-year graduate student in the Quantitative Research Methods Ph.D. program at Arizona State University. She earned my Masters in Psychology and B.S. in Psychological Sciences with a minor in Statistics at Arizona State University. Kim’s research interests revolve around the analysis of longitudinal data, focusing in the areas of functional data analysis and mixed-effects models.

 

Heather Gunn

Heather is a sixth-year graduate student in the Quantitative Research Methods program at Arizona State University. She earned her B.A. in Psychology with a minor in Mathematics at Texas Tech University. Heather’s quantitative research interests include measurement invariance, multilevel modeling, and item response theory. Her substantive interests are in the education and health fields.

 

Gina Mazza

Gina is currently pursuing her Ph.D. in Psychology, Quantitative Research Methods at Arizona State University. While at Arizona State University, she received her M.A. in Psychology, Quantitative Research Methods, and her B.S. in Psychology with a minor in Mathematics. Gina’s research focuses on the development and advancement of methods for addressing two pervasive issues in medical and psychological research—missing data and treatment nonadherence. She is also interested in the application of these methods to improve public health and patient care.

 

Gabi Stegmann

Gabi is a second-year graduate student in the Quantitative Research Methods program at Arizona State University. She received my B.A. in Psychology with a minor in Mathematics at the University of North Florida, where she also received her M.A. in Counseling Psychology and her M.S. in Mathematics with concentration in Statistics. Gabi’s research interests include longitudinal analysis, missing data, and data mining methods.

 

Alumni

Joel Steele, Ph.D. (University of California, Davis, 2011),

Assistant Professor, Department of Psychology, Portland State University

Associate Professor, Department of Psychology, Portland State University

 

Laura Castro-Schilo, Ph.D. (University of California, Davis, 2013)

Assistant Professor, Department of Psychology, University of North Carolina-Chapel Hill

Research Statistician, SAS

 

Jonathan Helm, Ph.D. (University of California, Davis, 2014)

Post-doctoral Researcher, University of California, Davis

Post-doctoral Researcher, The Pennsylvania State University

Assistant Professor, Department of Psychology, San Diego State University

 

Pega Davoudzadeh, Ph.D. (University of California, Davis, 2016)

Post-doctoral Researcher, University of California, Davis

People Data Researcher, Yahoo!

 

Katerina Marcoulides, Ph.D. (Arizona State University, 2017)

Assistant Professor, Research and Evaluation Program, College of Education, University of Florida

 

Collaborators

Steven Boker, Ph.D., Professor of Psychology, University of Virginia

Ian Campbell, Ph.D., Project Scientist, University of California, Davis

Carol Connor, Ph.D., Chancellor’s Professor, School of Education, University of California, Irvine

Mary Davis, Ph.D., Professor of Psychology, Arizona State University

Leah Doane, Ph.D., Associate Professor of Psychology, Arizona State University

Jason Downer, Ph.D., Research Associate Professor, Curry School of Education, University of Virginia

Ryne Estabrook, Ph.D., Assistant Professor of Medical Social Sciences, Northwestern University

Emilio Ferrer, Ph.D., Professor of Psychology, University of California, Davis

Simona Ghetti, Ph.D., Professor of Psychology, University of California, Davis

David Grissmer, Ph.D., Principal Scientist, Curry School of Education, University of Virginia

Frank Infurna, Ph.D., Assistant Professor of Psychology, Arizona State University

Ross Jacobucci, Ph.D., Assistant Professor of Psychology, University of Notre Dame

Jungmeen Kim-Spoon, Ph.D., Professor of Psychology, Virginia Tech

Kathy Lemery-Chalfant, Ph.D., Professor of Psychology, Arizona State University

Michèle Mazzocco, Ph.D., Professor of Child Development, University of Minnesota

John J. McArdle, Ph.D., Professor of Psychology and Gerontology, University of Southern California

Marisol Perez, Ph.D., Associate Professor of Psychology, Arizona State University

Robert Pianta, Ph.D., Dean of the Curry School of Education, University of Virginia

Nilam Ram, Ph.D., Professor of Human Development and Family Studies, Pennsylvania State University

Richard Van Dorn, Ph.D., Senior Mental Health Services Researcher, Research Triangle Institute

Lijuan Wang, Ph.D., Associate Professor of Psychology, University of Notre Dame

Keith Widaman, Ph.D., Associate Dean & Professor, Graduate School of Education, University of California, Riverside

Zhiyong Johnny Zhang, Ph.D., Associate Professor of Psychology, University of Notre Dame

Select Publications

Books

  1. Grimm, K. J., Ram, N., & Estabrook, R. (2017). Growth modeling: Structural equation and multilevel modeling approaches. New York, NY: Guilford.
  2. Jacobucci, R., & Grimm, K. J. (under contract). Exploratory data mining for social and behavioral scientists. New York, NY: Guilford.

 

Articles

  1. Grimm, K. J. (2007). Multivariate longitudinal methods for studying developmental relationships between depression and academic achievement. International Journal of Behavioral Development, 31, 328-339.
  2. Grimm, K. J., Pianta, R. C., & Konold, T. R. (2009). Longitudinal multitrait-multimethod models for developmental research. Multivariate Behavioral Research, 44, 233-258.
  3. Grimm, K. J., & Ram, N. (2009). Nonlinear growth models in Mplus and SAS. Structural Equation Modeling: A Multidisciplinary Journal, 16, 676-701.
  4. Grimm, K. J., & Ram, N. (2009). A second-order growth mixture model for developmental research. Research in Human Development, 2-3, 121-143.
  5. Grimm, K. J., & Widaman, K. F. (2010). Residual structures in latent growth curve analysis. Structural Equation Modeling: A Multidisciplinary Journal, 17, 424-442.
  6. Grimm, K. J., Ram, N., & Estabrook, R. (2010). Nonlinear structured growth mixture models in Mplus and OpenMx. Multivariate Behavioral Research, 45, 887-909.
  7. Grimm, K. J., Ram, N., & Hamagami, F. (2011). Nonlinear growth curves in developmental research. Child Development, 82, 1357-1371.
  8. Grimm, K. J., An, Y., McArdle, J. J., Zonderman, A. B., & Resnick, S. M. (2012). Recent changes leading to subsequent changes: Extensions of multivariate latent difference score models. Structural Equation Modeling: A Multidisciplinary Journal, 19, 268-292.
  9. Grimm, K. J., *Steele, J. S., Ram, N., & Nesselroade, J. R. (2013). Exploratory latent growth models in the structural equation modeling framework. Structural Equation Modeling: A Multidisciplinary Journal, 20, 568-591.
  10. Grimm, K. J., Zhang, Z., Hamagami, F., & Mazzocco, M. M. (2013). Modeling nonlinear change via latent change and latent acceleration frameworks: Examining velocity and acceleration of growth trajectories. Multivariate Behavioral Research, 48, 117-143.
  11. Grimm, K. J., *Casto-Schilo, L., & *Davoudzadeh, P. (2013). Modeling intraindividual change in nonlinear growth models with latent change scores. GeroPsych, 26, 153-162.
  12. *Serang, S., Zhang, Z., *Helm, J., *Steele, J. S., & Grimm, K. J. (2015). Evaluation of a Bayesian approach to estimating nonlinear mixed-effects mixture models. Structural Equation Modeling: A Multidisciplinary Journal, 22, 202-215.
  13. *Davoudzadeh, P., *McTernan, M. L., & Grimm, K. J. (2015). Early school readiness predictors of grade retention from kindergarten through eighth grade: A multilevel discrete-time survival analysis approach. Early Childhood Research Quarterly, 32, 183-192.
  14. Grimm, K. J., & *Marcoulides, K. M. (2016). Individual change and the timing and onset of important life events: Methods, models, and assumptions. International Journal of Behavioral Development, 40, 87-96.
  15. Grimm, K. J., & *Liu, Y. (2016). Residual structures in growth models with ordinal outcomes. Structural Equation Modeling: A Multidisciplinary Journal, 23, 466-475.
  16. *Jacobucci, R., Grimm, K. J., & McArdle, J. J. (2016). Regularized structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 23, 555-566.
  17. Grimm, K. J., *Mazza, G. L., & Mazzocco, M. M. M. (2016). Advances in methods for assessing longitudinal change. Educational Psychologist, 51, 342-353.
  18. *Serang, S., Grimm, K. J., & McArdle, J. J. (2016). Estimation of time-unstructured nonlinear mixed-effects mixture models. Structural Equation Modeling: A Multidisciplinary Journal, 23, 856-869.
  19. Grimm, K. J., *Mazza, G., & *Davoudzadeh, P. (2017). Model selection in finite mixture models: A k-fold cross-validation approach. Structural Equation Modeling: A Multidisciplinary Journal, 24, 246-256.
  20. *Jacobucci, R., Grimm, K. J., & McArdle, J. J. (2017). A comparison of methods for uncovering sample heterogeneity: Structural equation model trees and finite mixture models. Structural Equation Modeling: A Multidisciplinary Journal, 24, 270-282.
  21. *Serang, S., *Jacobucci, R., *Brimhall, K. C., & Grimm, K. J. (in press). Exploratory mediation analysis via regularization. Structural Equation Modeling: A Multidisciplinary Journal.
  22. *Marcoulides, K. M., & Grimm, K. J. (in press). Data integration approaches to longitudinal growth modeling. Educational & Psychological Measurement.
  23. *Gonzalez, O., *Wurpts, I. C., *O’Rourke, H., & Grimm, K. J. (in press). Evaluating Monte Carlo simulations through data mining methods. Structural Equation Modeling: A Multidisciplinary Journal.
  24. *Stegmann, G., & Grimm, K. J. (in press). A new perspective on the effects of covariates in mixture models. Structural Equation Modeling: A Multidisciplinary Journal.
  25. Castro-Schilo, L., & Grimm, K. J. (in press). Using residualized change versus difference score for longitudinal research. Journal of Social and Personal Relationships.

News & more

Katerina Marcoulides, Ph.D., has accepted a position as an Assistant Professor of Informatics and Statistics in the College of Education at the University of Florida.

 

Special Issue of the Structural Equation Modeling: A Multidisciplinary Journal on Novel Approaches in Mixture Modeling, edited by Gitta Lubke and Kevin Grimm, was published in 2017

Please visit our Google website for more info!