Michael J. Rovine, Ph.D.
1982, Pennsylvania State University
Professor of Human Development
119-C
Henderson
(814) 865-7094
mr7@psu.edu
Research
My current interests are in areas related to statistical modeling. In the area of structural equations modeling, I am looking at ways to estimate a number of different multilevel models as SEM. One model of particular interest is a multilevel autoregressive model that could have important implications for those collecting relatively intensive time series data. I am also working on a general model, the nonstationary autoregressive moving average model that can be used to describe essentially any latent variable model. This general model has important implications for model comparison and testing.
Another interest of mine relates to the history of statistics, in particular the contributions of the philosopher C.S. Peirce to the development of statistical methodology. My interest in this area was sparked by my attempts to develop variations of the correlation coefficient that could be used to describe effect sizes in uncontrolled studies. Looking to see whether similar work had been done in the past, I discovered an interesting history of correlation and regression that predated the better known work of Pearson and Galton.
My main focus, however, is on a more idiographic approach to the description of developmental phenomena. Along with Erik Loken (HDFS), David Nembhard (Engineering), Cynthia Stifter (HDFS) and Peter Molenaar (HDFS), I am beginning an NSF funded study to develop and apply time series models to developmental data. We will be working with a number of different models including multilevel ARMA, state space, and control models. A brief abstract for the study follows.
Multilevel ARMA and Dynamic Models for the Longitudinal Study of Human Interactions. Michael J. Rovine (PI), Penn State University. Time series methods are used to model phenomena as varied as patterns in the weather, fluctuations in the stock market, changes in populations, quality of industrial products, patterns of sleep, physiological characteristics such as heart rate, blood pressure, and brain wave activity, and the flight of the space shuttle. The use of these methods, which are so common in the areas of engineering and econometrics and which seem so naturally suited for application in the study of human interactions have been surprisingly overlooked in the developmental sciences. In this proposal we will adapt, extend, and, where necessary, develop new methods that will be particularly well-suited to developmental research and the study of human interactions. We intend to implement these models in ways that will make them easily accessible to developmental researchers studying human interaction. We will demonstrate the utility of these methods by analyzing data from the Infant and Child Temperament Study related to infant's self regulation of emotion, and parent-infant interaction related to the parents ability to soothe a distressed child.
Education
- University of Pennsylvania, B.S., 1971, Mathematics
- The Pennsylvania State University, M.S., 1979, Ed. Psychology
- The Pennsylvania State University, Ph.D., 1982, Ed. Psychology
Research and Professional Experience
- 2004-present: Director, Health and Human Development Methodology Consulting Center
- 2004-2005: Visiting Professor, Applied Psychology and Human Development, University of Pennsylvania
- 1997-1998: Visiting Professor, Department of Developmental Psychology, University of Amsterdam
- 1991-Present: Associate Professor of Human Development, Department of Human Development and Family Studies, College of Health and Human Development, The Pennsylvania State University
- 1992-2004: Associate Director, Center for Developmental and Health Research Methodology, College of Health and Human Development, The Pennsylvania State University
- 1993-1994: Acting Director, Center for Developmental and Health Research Methodology, College of Health and Human Development, The Pennsylvania University
- 1990-1993: Research Associate, Center for Developmental and Health Research Methodology, College of Health and Human Development, The Pennsylvania State University
- 1984-1991: Assistant Professor of Human Development, Department of Human Development and Family Studies, College of Health and Human Development, The Pennsylvania State University
- 1982-1983: Post-doctoral Research Associate, Infant and Family Development Project, The Pennsylvania State University
- 1981: Instructor, Department of Educational Psychology, College of Education, The Pennsylvania State University--Altoona Campus
Selected Publications
- Rovine, M. J., & von Eye, A. (1997). a 14th way to look at a correlation coefficient: Correlation as the proportion of matches. American Statistician, 51, 42-46.
- von Eye, A., Brandstadter, J., & Rovine, M. J. (1998). Models for prediction analysis in longitudinal research. Journal of Mathematical Sociology, 22(4), 355-371.
- Rovine, M. J., & Molenaar, P. C. M. (1998). A nonstandard method for estimating a linear growth model. International Journal of Behavior and Development, 22(3), 453-473.
- Rovine, M. J., & Molenaar, P. C. M. (1998). The covariance between level and shape in the latent growth curve model with estimated basis vector coefficients. Methods of Psychological Research, 3(2), 95-107.
- Rovine, M. J., & Molenaar, P. C. M. (1998). A LISREL model for the analysis of repeated measures with a patterned covariance matrix. Structural Equation Modeling, 5(4), 318-343.
- Rovine, M. J., Molenaar, P. C. M., & Corneal, S. E. (1999). Analysis of emotional response patterns for adolescent stepsons using p-technique factor analysis. In R. Silbereisen & A. von Eye (Eds.), Growing up in times of social change (pp. 261-286). New York: De Gruyter.
- Molenaar, P. C. M., Rovine, M. J., & Corneal, S. E. (1999). Dynamic factor analysis of emotional dispositions of adolescent stepsons towards their stepfaters. In R. Silbereisen & A. von Eye (Eds.), Growing up in times of social change (pp. 287-318). New York: De Gruyter.
- Rovine, M. J., & Molenaar, P. C. M. (2000). A structural modeling approach to the random coefficients model. Multivariate Behavioral Research, 35(1), 51-58.
- Rovine, M. J., & Molenaar, P. C. M. (2001). A structural equations modeling approach to the general linear mixed model. In L. Collins & A. Sayer (Eds.), New methods for the analysis of change. (pp 65-96). Washington, DC: American Psychological Association.
- von Eye, A., Spiel, C., & Rovine, M. J. (2003). What goes together and what does not go together: Configural frequency analysis on neuropsychological research. In R. D. Franklin (Ed.), Prediction in forensic and neuropsychology (pp 149-169). Mahwah, NJ: Erlbaum.
- Rovine, M. J., & Molenaar, P. C. M. (2003). Estimating analysis of variance models as structural equation models. In B. Pugesek, A. Tomer, & A. von Eye (Eds.), Structural equation modeling: Applications in ecological and evolutionary biology research (235-280). New York: Cambridge.
- Rovine, M. J., & Anderson, D. R. (2004). Peirce and Bowditch: An American contribution to correlation and regression. American Statistician, 59(3), 232-236.
- Laurenceau, J-P., Feldman Barrett, L. A., & Rovine, M. J. (2005). Intimacy in marriage: A daily-diary approach. Journal of Family Psychology, 19(2), 1-9.
- Rovine, M. J. (2005). Number of matches and magnitude of correlation. In B.S. Everitt & D. C. Howell (Eds.), Encyclopedia of Statistics in Behavioral Science. (pp 1446-1448). New York: Wiley.
- Rovine, M. J., & Molenaar, P. C. M. (2005). Relating factor models for longitudinal data to quasi-simplex and NARMA models. Multivariate Behavioral Research, 40(1), 83-115.
- Woodhead, E.L., Zarit, S.H., Braungart, E.R., Rovine, M.J., & Femia, E.E. (2005). Behavioral and psychological symptoms of dementia: The effects of physical activity at adult day service centers. American Journal of Alzheimer's Disease and Other Dementias, 20(3), 171-180.
- Rovine, M. J., & Walls, T. A. (2006). A multilevel autoregressive model to describe interindividual differences in the stability of a process. In J. L. Schafer & T. A. Walls (Eds.), Models for intensive longitudinal data (pp. 124-147). New York: Oxford.
- Loken, E., & Rovine, M.J. (2006). Peirce's 19th century mixture model approach to rater agreement. American Statistician, 60(2), 158-161.
- Rovine, M. J., & Anderson, D. R. (2006, in press). Peirce's coefficient of the science of the method: An early form of the correlation coefficient. In D. R. Anderson (Ed.), The Pragmatic Meaning of Peirce's Realism.
- Hoffman, L., & Rovine, M.J. (2006, in press). Multilevel Models for the Experimental Psychologist: Foundations and Illustrative Examples. Behavior Research Methods.