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Summer Institute on Longitudinal Research &
National Drug Abuse Treatment Clinical Trials
Network (CTN) Dissemination Conference
August 9-11, 2010
Clinical Trials Network
John (Jack) McArdle, Ph.D., University of Southern California
DAY TWO – Tuesday, August 10, 2010
Statistical Workshop
Track 2: Advanced Topics in Longitudinal Data Analysis for Investigators, Session I
PRESENTATION/HANDOUTS:
A Two-Day Workshop in Longitudinal Structural Equation Modeling
Introduction to Dealing with Incomplete Longitudinal Data
Likelihood Based Modeling with Incomplete Data
Expanding the Features of Incomplete Longitudinal Data
SELECTED REFERENCES:
McArdle, J.J. & Prindle, J.J. (2008). A latent change score analysis of a randomized clinical trial in reasoning training. Psychology and Aging, 23(4), 702-719.
Ferrer, E., McArdle, J.J., Shaywitz, B.A., Holahan, J.M., Marchione, K., & Shaywitz, S.E. (2007). Longitudinal models of developmental dynamics between reading and cognition from childhood to adolescence. Developmental Psychology, 43, 1460-1473.
McArdle, J.J. (1994). Structural factor analysis experiments with incomplete data. Multivariate Behav. Research, 29(4), 409 454.
McArdle, J.J., Fisher, G.G. & Kadlec, K.M. (2007). Latent Variable Analysis of Age Trends in Tests of Cognitive Ability in the Health and Retirement Survey, 1992-2004. Psychology and Aging, 22(3), 525-545.
McArdle, J.J. (2008). Latent variable modeling of longitudinal data. Annual Review of Psychology, 60, 577–605.
McArdle, J.J. (2010). How Much Life-Span Data Do We Really Need? In W.F. Overton (Ed.), Biology, cognition and methods across the life-span. Volume 1 of the Handbook of Life-Span Development (pp. 36-55), with Editor-In-Chief, R. M. Lerner. Hoboken, NJ: Wiley.
DAY THREE – Wednesday, August 11, 2010
Statistical Workshop
Track 1: Advanced Topics in Longitudinal Data Analysis for Investigators, Session II
PRESENTATION/HANDOUTS:
Lecture 1: Causal Inference from Cross-Lagged Data
Lecture 2: Modeling Changes in Common Factors
Lecture 3: Multivariate Dynamic Modeling Using Latent Change Scores
SELECTED REFERENCES:
McArdle, J.J. & Prindle, J.J. (2008). A latent change score analysis of a randomized clinical trial in reasoning training. Psychology and Aging, 23(4), 702-719.
Ferrer, E., McArdle, J.J., Shaywitz, B.A., Holahan, J.M., Marchione, K., & Shaywitz, S.E. (2007). Longitudinal models of developmental dynamics between reading and cognition from childhood to adolescence. Developmental Psychology, 43, 1460-1473.
McArdle, J.J. (1994). Structural factor analysis experiments with incomplete data. Multivariate Behavioral Research, 29 (4), 409 454.
McArdle, J.J., Fisher, G.G. & Kadlec, K.M. (2007). Latent Variable Analysis of Age Trends in Tests of Cognitive Ability in the Health and Retirement Survey, 1992-2004. Psychology and Aging, 22 (3), 525-545.
McArdle, J.J. (2008). Latent variable modeling of longitudinal data. Annual Review of Psychology, 60, 577–605.
McArdle, J.J. (2010). How Much Life-Span Data Do We Really Need? In W.F. Overton (Ed.), Biology, cognition and methods across the life-span. Volume 1 of the Handbook of life-span development (pp. 36-55), with Editor-In-Chief, R. M. Lerner. Hoboken, NJ: Wiley.
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