The Center for Integrated Latent Variable Research (CILVR)
MODERN LONGITUDINAL DATA ANALYSIS:
MIXED EFFECTS MODELS USING R
MARCH 3-5, 2021
Jeffrey R. Harring, University of Maryland
This three-day short course is intended as both a theoretical and practical introduction to modern statistical techniques for longitudinal data analysis as it pertains to methods regularly used in educational, behavioral, and social science research. An understanding of modern longitudinal data analytic methods will be developed by relating it to participants’ existing knowledge of traditional statistical methods, particularly multiple linear regression. A participant’s experience in this workshop will be enhanced by additional prior coursework or knowledge of advanced statistical techniques such as multilevel modeling.
An outline of topics covered during the three-day short course follow sound principles of any data analytic endeavor. The course begins with discussion of longitudinal designs, data management, and exploratory data analysis. Linear mixed-effects models focusing on specifying a model for individuals, means, variances, and covariances will be presented. Maximum likelihood and Bayesian estimation approaches will be discussed as a precursor to drawing inferences through the hypothesis testing paradigm. On the third day, nonlinear longitudinal models will be presented and many extensions to basic models will be discussed.
Examples used in this short course draw primarily from social and behavioral science research, including the fields of education and psychology. Datasets will be made available to participants as well as R scripts to run the examples. Throughout the course, participants will be able to practice exercises using R statistical software. Participants are encouraged to use their own laptops with R pre-installed to perform these exercises. Participants will be instructed on how to download R prior to the course.
Full-time student*: $295
*Full-time students must submit student status proof at https://go.umd.edu/CILVR-STUDENT for prompt processing of the registration.
Free for registered HDQM Department faculty and HDQM degree-seeking students, although you must register through the internal link.
REFUND POLICY: Full refund if cancellation occurs at least 10 business days prior to the workshop date; 50% refund if within 10 days of the first day of the course.
More details and registration instructions available on the LONGITUDINAL-2021 Workshop page.
For any questions, please contact Ms. Jung-Jung Lee at email@example.com.