Pennsylvania State University 3 credits HDFS
The course will provide an overview of the concepts and theory behind dynamical systems. Practical methods for exploring linear and nonlinear relations in multivariate longitudinal data, as well as methods for fitting dynamical systems models to panel and intensive longitudinal data (e.g., diary / experience sampling / ecological momentary assessments) will be presented. Examples may include difference and differential equation models, structural equation models with regime switching/latent transition, and mixture/random effects extensions of these models. A variety of examples of dynamical systems from developmental research, family studies, and intervention science will be presented to provide some perspectives on when Dynamical Systems techniques might be useful. We will also develop hands-on familiarity with different types of dynamical systems by using software programs to simulate, fit, and assess model-fitting results from different dynamical systems models. Students are encouraged to bring research issues and data pertinent to their own interests to class for discussion and critique. Recommended Preparations: HDFS 523 or other equivalents covering regression and multivariate data analysis techniques. The prerequisite may be waived or replaced with other courses in consultation with the instructor. Prior experience in mixed effects modeling and/or structural equation modeling is helpful, but not required.
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