Applied Longitudinal Data Analysis

Course Description

Students learn techniques for analysis of intensive longitudinal data in the social sciences. The purpose of this course is to facilitate formulation of research questions, design of studies, measurement devices, and methods of analysis suitable for the types of empirical data obtained in intensive longitudinal studies (e.g., diary / experience sampling / ecological momentary assessment) being used in the social sciences. Students will gain skills useful in the study of developmental or other change-based processes. In particular, students will gain abilities related to research conceptualization, research design, data analysis, results interpretation, and the presentation and critique of longitudinal research. The course will (1) highlight general issues regarding the link between process-oriented research questions and longitudinal study designs, (2) survey a selection of intraindividual change and variability concepts, (3) provide step-by-step instruction on data manipulation, graphing, and the analysis of intensive repeated measures data (univariate and multivariate), and (4) develop students' skill in effectively communicating the features of longitudinal data and results of longitudinal analysis. Specific topics include the use of intraindividual variability metrics, multilevel models, generalized multilevel models, multivariate multilevel models, and P-technique factor analysis for measurement and modeling of dynamic characteristics and dynamic processes; the design and implementation of multiple time-scale studies; and how new technologies are shaping both the collection and analysis of intensive longitudinal data in the social sciences.

Code

HDFS 575

Credits

3

Subject

HDFS