Courses with the PREV_SCI Subject

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The online catalog includes the most recent changes to courses and degree requirements that have been approved by the Faculty Senate, including changes that are not yet effective. Courses showing two entries of the same number indicate that the course information is changing. The most recently approved version is shown first, followed by the older version, in gray, with its last-effective term preceding the course title. Courses shown in gray with only one entry of the course number are being discontinued. Course offerings by term can be accessed by clicking on the term links when viewing a specific campus catalog.

Prevention Science (PREV_SCI)

508 Longitudinal Structural Equation Modeling 3 Longitudinal structural equation modeling and the use of Mplus statistical software to perform and interpret a broad range of longitudinal structural equation models. Recommended preparation: ED PSYCH 576, PSYCH 514, PSYCH 516, or previous knowledge of multivariate analysis and factor analysis.

510 Multilevel Modeling II: Advanced Multilevel Models for Longitudinal Data 3 Advanced applications of the general linear mixed model (aka multilevel model, hierarchical linear model, latent growth curve model, random coefficients model) used to analyze data from longitudinal, repeated measures designs; conduct cumulative steps in a longitudinal multilevel analysis, including setting up data file and coding variables, evaluating fixed and random effects and interpreting covariance structures, predicting between- and within-person variation using time-invariant and time-varying covariates, and interpreting empirical findings. Recommended preparation: ED PSYCH 575 or previous knowledge of multivariate analysis and multilevel modeling.

511 Introduction to Prevention Science 3 Disciplinary roots; the epidemiological approach to risk and prevention; design, implementation, and dissemination of preventive interventions.

512 Finite and Growth Mixture Modeling 3 Introduction to a specific type of latent variable statistical models, commonly referred to as finite mixture models, which include several distinct subtypes including latent class analysis, latent profile analysis, latent transition analysis, and latent class growth analysis; conceptual background for models and application of models in practice. Recommended preparation: ED PSYCH 514 and ED PSYCH 576, or knowledge of multivariate analysis and psychometrics.

513 Research Methods in Prevention Science 3 Introduction to process of research and methods in prevention science; techniques of research, data collection, and data analysis procedures.

535 Effective Prevention Strategies I 3 Community mobilization and problem analysis; program selection, implementation, and management; grant writing.

540 Effective Prevention Strategies II 3 Evaluation of prevention science programs.

700 Master's Research, Thesis, and/or Examination V 1-18 May be repeated for credit. Independent research and advanced study for students working on their master's research, thesis and/or final examination. Students must have graduate degree-seeking status and should check with their major advisor/committee chair before enrolling for 700 credit. S, U grading.

800 Doctoral Research, Dissertation, and/or Examination V 1-18 May be repeated for credit. Course Prerequisite: Admitted to the Prevention Sciences PhD program. Independent research and advanced study for students working on their doctoral research, dissertation and/or final examination. Students must have graduate degree-seeking status and should check with their major advisor/committee chair before enrolling for 800 credit. S, U grading.