LONGITUDINAL ANALYSIS WITH LATENT VARIABLES Syllabus
Course Learning ObjectivesUpon successfully completing this course, students will be able to: to be added at a later date
Acquaints students with the use of latent variables in longitudinal data analysis as it is conceptualized in the Mplus framework. Focuses on modeling opportunities for observed categorical (binary and ordinal) and count variables with both continuous and categorical latent variables. Using standard linear regression models as a point of departure, covers binary and ordinal logistic regression; latent growth curve models with binary and ordinal outcome variables; Poisson regression; Poisson and zero-inflated Poisson (ZIP) latent growth curve models; discrete- and continuous-time survival analysis; and latent transition analysis. Students study examples drawn from available public date sets.
Students with an interest in the use of latent variables in longitudinal data analysis as it is conceptualized in the Mplus framework. Not appropriate for undergraduate students.
Methods of Assessment
Grading Policy: Based on active participation and written lab reports.
Grading Restrictions: Letter grade
330.657 and 140.658 (2 terms) or equivalent
Academic Ethics Code
The code, discussed in the Policy and Procedure Memorandum for Students, March 31, 2002, will be adhered to in this class:
Students enrolled in the Bloomberg School of Public Health of The Johns Hopkins University assume an obligation to conduct themselves in a manner appropriate to the University's mission as an institution of higher education. A student is obligated to refrain from acts which he or she knows, or under the circumstances has reason to know, impair the academic integrity of the University. Violations of academic integrity include, but are not limited to: cheating; plagiarism; knowingly furnishing false information to any agent of the University for inclusion in the academic record; violation of the rights and welfare of animal or human subjects in research; and misconduct as a member of either School or University committees or recognized groups or organizations.
Disability Support Services
If you are a student with a documented disability who requires an academic accommodation, please contact Betty H. Addison in the Office of Student Life Services: firstname.lastname@example.org, 410-955-3034, or 2017 E. Monument Street.