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140.608.11 Analysis of Longitudinal Data

Department:
Biostatistics
Term:
Summer Inst. term
Credits:
2 credits
Academic Year:
2019 - 2020
Location:
East Baltimore
Dates:
Mon 06/17/2019 - Fri 06/21/2019
Class Times:
  • M Tu W Th F,  8:30 - 11:50am
Auditors Allowed:
No
Grading Restriction:
Letter Grade or Pass/Fail
Contact:
Ayesha Khan
Course Instructor:
Resources:
Prerequisite:

Intermediate level biostatistics and epidemiology

Description:

Covers statistical models for drawing scientific inferences from longitudinal data. Topics include longitudinal study design; exploring longitudinal data; linear and generalized linear regression models for correlated data, including marginal, random effects, and transition models; and handling missing data.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Prepare graphical or tabular displays of longitudinal data that effectively communicate the patterns of scientific interest
  2. Use a general linear model to make scientific inferences about the relationship between response and explanatory variables while accounting for the correlation among repeated responses for an individual
  3. Use marginal, random effects, or transitional generalized linear models to make scientific inferences when the repeated observations are binary, counts, or non-Gaussian continuous observations
  4. Use SAS or STATA to conduct the appropriate longitudinal data analyses
Methods of Assessment:

Student evaluation based on analysis of a longitudinal data set, presentation of the results, and a written scientific report of the analysis methods and results

Instructor Consent:

No consent required

Special Comments:

Enrollment limited; students are required to bring a laptop to class, with Stata installed.