Course overview
The aim of this course is to enable students to apply appropriate methods to the analysis of data arising from longitudinal (repeated measures) epidemiological or clinical studies, and from studies with other forms of clustering (cluster sample surveys, cluster randomised trials, family studies) that will produce non-exchangeable outcomes. The content includes: paired data; the effect of non-independence on comparisons within and between clusters of observations; methods for continuous outcomes; normal mixed effects (hierarchical or multilevel) models and generalised estimating equations (GEE); role and limitations of repeated measures ANOVA; methods for discrete data: GEE and generalised linear mixed models (GLMM); and methods for count data.
Course learning outcomes
- Recognise the existence of correlated or hierarchical data structures, and describe the limitations of standard methods in these settings
- Develop and analytically describe appropriate models for longitudinal and correlated data based on subject matter considerations
- Be proficient at using statistical software packages (Stata and R) to fit models and perform computations for longitudinal data analyses, and correctly interpret results
- Express the results of statistical analyses of longitudinal data in language suitable for communication to medical investigators or publication in biomedical or epidemiological journal articles
Availability
Class details
Online
Group 1
Class number 60455
Section 01OL
Size 30
Available 30
Class details
Online
Group 1
Class number 25463
Section 01OL
Size 30
Available 30
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