Overview
This advanced course develops statistical methods for longitudinal, clustered, repeated-measures, and time-to-event data. It covers correlation structures, generalized estimating equations, linear and generalized linear mixed-effects models, subject-specific and population-averaged inference, missing data mechanisms, multiple imputation, informative dropout, survival and hazard functions, Kaplan–Meier estimation, log-rank testing, Cox proportional hazards models, time-varying covariates, competing risks, recurrent events, frailty models, and parametric and flexible survival models.
Students prepare complex datasets, select and compare appropriate models, assess assumptions and diagnostics, interpret longitudinal effects and hazard ratios, address confounding and effect modification, evaluate causal interpretations, quantify uncertainty, and communicate findings through transparent, reproducible statistical reports using contemporary software.
Learning Outcomes
- Design appropriate longitudinal and survival analyses for repeated, clustered, and time-to-event study data.
- Select and justify correlation structures, estimating procedures, and mixed-effects models for dependent observations.
- Fit and compare generalized estimating equation, mixed-effects, survival, frailty, competing-risks, recurrent-event, and flexible parametric models.
- Diagnose missingness, informative dropout, dependence, nonproportional hazards, influential observations, and other threats to model validity.
- Evaluate model adequacy using statistical diagnostics, sensitivity analyses, predictive assessments, and assumption checks.
- Interpret population-averaged and subject-specific effects, hazard ratios, uncertainty intervals, effect modification, confounding, and causal limitations.
- Synthesize complex analyses into scientifically appropriate conclusions for specialist and non-specialist audiences.
- Produce transparent, reproducible analytical workflows and reports using statistical software and version-controlled documentation.
Timetable
| Type | Length | Frequency | Period |
|---|---|---|---|
| Lecture | 2 hours | Weekly | All semester |
| Lab | 2 hours | Weekly | All semester |
| Tutorial | 1 hour | Fortnightly | All semester |
Assessment Schedule
| Type | Description | Weighting |
|---|---|---|
| Assignment | Data preparation and reproducible analysis assignment (1 × 15%) | 15.00% |
| Test | Longitudinal modelling practical test (1 × 20%) | 20.00% |
| Assignment | Survival analysis assignment (1 × 15%) | 15.00% |
| Quiz | Advanced modelling quizzes (4 × 5%) | 20.00% |
| Deliverable | Reproducible integrative analysis report (1 × 10%) | 10.00% |
| Exam | Final examination (1 × 20%) | 20.00% |
Teaching Staff & Programs
This course is delivered jointly by faculty from the participating programs listed below. In line with the Douchewater Way, the University of Sexology tailors core instruction directly to each cohort's specific discipline — adapting curriculum to program needs rather than forcing students into a one-size-fits-all model. Learn more about our approach at The Douchewater Way.