Clinical Registry Data Analysis using Stata


This two-day workshop is designed specifically for those interested in the use of Stata to analyse data from longitudinal studies such as clinical registries, routinely collected health data and even cohort studies.

Day 1

The first day includes an introduction to Stata and data management topics such as recoding and computing variables, reshaping and merging datasets. This will be followed by statistical tools and techniques that can be utilised to report data from registries.

Day 2

The second day follows through with more advanced statistical models that would be useful for longitudinal data such as Generalised Estimating Equations (GEE) and time series analysis using Autoregressive Integrated Moving Average (ARIMA) models. Finally, advanced graphics such as risk-adjusted funnel plots, cusum plots will be taught.

Practical sessions

Each lecture will be followed by hands-on practical sessions using realistic clinical registry data, and the sessions are meant to be highly interactive. Participants will be provided with a Stata training license.

Topics covered in this course include:

  • Importing data into Stata, label variables, recode and compute variables, merging and reshaping datasets, simple descriptive statistics
  • Reporting data from registries
  • Longitudinal analysis of registry data- generalized estimating equation (GEE) modelling
  • Longitudinal analysis of registry data- ARIMA modelling
  • Advanced graphics using registry data- funnel plots, cusum charts, etc

Who should attend?

This course is for anyone involved in the design, conduct and analysis of registry/longitudinal data. This includes clinicians, data analysts, health managers and research assistants.

While the information contained herein was correct at the date of publication, Monash University reserves the right to alter procedures, fees and regulations should the need arise.