Clinical Registry Data Analysis Using Stata

The School of Public Health and Preventive Medicine are offering a workshop.

About the workshop: 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 cohort studies.

The workshop will touch on data management and report automation in Stata, and discuss models useful for longitudinal data, including generalised estimating equations (GEE) and autoregressive integrated moving average (ARIMA) models. Data visualisation for funnel plots, CUSUM and survival curves will also be taught. 

Course structure:

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 should bring a laptop and will be provided with a Stata training license.
Day 1

The first day includes an introduction to Stata and data management topics such as recoding and computing variables, reshaping and merging datasets and basic tests of associations.

This will be followed by statistical tools and techniques that can be utilised to automate reporting 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 and survival plots will be taught.
Topics covered

    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 – generalised estimating equation (GEE) modelling
    Longitudinal analysis of registry data – ARIMA modelling
    Advanced graphics – funnel plots, cusum charts, survival plots etc