Clinical Registry Data Analysis Using Stata - PDM1119
- 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.
- 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.
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.
- 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
A/Prof Arul Earnest, who works in the School’s Biostatistics, Data Analytics/Modelling and the Health Economics Division & Clinical Outcomes data Reporting and Research Program.
Additional course information
Participants may register for one or both days of this course
1 day: $550 incl. GST 2 days: $1,100 incl. GST
Alumni discounted fees
10% discount for Student/ Alfred staff/ Monash staff/ Alumni