Program Overview

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Clinical Registry Data Analysis Using Stata

Overview

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.

Who Should Attend

This course is designed for anyone involved in the design, conduct and analysis of registry/longitudinal data. This includes clinicians, data analysts, health managers and research assistants. Those with no Stata background are welcomed, as the software would be taught and introduced in Day 1. All software codes for the lectures and practical sessions will be provided, along with a time-limited training license for Stata software.

What You Will Learn

Topics covered are:

• 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

Program 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.

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.

Testimonials

All the speakers are very good and very supportive and kind. Very worthwhile, thanks!

Professor Arul Earnest

Professor Earnest is a leading academic research biostatistician at the Biostatistics Unit & Deputy Head, Clinical Outcomes Data Reporting and Research Program (CORRP) at the School of Public Health & Preventive Medicine (SHPHM). He has authored a successful textbook, three book chapters, and 245 publications in peer-reviewed international medical journals, earning 19 scientific awards and scholarships. With an H-index of 54 and an I10-index of 173 (citations=10742), his expertise in biostatistics is well-recognized.

Learn More

Learn more about Professor Earnest

Learn more about the program's terms and conditions.

This course is provided by the School of Public Health and Preventive Medicine

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• A-Z index
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Contact

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• Recruit a student
• Pay online

News

• Latest news
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• Monash Life

On Our Site

• Who we are
• Find a course
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• Partner with Monash
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