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.

Stata is a statistical analysis software designed for researchers. This software enables data manipulation, visualisation, statistics, and reproducible reporting.

Course structure


  • 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 should bring laptops and will be provided with a Stata training license.

Scholar testimonials

The last Clinical Registry Data Analysis using Stata course taught by A/Prof Arul Earnest received an average rating of 4.65/5 on the participant evaluation form assessing the overall quality of the course. Quote from a past participant

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

Who should attend

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

Course Director

A/Prof Arul Earnest

PhD, MSc, DLSHTM, B.Soc.Sc(Hons)

Monash University


Arul is currently an Associate Professor with the Biostatistics Unit and senior Biostatistician with the Registry Sciences Unit in the Department of Epidemiology and Preventive Medicine. He was previously Director of the Centre for Quantitative Medicine (CQM) at Duke-NUS in Singapore. His current research interest is in risk adjustment and time series analysis of clinical registry data and Bayesian spatio-temporal models. He has developed and applied these models on a number of clinical registries in Australia and internationally.

For close to 20 years, Arul has provided consultative and collaborative methodological input to various collaborators. The outcome for some of this work has been more than 178 publications in a variety of peer-reviewed international journals, including BMC Health Services Research, BMJ and JAMA, and numerous presentations. He is the author of the book entitled “Essentials of a Successful Biostatistical Collaboration” published in September 2016 by CRC Press. He has been awarded several research awards including the University of Sydney International Research Collaboration Award in 2013 and the SingHealth Partners in Education Award: RISE award for mentors and teachers of residents in Singapore. Arul has secured more than 13 grants. He has published a number of methodological papers in the Bayesian field, and also contributed to two book chapters, including one on disease mapping using Bayesian hierarchical models, in collaboration with Queensland University of Technology, Viertel Centre for Research in Cancer Control and CRC for Spatial Information, Australia. Arul currently teaches into the Masters of Public Health program in Monash University and is coordinating one of the units. He is also co-supervising 5 PhD. Arul has previously taught and mentored medical students, clinician researchers and statisticians.

He was awarded the status of Chartered Statistician (C.Stat) by the Royal Statistical Society in London in 2003. He had previously served as the academic editor of the editorial board of PLOS ONE, a non-profit, open-access, online publication that reports on original research from all disciplines within science and medicine as well as a Local Review Panel (LRP) member for the National Medical Research Council Clinician Scientist Individual Research Grant Scheme, as well as the National Healthcare Group Domain-Specific Review Board in Singapore. He has been in several organising committees for national as well as international conferences, including the International Society of Bayesian Analysis (ISBA) conference in 2008.

A/Professor Arul Earnest will be assisted by Dr Farhad Salimi and Ms Breanna Pellegrini to conduct this workshop.