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This course aims to provide you with the understanding and experience to undertake a basic research project in the social or health sciences using Stata as the statistical tool.
Instructor
Dr Joanna Dipnall is an applied statistician with particular interests in the advanced statistical methods and machine and deep learning techniques. She completed her Honours in Econometrics with Monash University and PhD with IMPACT SRC, School of Medicine, Deakin University. Joanna works extensively with registry and linked medical data and collaborates extensively with the Faculty of IT at Monash to supervise Masters and PhD students to integrate AI within health research. Joanna teaches within the Monash Biostatistics Unit and is the Unit Coordinator for the Monash Masters of Health Data Analytics course. Joanna has taught advanced statistical methods for many years at universities and for ACSPRI.
Course Level
Stata is a comprehensive integrated package for data management, analysis and graphics. Stata has a comprehensive GUI interface. Sample datasets will be provided, but you are encouraged to bring some of your own data for analysis in Excel or ASCII format. Teaching and practice will be closed integrated, and individual assistance will be provided as needed.
The course is suitable for beginners to the Stata package and will be presented in a way that introduces survey research. It is also appropriate to those familiar with Stata as it extends the capabilities of more experienced researchers.
Day 1
Introduction
- About Stata
- Inputting data into Stata
- Exploring data in Stata
- Basic data modifications in Stata
Day 2
Basic Analysis
- Tables and Correlations
- T-tests and analysis of variance
- Handling dates
- Introductrion to Stata graphics
Day 3
More Analysis
- Developing scales
- Factor analysis
- Merging datasets
- Advanced Stata graphic
Day 4
“Day of Regression”
- OLS Regression
- Logistic Regression
- Poisson Regression
- Stepwise Regression
Day 5
Survey Data
- Analysis of survey data in Stata
- Group reposrts using Stata, based on research hypothesis
This course assumes that participants have;
(1) reasonable understanding of statistics to be able to comprehend the material covered in the course outline above (e.g. regression analysis)
(2) some familiarity with a PC environment including keyboard skills and understanding of folder and file structures,
(3) some experience in using Microsoft Word and Excel or their equivalent
(4) some experience using a text editor such as Notepad, UltraEdit.
It does not assume prior experience with Stata, SAS, SPSS or any other specific statistical packages although any such experience would be helpful.
The instructor's bound, book length course notes will serve as the course texts. These will be supplied to you on your 1st day.
No specific references are suggested although participants are encouraged to bring any Stata documentation they may have. For an overview of the Stata package, please visit http://survey-design.com.au or http://stata.com.
Q: Do I have to have any prerequisites to do this course?
A: It would be advised that you have completed an introductory statistics course i.e Fundamentals of Statistics.
I learnt Stata's rationale, which is really useful, rather than only seeing programming. I really recommend this course.
Jo did an amazing job at spending time explaining, allowing for questions and having time to work on an exercise. She took time to check that everyone understood the exercises and worked through them afterwards
I will be using stata a lot for my PhD however had had very minimal instruction on it. This went through the basics and then in depth. If there are things I discover were not covered, I now know how to access information
I have previously used Stata in research previously with little instruction and virtually no guidance. This course joined the dots of my limited knowledge. More importantly, I have learnt a systematic and clear approach to data organisation, file management and replication of research. The course increased my understanding of core analytical methodology in both regression and logistic analysis.
Online was great for this course. We could share screens, add code to chats etc
Good balance of theory and practical group work, and I found doing it online to be better as it could simultaneously run the code and make notes
I feel much more confident using Stata after the course and understand what I'm doing and the language much better.
It was a great course. The online zoom format worked really well. I would be keen to do any future online courses that may become available.
New skills learnt and covered a lot of material in 5 days.
Really enjoyed this class, a good mix of consolidating some basic concepts and applying stata commands. It was great to come away with files I can use as a template for my analyses.
This course improved my knowledge & skills in STATA. I did have very little knowledge on STATA, after this course I learned a lot.
Jo ran an excellent and energetic course both hands on and explained complicated concepts simply. Love the hands on.
Highly relevant to my work & research. Would highly recommend to others.