Fit, diagnose and interpret regression models for causal questions in Stata.
Multiple regression and causal inference provide researchers with the needed assurance that observed associations are valid. After using a bivariate test (such as chi-squared test, t-test, ANOVA, etc.
Dates to be announced
Registration isn't open yet. Register your interest and we'll contact you first.
Multiple regression models remain the most widely known approach for controlling for confounding, identifying risk factors and estimating independent effects. They are also commonly used to build predictive models, and the principles underlying them have influenced many modern artificial intelligence methods. Therefore, all quantitative researchers should be able to understand, build and interpret multiple regression models. Yet, many researchers who are comfortable with bivariate tests have never built or fully interpreted a regression model, leaving a critical gap between the analyses they conduct and the conclusions they need to draw. This course closes that gap.
This course is designed for quantitative researchers who are already proficient in descriptive statistics. Being comfortable conducting hypothesis tests, such as chi-squared tests, t-tests, and ANOVA, will be a plus. Using Stata as the analytical platform, participants will move from the bivariate tests to the regression models that extend and formalise them. By the end of the course, participants will be equipped to build, interpret and critically evaluate linear and logistic regression models, and to apply them with confidence in their own research. They will also be able to extend their knowledge and skills into other models in the generalised linear model family, including Poisson and binomial models.
Participants will consolidate their understanding of inferential statistics, conduct bivariate tests, and examine how these tests connect directly to regression models. They will develop a clear conceptual grasp of confounding and bias and understand why controlling for these is central to valid causal inference.
After completing this course, participants will be able to build and interpret linear and logistic regression models with confidence. They will understand the link between the bivariate tests they already know and the regression models that extend them. They will be able to adjust for confounders, estimate independent effects, and distinguish between causal and predictive modelling objectives — strengthening the rigour and credibility of their quantitative research.
“I have always wanted to become an excellent migration policy analyst, and I knew understanding data was the missing piece. This course helped me connect data analysis with policy and governance. I can now independently explore findings, identify patterns and contribute more meaningfully to evidence-based migration policy discussions.”
“Having worked in data management for about 10 years, I discovered that there were things I had been doing without fully understanding why. This course gave me a clearer understanding of inferential statistics. I also learned valuable teaching techniques, particularly the importance of engaging students and respecting their time.”
“Before this course, I knew what data was but didn’t understand data analysis or how relevant it was to my work. I now see how it can help me organise information, interpret findings, track the impact of my interventions, improve my programmes and make better decisions in mental health and adolescent counselling.”
“I particularly appreciate the teaching method and the respect shown to every participant. I know I still have more to learn, but I now have the confidence and foundation to keep practising.”
Advanced Course in Multiple Regression and Causal Inference Using Stata. Fields marked * are required.
Dates have not been set yet. Register your interest and we'll contact you as soon as a cohort is planned.
We'll contact you by email, phone or WhatsApp with the dates, delivery format and fee. Registering your interest doesn't commit you to anything.
Yes. Contact CESAR to discuss your objectives, preferred delivery format and training needs, and we'll tailor the course to your team.
Register your interest and hear first when the next cohort opens.
Register Your Interest
