Regression with Categorical Dependent Variables: An Introduction using STATA
Module fact file
- Masters Level
- Summer Term
- Contact Hours:
- Over two days
- 10 credits
- The course assumes that you have prior knowledge of common commands in Stata to organise and handle data and undertake standard regression techniques.
The module is run as a two-day statistical workshop on regression analysis with categorical dependent variables using the Stata software. It will include both taught and practical exercises using data series distributed by the module leader.
The taught component will include an overview of the most commonly used regression models for categorical outcomes: binary logit and probit, ordinal logit and probit and multinomial logit. Example data will be used to explore these estimation methods.
The emphasis in the practical component will be on the application of appropriate techniques and interpreting results using secondary data and the interpretation of results.
By the end of the two days you should have a good understanding of how to run your own regressions with categorical dependent variables using Stata and how to interpret their results.
On completion of the module, you will be able to:
- Assess and be able to interpret results in published research using regression methods with categorical dependent variables.
- Demonstrate a good understanding of modelling and interpretation of regression models with categorical dependent variables.
- Identify which limited dependent variable models are best suited to address specific research questions.
- Carry out regression analysis, interpret results and construct graphs for regression models with categorical dependent variables.
1 x 2,500 word assignment (100%)
The optional modules listed on the website for this programme may unfortunately occasionally be subject to change. As you will appreciate key members of staff may leave the University and this necessitates a review of the modules that are offered. Where the module is no longer available we will let you know as soon as we can and help you make other choices.