Presented by: Dr. Vincent O'Sullivan
This course is for professionals and researchers who are new to Stata. The course assumes only limited statistical knowledge and experience of using statistical software. The participants will be introduced to Stata’s interface. They will be shown how manage and prepare datasets for analysis. The fundamentals of data analysis and visualization will also be taught. Then, the participants will be introduced to two of the main data analysis tools: linear regression and logistic regression. Participants will be taught the statistical theory behind these methods, and they will apply these methods to specially chosen datasets using examples from health research.
||Q&A with Instructor
Day 1 Getting started with Stata
- Importing data from other formats
- User Interface; Click and go; Command line; Do files:
- Syntax of Stata commands
- Managing Projects, Data, Memory
- Altering Data Structure
- Transforming variables and creating new variables:
- Generating variables;
- Recoding variables
- Renaming variables
- Labelling data
- Storage Types and Working with String Variables
- Working with Dates
- Group-Level Characteristics
- Getting help and on-line resources
- Essential Descriptive Statistics:
- Measures of central tendency; measures of dispersion
- Cross tabulations and correlations
- Testing for differences between groups
- Confidence intervals; hypothesis testing
Day 2 Data analysis
- Histograms; Boxplots
- Kernel density functions
- Bivariate graphs: Scatter plots & Line graphs
- Formatting graphs
- Overlaying multiple plots
- Ordinary Least Squares in Stata
- Interpretation of results
- Model diagnostics
- Graphing actual and fitted values
- Short-comings of the linear probability model
- Theory of logistic regression
- Maximum likelihood estimation
- Interpretation of coefficients: odds ratios; marginal effects
- Multinomial logistic regression
Principal texts for pre- and post-course reading:
Alan C. Acock. 2018. A Gentle Introduction to Stata, Sixth Edition. Texas: Stata Press.
Angrist, Joshua & Jörn-Steffen Pischke (2014) Mastering ’metrics: The path from cause to effect. New Jersey: Princeton University Press.
Terms & Conditions
- Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
- Additional discounts are available for multiple registrations. Contact us for more information.
- Temporary, time limited licences for the software(s) used in the course will be provided. You are required to install the software provided prior to the start of the course.
- Full payment of course fees is required prior to the course start date to guarantee your place.
- Registration closes 1 calendar day prior to the start of the course.
Cancellations or changes to your registration
- 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
- 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
- No fee returned for cancellations made less than 14-calendar days prior to the start of the course.