This one-day introductory course is for people interested in using Stata for research. No prior knowledge of Stata is required.

Outline:

• Brief overview of Stata’s statistical, graphical, and data-management capabilities
• Introduction to the Stata working environment
• Using Stata via the Graphical User Interface and the Command window
• Understanding Stata’s command syntax
• Helping you help yourself—introducing Stata’s online help facilities
• Working efficiently with do-files
• Saving results output in a log file

This one-day introductory course is intended for people who would like to be able to produce publication-quality graphs using Stata. Some experience of using Stata and some level of statistical knowledge would be helpful though not essential.

Outline:

• Introduction to Stata graphics
• Resources for learning Stata graphics
• Producing graphs using the Graphical User Interface
• Producing graphs using the command syntax in do-files
• Editing graphs using Stata’s Graph Editor
• Combining graphs
• Graph schemes

This one-day introductory course is intended for people who are reasonably familiar with Stata (for example, those who have attended the one-day introduction to Stata course) but who would like to develop their data-management skills and work more efficiently.

Outline:

• Introduction to course and brief review of Stata basics
• Introduction to how Stata is organized
• Loading data into Stata from non-Stata formats
• Useful functions for creating summary variables
• Dealing with string variables and dates in Stata
• Changing the shape of your data
• Creating summary datasets
• Using Stata’s system variables for data-management tasks
• Some simple programming tools for saving time

This two-day introductory statistics course is intended for people who are reasonably familiar with Stata (for example, those who have attended the one-day introduction to Stata course) but who would like to develop their statistical analysis skills.

Outline:

• Introduction to course and data
• Principles of statistical analysis
• For each of continuous, binary, and time-to-event outcomes:
  • Fitting models in Stata and understanding the output
  • Including categorical explanatory variables
  • Fitting multiple explanatory variables
  • Fitting interactions
  • Comparing models and model selection
  • Obtaining model predictions
  • Reporting results
• For time-to-event outcomes:
  • Setting up survival data in Stata