Meta-analysis using Stata®



Last update: July 5, 2009

Organizer: Metrika Consulting

Date: Saturday October 17, 2009

Place: Stockholm

Language: English

Deadline: Sign up before October 10, 2009

Cancellation policy: If you have signed up and need to cancel, you do not need to pay any fee if you cancel more than 11 days before the course starts (the dead-line for signing up). You will need to pay half the fee if you cancel less than 11 days before the course starts.

Price: 3000 SEK, excl. VAT.

Registration: Just write an email to Metrika Consulting

Instructor:

Nicola Orsini
The National Institute of Environmental Medicine,
Karolinska Institutet, Stockholm, Sweden.
Phone: +46 8 52487837

Course description

The aim of this course is to provide an overview of methods to perform meta-analysis using Stata. We will cover Stata commands for a variety of tasks: data preparation and input, fixed and random-effect models, forest plots (publication quality graph), heterogeneity across studies, publications bias, sensitivity analysis, meta-regression models and dose-response trend analysis.

Participants

The course is intended for anyone who wishes or needs to use Stata® for meta-analysis of medical literature. No previous knowledge of Stata or of statistics is required, although familiarity with Microsoft Windows will be assumed. Students will gain the familiarity with Stata by practicing.

Preliminary outline of the course

Morning session

  • Brief introduction to Stata
  • Get the data ready for meta-analysis
  • Fixed-effect meta-analysis
  • Random-effect meta-analysis
  • Forest plot

Afternoon session

  • Heterogeneity across studies
  • Assessing publication bias
  • Sensitivity analysis
  • Meta-regression models
  • Dose-response trend analysis
Schedule

  9:00 - 12:00 Morning Session
12:00 - 13:00 Lunch
13:00 - 16:00 Afternoon Session

The students will have their hands on a keyboard with Stata running troughout the learning sessions. Each learning session will give equal weight to tutorials and practical exercises.

Course material

Lecture notes, datasets, exercises, and solutions will be available over the internet for the students.


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