Stata is an interactive data management and statistical analysis program, which has become very popular among researchers in most disciplines. The programme provides a broad range of statistics. It is very user-friendly and also has internet capabilities.

Systematic Stata imageThis is a 1 day course following on from the Introduction to Statistics Using Stata, Data Management & Statistical Analysis Using Stata, Statistical Modelling Using Stata (Continuous Outcomes) and Logistic Regression & Survival Analysis Using Stata courses.

This course goes through the process of a systematic review and presents more advanced techniques such as fixed and random-effects meta-analysis. It also provides explanations of various plots that are presented as well as introducing meta-regression.

Entry requirements: You should have attended the Introduction to Statistics Using Stata course or the Data Management & Statistical Analysis Using Stata course. Preferably you should have also attended the Statistical Modelling Using Stata (Continuous Outcomes) course and the Logistic Regression & Survival Analysis Using Stata course. Otherwise, you should have at least some familiarity with statistics and the Stata software.

Course Tutor: Joseph Eliahoo

This course has been approved by the Royal College of Physicians for 6 CPD credits.

 


EARLY BIRD RATE available upto 4 weeks before course date

Please book your course on-line by clicking on your chosen date below.

Any problems with booking, please contact us on stathelp@imperial.ac.uk.

Please book your place on-line below:

Course Fees

EARLY BIRD RATE

£198.00: Imperial College only.

£333.00: External rate.


STANDARD RATE

£220.00: Imperial College only.

£370.00: External rate

* Click here for Cancellation Policy

Time and Location

The courses will be run online via Microsoft Teams for an unforseeable future.

Exact details will be sent a week prior to the course date

Course Content

  • Systematic reviews/Meta-analysis
  • Fixed-effects meta-analysis
  • Heterogeneity and random-effects meta-analysis
  • Forest plot
  • Publication bias/Funnel plot
  • Galbraith plot
  • Meta-regression