Module leader: Dr Mona Kanaan
This course aims to provide you with the necessary skills and knowledge to allow you to analyse data with an awareness of effect modification and model diagnostics. It expands on the basic introduction to statistical methods provided in the Health and Social Statistics I module. If you want to be able to explore effect modifiers when building your linear or logistic regression models or your outcome is either a time-to-event (survival analysis/Cox regression) or a count (Poisson/Negative binomial regression) then this is the course for you. You will be made aware of the conditions under which the technique may or not may be applied. The course enables you to evaluate the use of a wide range of statistical analysis in published research.
Each session is composed of a lecture and a computer lab session where you have the opportunity to analyse real data using the statistical software STATA. The computer lab sessions offer you a hands on approach to applying statistical techniques with the support of your tutors.
You should normally be a graduate with a 2:1 degree or higher, or equivalent from an overseas university, and be able to demonstrate that you have the necessary knowledge of and interest in a relevant area of health sciences. Applicants are assessed on a case-by-case basis, and we follow the University’s Equal Opportunities policy.
In addition you should be able to demonstrate that you have basic knowledge of regression analysis.
If you successfully complete this course you will be awarded 10 credit points by the University of York, at Level 7. You can also attend the course without completing the assessment.
Please visit www.york.ac.uk/healthsciences/gradschool/funding/.