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Courses offered

Introduction to Statistical Modelling

Academic Lead: Dr Ioannis Bakolis

Date: 21st January – 25th January 2019

Last booking date:  10th January 2019

Time: 09:00-17:30

Venue: Rubin Murray Lecture Theater, Main Building, Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King's College London. View Map.

Cost:

  • External Early bird: £675 (till 15/10/18, price thereafter £750)
  • KCL Staff Early bird: £506.25 (till 15/10/18, price thereafter £562.5)
  • KCL Student Early bird: £337.5 (till 15/10/18, price thereafter £475)
  • Other Student Early bird: £506.25 (till 15/10/18, price thereafter £562.5)
  • Kings Health Partner Early bird: £506.25 (till 15/10/18, price thereafter £562.5)

BOOKING: Booking for this course has now closed. 


 

COURSE AIM

To understand the theoretical basis of generalized linear and generalised mixed models to apply to a diverse range of practical problems. To relate modern statistical models and methods to real life situations and use relevant computer software (STATA) for statistical analysis.

REQUIREMENTS

This workshop will assume that participants have a good knowledge of basic regression, any syntax based statistical software, such as STATA (such as can be obtained from the BHI Introduction to Programming course running in October). Participants will need to bring their own laptop computer with STATA installed.

LEARNING OUTCOMES

Subject specific: Knowledge, Understanding and Skills

  • At the end of the course the students should be able to demonstrate subject specific knowledge, understanding and skills and have the ability to:
  • Develop an understanding of the underlying assumptions and principals of statistical modelling *Understand the foundation theory of Generalised Linear Models and Generalised Linear Mixed Models
  • Identify appropriate methods of estimation using Bayesian and frequentist approaches
  • Understand different missing data mechanisms and their assumptions
  • Formulate sensible models for a set of data, conduct statistical inference and interpret the results of any analysis.
  • Critique, and adapt, statistical models to cope with atypical error structures and non-independence
  • With limited guidance, deploy established techniques of analysis and enquiry in scientific endeavour

General: Knowledge, Understanding and Skills

  • On successful completion of this module the student should be able to
  • Understand and explain the role of statistical models.
  • Justify and critique the use of statistical methods for real life applications.
  • Show confidence in the use of STATA to implement statistical models for real life application.

 

Please note the following:

If you would like to pay by internal transfer, please contact iop-biostatisticseducation@kcl.ac.uk

Your place will not be confirmed until payment has been made.

Failure to cancel without sufficient notice will forfeit your course fee and access to future courses.

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