Dr Stephanie MacNeil (course organiser) Chris Metcalfe, Prof Jonathan Sterne, Dr Hayley Jones and Prof Richard Morris.
9-13 May 2016
To provide an understanding of the statistical principles behind, and the practical application of, univariable and multivariable linear and logistic regression in medical, epidemiological and health services research. By the end of the course, students will:
have a thorough conceptual understanding of linear and logistic regression;
appreciate the common threads running through these methods, including stratified analysis, different options for handling explanatory variables, and concepts such as confounding and interaction;
have a working knowledge of the Stata commands to run these models, and a thorough understanding of the output generated from such a package;
know the basis on which analytical strategy and model choice is made, and how the results should be interpreted.
Those analysing data from medical, epidemiological, and health services research, who have used simple methods such as t-tests and chi-square tests, but who now wish to use multivariable methods to control confounding, accommodate interaction, and increase statistical power.
Participants must have knowledge of statistical methods to the level of the Introduction to Statistics course. Knowledge of Stata is essential. Participants will find knowledge of the basic study designs helpful: randomised controlled trials, cross-sectional studies, cohort studies, and case-control studies. Chapter 34 of "Essential Medical Statistics" is at the appropriate level (see Recommended reading below).
Revision of basic methods in a statistical modelling framework; terminology in regression modelling; indicator variables to incorporate categorical explanatory variables; univariable and multivariable regression; common features of linear and logistic regression models; interpretation of model coefficients as differences in means or odds ratios; adjustment for confounding and exploring effect modification (interaction) in multivariable regression; comparing models with Wald tests and likelihood ratio tests; model assumptions; analytical strategies.
Course handouts will cover all material. All participants will be expected to have a copy of 'Essential Medical Statistics' with them during the course: Kirkwood BR, Sterne JAC. Essential Medical Statistics, 2nd ed. Oxford: Blackwell Science, 2003. The book can be purchased at a discount at the time of booking on this course.
For further information please contact email@example.com