Regression: Multivariate Analysis
Content
Multivariate analysis involves the statistical investigation of information from multiple cases and multiple variables.
One of the most common forms of multivariate analysis is regression. In regression a distinction is made between a single dependent variable - the phenomenon we want to explain - and independent variables - the factors that may help explain it.
Although most researchers will have some experience with regression, they will have encountered in software and in the literature a great number of variants:
One of the aims of the clinic is to bring some order to these different forms of regression, and to provide practical advice about when and how to utilise each form.
Some of the costs, in terms of assumptions and benefits, in terms of statistical testing of each of these varieties will be highlighted, and the problem how to handle trade-offs that any choice will involve will be discussed. The clinic will give particular attention to ways of clearly communicating the results of regression analyses.
This clinic will be supplemented with online learning materials which can be accessed after the event.
Prerequisites
Introductory understanding of statistics, e.g. the mean, standard deviation and standard error of a variable. If you are attending the clinic as part of our Researcher Development Initiative then you automatically fulfil the prerequisites.