The main objectives of this module are:
Upon completing this course the student should be able to:
- Choose an appropriate multivariable statistical technique to analyze data gathered in the context of medical scientific research.
- Perform multivariable regression analyses with the aid of the computer package R/SPSS, interpret the results, and report the conclusions.
- Describe (roughly) the statistical background of some multivariable analysis techniques that are frequently applied in medical scientific research.
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The module
To a large extent, medical research is aimed at identifying associations between two variables. For example, we may be interested in the association between an independent variable treatment and a dependent variable survival. However, in most cases there are other variables that act as confounders of an observed association and have to be taken into account. Although we are not directly interested in the confounders, they (partially) explain the relationship between the explanatory and outcome variables. It is important to take potential confounders into consideration in order to properly understand the association between the variables that we are interested in. This course considers techniques that correct for potential confounders and provide a valid statistical interpretation of confounded relationships. Confounding can be controlled for analytically, using either stratified analyses or through the use of multiple regression techniques. The regression approaches considered in this course are also used when one is interested in the relationship between one variable (the dependent variable) and a number of other explanatory variables considered simultaneously. Multivariable analysis methods are very useful, particularly in the context of observational epidemiological research. The statistical package R or SPSS is used for the practical training of those techniques.
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