Explanatory variables

Modified on Fri, 13 Nov, 2020 at 9:51 AM

What are explanatory variables in multivariate analysis?

The aim of a multivariate analysis is to assess the factors influencing a studied variable, called variable to explain, for example the risk factors for the occurrence of a medical complication or the risk factors for death in a disease. The variables used to describe the dependent variable are called independent variables or explanatory variables.

Eg. If the dependent variable is the occurrence of cardiovascular disease, the explanatory variables may be smoking, diabetes, high blood pressure, ...

Which explanatory variables to choose?

When performing a multivariate analysis, the following variables should be studied:

  • Any variable which is known to have an influence on the dependent variable. If it has already been proven in the scientific literature that the age of the patient has an influence on the variable you want to study, you have to include it in the explanatory variables.
  • The variables which are statistically linked to the dependent variable in your study. For example, if you have found a strong association between the dependent variable and the sex of patients, you should probably include it in the explanatory variables.
  • The variable(s) for which your study was designed. For example, if you conduct a randomized controlled trial on a drug, the group in which the patient was randomized should be an explanatory variable.

Was this article helpful?

That’s Great!

Thank you for your feedback

Sorry! We couldn't be helpful

Thank you for your feedback

Let us know how can we improve this article!

Select at least one of the reasons
CAPTCHA verification is required.

Feedback sent

We appreciate your effort and will try to fix the article