## 04 JulLinear regressions

When the outcome variable is quantitative and continuous, the appropriate statistical model is the linear regression When there is only one explanatory variable which is qualitative, linear regression yields a result close to a Welch or Student T test In an attempt to simplify this, we will name Y the variable that...

## 03 JulUnivariate and multivariable analyses

We can consider the following three types of analyses: descriptive analyses, univariate analyses and multivariable (often unproperly named multivariate) analyses Descriptive analyses are used to describe the data, and are useful for detecting problems Univariate and multivariable analyses allow statistical comparisons (obtaining a p-value), and only multivariable analyses allow confounding factors to...

## 03 JulTransformation of numerical variables

In statistical modeling, it is often necessary to group the numerical variables to create classes in order to meet the conditions of the model. If we have no a priori idea about the appropriate grouping, it is preferable to base ourselves on the splines representing the link between the...

## 03 JulHow to perform a multivariable analysis when you have too subjects

It is sometimes surprising not to be able to carry out a multivariablee analysis because the number of subjects is too small while the file contains several hundred observations (patients, subjects). Linear regressions For linear regressions, i. e. multivariable analyses for which the outcome variable is numerical, it is necessary to have...