**Univariate
analysis**

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This module tests for associations
between each independent variable and each outcome. It is used to identify
potential risk factors and confounders.

Given a set of outcomes, a set of
risk factors and a set of covariates, this module will perform univariate
regression for *each* outcome with each
risk factor and each covariate.

The module automatically detects
whether the outcome variable is binary or continuous and selects logistic or
linear regression as appropriate. You also can specify the distribution
and link function for each outcome manually, right click the variable and then
select “Change functions”. In the popup window, select the distribution and
link function.

If a stratified variable is
specified, this module will report the associations within each subgroup as
well as the whole sample.

**What
it’s used for**

Univariate analysis is usually the
first step to assess the association between the risk factor and outcome, and
to identify potential confounders.

**Screen
shot of sample designs:**

Sample
output tables: