# Regression

## Test multivariate associations using regression techniques

Regression is a statistical technique used to understand multivariate associations between predictor, demographic, prognostic, clinical, confounding variables and outcome variables. The type of regression technique used depends upon the scale of measurement of the outcome variable. Click on a button below to learn more about that type of regression.

### Types of regression

Regression analysis for a dichotomous categorical outcome.

Regression analysis for a polychotomous categorical outcome.

Regression analysis for an ordinal outcome.

Regression analysis for survival or time-to-event based on a dichotomous categorical outcome.

Regression analysis for a continuous outcome.

Regression analysis for a count outcome where the mean is higher than the variance.

Regression analysis for a count outcome where the variance is higher than the mean.

Use regression models to generate the probability of a disease state given known risk factors and provide a scoring system for clients and clinicians.

### Methods of regression

There are three different methods of conducting a regression model. Different methods allow researchers to 1) control for confounding variables (

__), 2) choose the best set of predictor variables that account for the most variance in an outcome (__**simultaneous regression**__), or 3) test theoretical models (__**stepwise regression**__). Click on a__**hierarchical regression****button**below to learn more.### Regression diagnostics

Regression diagnostics are absolutely necessary when conducting any of the aforementioned regression analyses. Click on a button below to learn more about each type of diagnostic test.

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