This article describes how to create a Goodness-of-Fit Plot from a regression output. It produces a scatterplot of target outcomes (x-axis) versus fitted values (y-axis). The Spearman's rank correlation coefficient is shown. A high correlation indicates that fitted values are ranked in a similar order to target outcomes. Points should be randomly scattered around a 45 degree line through the origin.

## Requirements

- A regression output (eg. binary logit, poisson, ordered logic, linear, etc.)

## Method

- With the regression output selected, from the
**object inspector**, go to**DIAGNOSTICS > Plot - Goodness of Fit**. - OPTIONAL: Input the maximum number of points to plot into the
**Maximum Points**menu. If the object contains more data points, a random sample is taken.

## Next

How to Run Binary Logit Regression

How to Run a Generalized Linear Model

How to Run a Multinomial Logit Regression

How to Run NBD Regression in Displayr

How to Run Ordered Logit Regression

How to Run Quasi-Poisson Regression

How to Run a Stepwise Regression

How to Create a Goodness of Fit Plot from a Dimension Reduction Output

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