UPCOMING WEBINAR: Optimize product ranges using TURF, Factor, and Correspondence Analysis 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