# Select the graphs to display for Fit Mixed Effects Model

Stat > ANOVA > Mixed Effects Model > Fit Mixed Effects Model > Graphs

Select the type of residual to display and which residual plots to show.

Residuals for plots
You can specify marginal or conditional residuals to display on the plots.
• Conditional regular: Conditional residuals are the difference between the conditional fits and the observed values in the sample data. Use the conditional residuals to check the normality of the error term.
• Conditional standardized: Plot the standardized versions of the conditional residuals. If an observation has a standardized residual greater than 2, it may be an outlier in your data.
• Marginal regular: Marginal residuals are the difference between the marginal fits and the observed values in the sample data. Use marginal residuals to evaluate whether the marginal equations can represent the mean responses of y well at different levels of the fixed effect terms.
• Marginal standardized: Plot the standardized versions of the marginal residuals. If an observation has a standardized residual greater than 2, it may be an outlier in your data.
Residuals plots
Use residual plots to examine whether your model meets the assumptions of the analysis. For more information, go to Residual plots in Minitab.
• Individual plots: Select the residual plots that you want to display.
Histogram of residuals
Display a histogram of the residuals.
Normal probability plot of residuals
Display a normal probability plot of the residuals.
Residuals versus fits
Display the residuals versus the fitted values.
Residuals versus order
Display the residuals versus the order of the data. The row number for each data point is shown on the x-axis.
• Four in one: Display all four residual plots together in one graph.
Residuals versus the variables
Enter one or more variables to plot versus the residuals. You can plot the following types of variables:
• Variables that are already in the current model, to look for curvature in the residuals.
• Important variables that are not in the current model, to determine whether they are related to the response.