Modeling and Multivariate Methods - SAS

310 Fitting Dispersion Effects with the Loglinear Variance Model Chapter 12
Loglinear Platform Options
Does the variance model fit significantly better than the original model? The likelihood ratio test for this
question compares the fitted model with the model where all parameters are zero except the intercept, the
model of equal-variance. In this case the p-value is highly significant. Changes in Hold Time change the
variance.
The Variance Effect Likelihood Ratio Tests refit the model without each term in turn to create the
likelihood ratio tests. These are generally more trusted than Wald tests.
Loglinear Platform Options
The red triangle menu next to Loglinear Variance Fit contains the following options.
Table 12.1 Descriptions of Loglinear Platform Options
Save Columns
Creates one or more columns in the data table. See “Save Columns” on
page 310.
Row Diagnostics Plots row diagnostics. See “Row Diagnostics” on page 311.
Profilers
Model Dialog
Script
Opens the Profiler, Contour Profiler, or Surface Profiler. See “Factor
Profiling” on page 92 in the “Fitting Standard Least Squares Models”
chapter.
Shows the completed launch window for the current analysis.
Contains options that are available to all platforms. See Using JMP.
Save Columns
Table 12.2 Descriptions of Save Columns Options
Prediction Formula
Variance Formula
Std Dev Formula
Residuals
Studentized Residuals
Creates a new column called Mean. The new column contains the predicted
values for the mean, as computed by the specified model.
Creates a new column called Variance. The new column contains the
predicted values for the variance, as computed by the specified model.
Creates a new column called Std Dev. The new column contains the
predicted values for the standard deviation, as computed by the specified
model.
Creates a new column called Residual that contains the residuals, which are
the observed response values minus predicted values. See “Examining the
Residuals” on page 311.
Creates a new column called Studentized Resid. The new column values are
the residuals divided by their standard error.