General Loglinear Analysis Save
Select the values you want to save as new variables in the active dataset. The suffix n in the new variable names increments to make a unique name for each saved variable.
The saved values refer to the aggregated data (cells in the contingency table), even if the data are recorded in individual observations in the Data Editor. If you save residuals or predicted values for unaggregated data, the saved value for a cell in the contingency table is entered in the Data Editor for each case in that cell. To make sense of the saved values, you should aggregate the data to obtain the cell counts.
Four types of residuals can be saved: raw, standardized, adjusted, and deviance. The predicted values can also be saved.
- Residuals. Also called the simple or raw residual, it is the difference between the observed cell count and its expected count.
- Standardized residuals. The residual divided by an estimate of its standard error. Standardized residuals are also known as Pearson residuals.
- Adjusted residuals. The standardized residual divided by its estimated standard error. Since the adjusted residuals are asymptotically standard normal when the selected model is correct, they are preferred over the standardized residuals for checking for normality.
- Deviance residuals. The signed square root of an individual contribution to the likelihood-ratio chi-square statistic (G squared), where the sign is the sign of the residual (observed count minus expected count). Deviance residuals have an asymptotic standard normal distribution.
Saving New Variables
This feature requires the Advanced Statistics option.
- From the menus choose:
- In the General Loglinear Analysis dialog box, click Save.