Complex Samples Logistic Regression Save
Save Variables. This group allows you to save the model-predicted category and predicted probabilities as new variables in the active dataset.
Export model as IBM® SPSS® Statistics data. Writes a dataset in IBM SPSS Statistics format containing the parameter correlation or covariance matrix with parameter estimates, standard errors, significance values, and degrees of freedom. The order of variables in the matrix file is as follows.
- rowtype_. Takes values (and value labels), COV (Covariances), CORR (Correlations), EST (Parameter estimates), SE (Standard errors), SIG (Significance levels), and DF (Sampling design degrees of freedom). There is a separate case with row type COV (or CORR) for each model parameter, plus a separate case for each of the other row types.
- varname_. Takes values P1, P2, ..., corresponding to an ordered list of all model parameters, for row types COV or CORR, with value labels corresponding to the parameter strings shown in the parameter estimates table. The cells are blank for other row types.
- P1, P2, ... These variables correspond to an ordered list of all model parameters, with variable labels corresponding to the parameter strings shown in the parameter estimates table, and take values according to the row type. For redundant parameters, all covariances are set to zero; correlations are set to the system-missing value; all parameter estimates are set at zero; and all standard errors, significance levels, and residual degrees of freedom are set to the system-missing value.
Note: This file is not immediately usable for further analyses in other procedures that read a matrix file unless those procedures accept all the row types exported here.
Export Model as XML. Saves the parameter estimates and the parameter covariance matrix, if selected, in XML (PMML) format. You can use this model file to apply the model information to other data files for scoring purposes. See the topic Scoring Wizard for more information.
To Save Variables in Complex Samples Logistic Regression
This feature requires the Complex Samples option.
- From the menus choose:
- Select a plan file. Optionally, select a custom joint probabilities file.
- Click Continue.
- In the Complex Samples Logistic Regression dialog box, click Save.
- Select the variables that you want to save.