IBM SPSS COMPLEX SAMPLES 19 Water System User Manual


 
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Complex Samples Logistic Regression
Complex Samples Logistic Regression Save
Figure 10-7
Logistic Regression Save dialog box
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 SPSS Statistics data. Writes a dataset in IBM® SPSS® Statistics format containing
the parameter
correlation or covariance matrix with parameter estimates, standard errors,
signicance values, and degrees of freedom. The order of variables in the matrix le is as follows.
rowtype_. Takes values (and value labels), COV (Covariances), CORR (Correlations), EST
(Parameter e
stimates), SE (Standard errors), SIG (Signicance 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 p arameter 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, signicance levels, and residual degrees of freedom are set to
the system
-missing value.
Note:Thisle is not immediately usable for further analyses in other procedures that read a matrix
le unless those procedures accept all the r ow 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 le to apply the model information to
other data les for scoring purposes.