Logistic Regression
Notes

 Output Created                                     05-AUG-2026 12:35:10        
 Comments                                                                       
 Input                  Data                        D:\opencode\spss-studio-mcp 
                                                    \examples\data\survival_stu 
                                                    dy.sav                      
                        Filter                      <none>                      
                        Weight                      <none>                      
                        Split File                  <none>                      
                        N of Rows in Working Data   150                         
                        File                                                    
 Missing Value Handling Definition of Missing       User-defined missing values 
                                                    are treated as missing      
 Syntax                                             LOGISTIC REGRESSION         
                                                    VARIABLES=status            
                                                    /METHOD=ENTER treatment     
                                                    time.                       
                                                                                
 Resources              Processor Time              00:00:00.02                 
                        Elapsed Time                00:00:00.01                 

D:\opencode\spss-studio-mcp\examples\data\survival_study.sav
Case Processing Summary

 Unweighted Cases(a)                      N   Percent 
 Selected Cases      Included in Analysis 150 100.0   
                     Missing Cases        0   .0      
                     Total                150 100.0   
 Unselected Cases                         0   .0      
 Total                                    150 100.0   
a If weight is in effect, see classification table for the total number of cases.

Dependent Variable Encoding

 Original Value Internal Value 
 删失         0              
 死亡         1              

Block 0: Beginning Block
Classification Table(a,b)

      Observed            Predicted                
                          结局状态  Percentage 
                          删失 死亡 Correct    
 Step 结局状态 删失 0      29     .0         
 0                 死亡 0      121    100.0      
      Overall Percentage                80.7       
a Constant is included in the model.
b The cut value is .500

Variables in the Equation

                 B     S.E. Wald   df Sig. Exp(B) 
 Step 0 Constant 1.428 .207 47.736 1  .000 4.172  

Variables not in the Equation

                             Score df Sig. 
 Step Variables 治疗方案 .091  1  .763 
 0              随访月数 .019  1  .891 
      Overall Statistics     .183  2  .913 

Block 1: Method = Enter
Omnibus Tests of Model Coefficients

            Chi-square df Sig. 
 Step Step  .182       2  .913 
 1    Block .182       2  .913 
      Model .182       2  .913 

Model Summary

 Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square 
 1    147.124(a)        .001                 .002                
a Estimation terminated at iteration number 4 because parameter estimates changed by less than .001.

Classification Table(a)

      Observed            Predicted                
                          结局状态  Percentage 
                          删失 死亡 Correct    
 Step 结局状态 删失 0      29     .0         
 1                 死亡 0      121    100.0      
      Overall Percentage                80.7       
a The cut value is .500

Variables in the Equation

                   B     S.E. Wald  df Sig. Exp(B) 
 Step 治疗方案 .187  .462 .163  1  .686 1.205  
 1(a) 随访月数 .006  .019 .091  1  .763 1.006  
      Constant     1.065 .870 1.501 1  .220 2.902  
a Variable(s) entered on step 1: 治疗方案, 随访月数.

