1-1 Match Pairs

Social Survey Example

[Data] In the 2000 General Social Survey, 1144 subjects were asked whether, to help the environment, they would be willing to (1) pay higher taxes or (2) accept a cut in living standards.

Social Survey Example

		Cut Living Standards
Pay Higher Taxes	Yes	No	Total
Yes	227	132	359
No	107	678	785
Total	334	810	1144

McNemar’s test

data survey;
 input HigherTax $ LivingStandard $ Count;
 datalines;
Yes Yes 227
Yes No 132
No Yes 107
No No 678
;
proc freq data=survey;
weight count;
tables HigherTax *LivingStandard/ agree; exact mcnem;
run;

                            The FREQ Procedure

                   Table of HigherTax by LivingStandard

                    HigherTax     LivingStandard

                    Frequency|
                    Percent  |
                    Row Pct  |
                    Col Pct  |No      |Yes     |  Total
                    ---------+--------+--------+
                    No       |    678 |    107 |    785
                             |  59.27 |   9.35 |  68.62
                             |  86.37 |  13.63 |
                             |  83.70 |  32.04 |
                    ---------+--------+--------+
                    Yes      |    132 |    227 |    359
                             |  11.54 |  19.84 |  31.38
                             |  36.77 |  63.23 |
                             |  16.30 |  67.96 |
                    ---------+--------+--------+
                    Total         810      334     1144
                                70.80    29.20   100.00

            Statistics for Table of HigherTax by LivingStandard

                              McNemar's Test
                       ----------------------------
                       Statistic (S)         2.6151
                       DF                         1
                       Asymptotic Pr >  S    0.1059
                       Exact      Pr >= S    0.1204

                         Simple Kappa Coefficient
                     --------------------------------
                     Kappa                     0.5056
                     ASE                       0.0277
                     95% Lower Conf Limit      0.4512
                     95% Upper Conf Limit      0.5599

                            Sample Size = 1144

MH Odds Ratio

In PROC FREQ, specify a three-way table with subject (pair identifier), as a stratifying variable. Then specify CMH option. - The NOPRINT option suppresses printing of the separate tables for the pairs (1144 tables in this case)

data survey;
  do subject=1 to 227;
    response = 1; question = 1; output;
    response = 1; question = 2; output;
  end;
  do subject=227+1 to 227+132;
    response = 1; question = 1; output;
    response = 0; question = 2; output;
  end;
  do subject=227+132+1 to 227+132+107;
    response = 0; question = 1; output;
    response = 1; question = 2; output;
  end; 
  do subject=227+132+107+1 to 227+132+107+678;
    response = 0; question = 1; output;
    response = 0; question = 2; output;
  end;
run;

proc freq order=data data=survey;
 table subject*question*response / cmh noprint;
run;

                            The FREQ Procedure

                Summary Statistics for question by response
                          Controlling for subject

        Cochran-Mantel-Haenszel Statistics (Based on Table Scores)
 
      Statistic    Alternative Hypothesis    DF       Value      Prob
      ---------------------------------------------------------------
          1        Nonzero Correlation        1      2.6151    0.1059
          2        Row Mean Scores Differ     1      2.6151    0.1059
          3        General Association        1      2.6151    0.1059

                   Common Odds Ratio and Relative Risks
 
         Statistic                   Method                  Value
         ---------------------------------------------------------
         Odds Ratio                  Mantel-Haenszel        1.2336
                                     Logit **               1.2584

         Relative Risk (Column 1)    Mantel-Haenszel        1.0749
                                     Logit **               1.1218

         Relative Risk (Column 2)    Mantel-Haenszel        0.9691
                                     Logit **               0.8914

                   Common Odds Ratio and Relative Risks
 
  Statistic                   Method                95% Confidence Limits
  -----------------------------------------------------------------------
  Odds Ratio                  Mantel-Haenszel        0.9560        1.5919
                              Logit **               0.9390        1.6864

  Relative Risk (Column 1)    Mantel-Haenszel        0.9848        1.1731
                              Logit **               0.9524        1.3213

  Relative Risk (Column 2)    Mantel-Haenszel        0.9330        1.0067
                              Logit **               0.7569        1.0500

     ** These logit estimators use a correction of 0.5 in every cell  
          of those tables that contain a zero. Tables with a zero 
          row or a zero column are not included in computing the 
          logit estimators.

                           Breslow-Day Test for
                      Homogeneity of the Odds Ratios
                      ------------------------------
                      Chi-Square            475.3777
                      DF                         238
                      Pr > ChiSq              <.0001

                         Total Sample Size = 2288

Diabetes MI Pairs Example

[Data] A study of acute myocardial infarction (MI) among Navajo Indians matched 144 victims of MI according to age and gender with 144 individuals free of heart disease. Subjects were then asked whether they had ever been diagnosed as having diabetes (x = 0, no; x = 1, yes).

Diabetes MI Pairs Example

		MI Cases
MI Controls	Diabetes	No Diabetes	Total
Diabetes	9	16	25
No Diabetes	37	82	119
Total	46	98	144

Conditional Logistic Regression Approach

• \(\alpha_i\) are not estimated.
• The \(\hat\beta\) is 0.8383. The odds ratio estimates is \(\exp(\hat\beta)=2.312\).
• The esitmated odds ratio is the same as the direct Mantel-Haensze odds ratio, which is \[ 37/16= 2.3125 \]

data MI_data;
  do subject=1 to 9;
    MI = 1; diabetes = 1; output;
    MI = 0; diabetes = 1; output;
  end;
  do subject=9+1 to 9+16;
    MI = 1; diabetes = 0; output;
    MI = 0; diabetes = 1; output;
  end;
  do subject=9+16+1 to 9+16+37;
    MI = 1; diabetes = 1; output;
    MI = 0; diabetes = 0; output;
  end;
  do subject=9+16+37+1 to 9+16+37+82;
    MI = 1; diabetes = 0; output;
    MI = 0; diabetes = 0; output;
  end;
run;

proc logistic descending data=MI_data;
  class diabetes (param=ref ref='0');
  strata subject;
  model MI = diabetes;
run;

                          The LOGISTIC Procedure
 
                           Conditional Analysis

                            Model Information

            Data Set                      WORK.MI_DATA        
            Response Variable             MI                  
            Number of Response Levels     2                   
            Number of Strata              144                 
            Model                         binary logit        
            Optimization Technique        Newton-Raphson ridge

                  Number of Observations Read         288
                  Number of Observations Used         288

                              Response Profile
 
                     Ordered                      Total
                       Value           MI     Frequency

                           1            1           144
                           2            0           144

                       Probability modeled is MI=1.

                         Class Level Information
 
                                              Design
                     Class        Value     Variables

                     diabetes     0                 0
                                  1                 1

                              Strata Summary
 
                             MI
               Response    ------    Number of
                Pattern    1    0       Strata    Frequency

                      1    1    1          144          288

                     Newton-Raphson Ridge Optimization

                         Without Parameter Scaling

              Convergence criterion (GCONV=1E-8) satisfied.          

                           Model Fit Statistics
 
                                   Without           With
                  Criterion     Covariates     Covariates

                  AIC              199.626        193.073
                  SC               199.626        196.736
                  -2 Log L         199.626        191.073

                  Testing Global Null Hypothesis: BETA=0
 
          Test                 Chi-Square       DF     Pr > ChiSq

          Likelihood Ratio         8.5534        1         0.0034
          Score                    8.3208        1         0.0039
          Wald                     7.8501        1         0.0051

                        Type 3 Analysis of Effects
 
                                         Wald
               Effect        DF    Chi-Square    Pr > ChiSq

               diabetes       1        7.8501        0.0051

           Analysis of Conditional Maximum Likelihood Estimates
 
                                    Standard          Wald
   Parameter      DF    Estimate       Error    Chi-Square    Pr > ChiSq

   diabetes  1     1      0.8383      0.2992        7.8501        0.0051

                           Odds Ratio Estimates
                                     
                                  Point          95% Wald
            Effect             Estimate      Confidence Limits

            diabetes 1 vs 0       2.312       1.286       4.157

An Unconditional Logistic Regression Approach to 1:1 Matching

data new_MI;
  do subject=1 to 9;
    MI = 1; diabetes = 0; output;
  end;
  do subject=9+1 to 9+16;
    MI = 1; diabetes = -1; output;
  end;
  do subject=9+16+1 to 9+16+37;
    MI = 1; diabetes = 1; output;
  end;
  do subject=9+16+37+1 to 9+16+37+82;
    MI = 1; diabetes = 0; output;
  end;
run;

proc logistic descending data=new_MI;
  model MI = diabetes / noint;
run;

                          The LOGISTIC Procedure

                            Model Information

              Data Set                      WORK.NEW_MI     
              Response Variable             MI              
              Number of Response Levels     1               
              Model                         binary logit    
              Optimization Technique        Fisher's scoring

                  Number of Observations Read         144
                  Number of Observations Used         144

                              Response Profile
 
                     Ordered                      Total
                       Value           MI     Frequency

                           1            1           144

                       Probability modeled is MI=1.

                         Model Convergence Status

              Convergence criterion (GCONV=1E-8) satisfied.          

                           Model Fit Statistics
 
                                   Without           With
                  Criterion     Covariates     Covariates

                  AIC              199.626        193.073
                  SC               199.626        196.043
                  -2 Log L         199.626        191.073

                  Testing Global Null Hypothesis: BETA=0
 
          Test                 Chi-Square       DF     Pr > ChiSq

          Likelihood Ratio         8.5534        1         0.0034
          Score                    8.3208        1         0.0039
          Wald                     7.8501        1         0.0051

                 Analysis of Maximum Likelihood Estimates
 
                                   Standard          Wald
    Parameter    DF    Estimate       Error    Chi-Square    Pr > ChiSq

    diabetes      1      0.8383      0.2992        7.8501        0.0051

                           Odds Ratio Estimates
                                     
                              Point          95% Wald
               Effect      Estimate      Confidence Limits

               diabetes       2.312       1.286       4.157

NOTE: Since there is only one response level, measures of association 
      between the observed and predicted values were not calculated.

Unconditional Logistic Regression results in biased estimates.

• \(\alpha_i\) are estimated. Note that \(\alpha_i\)s are nuisance parameters, meaning the parameters that we are not interested. Therefore, you will see a long list of output.
• The \(\hat\beta\) is 1.6767. The odds ratio estimates is \(\exp(\hat\beta)=5.348\).
• The esitmated odds ratio is square of antel-Haensze odds ratio, \((37/16)^2 = 5.348\)

data MI_data;
  do subject=1 to 9;
    MI = 1; diabetes = 1; output;
    MI = 0; diabetes = 1; output;
  end;
  do subject=9+1 to 9+16;
    MI = 1; diabetes = 0; output;
    MI = 0; diabetes = 1; output;
  end;
  do subject=9+16+1 to 9+16+37;
    MI = 1; diabetes = 1; output;
    MI = 0; diabetes = 0; output;
  end;
  do subject=9+16+37+1 to 9+16+37+82;
    MI = 1; diabetes = 0; output;
    MI = 0; diabetes = 0; output;
  end;
run;

proc logistic descending data=MI_data;
    class diabetes (ref='0') subject (ref='144') / param=ref;
    model MI = subject diabetes;
run;

                          The LOGISTIC Procedure

                            Model Information

              Data Set                      WORK.MI_DATA    
              Response Variable             MI              
              Number of Response Levels     2               
              Model                         binary logit    
              Optimization Technique        Fisher's scoring

                  Number of Observations Read         288
                  Number of Observations Used         288

                              Response Profile
 
                     Ordered                      Total
                       Value           MI     Frequency

                           1            1           144
                           2            0           144

                       Probability modeled is MI=1.

                          Class Level Information
 
Class     Value                       Design Variables

diabetes  0       0                                                        
          1       1                                                        

subject   1       1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          2       0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
          3       0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
          4       0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
          5       0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
          6       0   0   0   0   0   1   0   0   0   0   0   0   0   0   0
          7       0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
          8       0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
          9       0   0   0   0   0   0   0   0   1   0   0   0   0   0   0
          10      0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
          11      0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
          12      0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
          13      0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
          14      0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
          15      0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
          16      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          17      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          18      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          19      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          20      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          21      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          22      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          23      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          24      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          25      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          26      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          27      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          28      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          29      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          30      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          31      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          32      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          33      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          34      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          35      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          36      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          37      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          38      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          39      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          40      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          41      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          42      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          43      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          44      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          45      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          46      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          47      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          48      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          49      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          50      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          51      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          52      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          53      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          54      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          55      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          56      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          57      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          58      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          59      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          60      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          61      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          62      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          63      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          64      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          65      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          66      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          67      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          68      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          69      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          70      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          71      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          72      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          73      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          74      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          75      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          76      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          77      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          78      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          79      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          80      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          81      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          82      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          83      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          84      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          85      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          86      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          87      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          88      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          89      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          90      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          91      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          92      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          93      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          94      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          95      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          96      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          97      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          98      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0

                         Class Level Information
 
                             Design Variables

                                                                          
                                                                          

 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
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                         Class Level Information
 
                             Design Variables

                                                                          
                                                                          

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                         Class Level Information
 
                             Design Variables

                                                                          
                                                                          

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                         Class Level Information
 
                             Design Variables

                                                                          
                                                                          

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                         Class Level Information
 
                             Design Variables

                                                                          
                                                                          

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                         Class Level Information
 
                             Design Variables

                                                                          
                                                                          

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 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0

                          Class Level Information
 
                              Design Variables

                                                                       
                                                                       

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     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0

                          Class Level Information
 
Class     Value                       Design Variables

          99      0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          100     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          101     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          102     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          103     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          104     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          105     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          106     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          107     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          108     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          109     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          110     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          111     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          112     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          113     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          114     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          115     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          116     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          117     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          118     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          119     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          120     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          121     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          122     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          123     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          124     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          125     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          126     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          127     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          128     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          129     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          130     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          131     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          132     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          133     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          134     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          135     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          136     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          137     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          138     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          139     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          140     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          141     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          142     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          143     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
          144     0   0   0   0   0   0   0   0   0   0   0   0   0   0   0

                         Class Level Information
 
                             Design Variables

 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0

                         Class Level Information
 
                             Design Variables

 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0

                         Class Level Information
 
                             Design Variables

 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0

                         Class Level Information
 
                             Design Variables

 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
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                         Class Level Information
 
                             Design Variables

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                         Class Level Information
 
                             Design Variables

 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
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                          Class Level Information
 
                              Design Variables

     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
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     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
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     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    0
     1    0    0    0    0    0    0    0    0    0    0    0    0    0
     0    1    0    0    0    0    0    0    0    0    0    0    0    0
     0    0    1    0    0    0    0    0    0    0    0    0    0    0
     0    0    0    1    0    0    0    0    0    0    0    0    0    0
     0    0    0    0    1    0    0    0    0    0    0    0    0    0
     0    0    0    0    0    1    0    0    0    0    0    0    0    0
     0    0    0    0    0    0    1    0    0    0    0    0    0    0
     0    0    0    0    0    0    0    1    0    0    0    0    0    0
     0    0    0    0    0    0    0    0    1    0    0    0    0    0
     0    0    0    0    0    0    0    0    0    1    0    0    0    0
     0    0    0    0    0    0    0    0    0    0    1    0    0    0
     0    0    0    0    0    0    0    0    0    0    0    1    0    0
     0    0    0    0    0    0    0    0    0    0    0    0    1    0
     0    0    0    0    0    0    0    0    0    0    0    0    0    1
     0    0    0    0    0    0    0    0    0    0    0    0    0    0

                         Model Convergence Status

              Convergence criterion (GCONV=1E-8) satisfied.          

                           Model Fit Statistics
 
                                               Intercept
                                Intercept            and
                  Criterion          Only     Covariates

                  AIC             401.253        672.146
                  SC              404.916       1203.275
                  -2 Log L        399.253        382.146

                  Testing Global Null Hypothesis: BETA=0
 
          Test                 Chi-Square       DF     Pr > ChiSq

          Likelihood Ratio        17.1068      144         1.0000
          Score                   16.6415      144         1.0000
          Wald                    15.7002      144         1.0000

                        Type 3 Analysis of Effects
 
                                         Wald
               Effect        DF    Chi-Square    Pr > ChiSq

               subject      143        8.4237        1.0000
               diabetes       1       15.7002        <.0001

                 Analysis of Maximum Likelihood Estimates
 
                                     Standard          Wald
  Parameter        DF    Estimate       Error    Chi-Square    Pr > ChiSq

  Intercept         1    -495E-20      1.4142        0.0000        1.0000
  subject   1       1     -1.6767      2.0443        0.6727        0.4121
  subject   2       1     -1.6767      2.0443        0.6727        0.4121
  subject   3       1     -1.6767      2.0443        0.6727        0.4121
  subject   4       1     -1.6767      2.0443        0.6727        0.4121
  subject   5       1     -1.6767      2.0443        0.6727        0.4121
  subject   6       1     -1.6767      2.0443        0.6727        0.4121
  subject   7       1     -1.6767      2.0443        0.6727        0.4121
  subject   8       1     -1.6767      2.0443        0.6727        0.4121
  subject   9       1     -1.6767      2.0443        0.6727        0.4121
  subject   10      1     -0.8383      2.1017        0.1591        0.6900
  subject   11      1     -0.8383      2.1017        0.1591        0.6900
  subject   12      1     -0.8383      2.1017        0.1591        0.6900
  subject   13      1     -0.8383      2.1017        0.1591        0.6900
  subject   14      1     -0.8383      2.1017        0.1591        0.6900
  subject   15      1     -0.8383      2.1017        0.1591        0.6900
  subject   16      1     -0.8383      2.1017        0.1591        0.6900
  subject   17      1     -0.8383      2.1017        0.1591        0.6900
  subject   18      1     -0.8383      2.1017        0.1591        0.6900
  subject   19      1     -0.8383      2.1017        0.1591        0.6900
  subject   20      1     -0.8383      2.1017        0.1591        0.6900
  subject   21      1     -0.8383      2.1017        0.1591        0.6900
  subject   22      1     -0.8383      2.1017        0.1591        0.6900
  subject   23      1     -0.8383      2.1017        0.1591        0.6900
  subject   24      1     -0.8383      2.1017        0.1591        0.6900
  subject   25      1     -0.8383      2.1017        0.1591        0.6900
  subject   26      1     -0.8383      2.1017        0.1591        0.6900
  subject   27      1     -0.8383      2.1017        0.1591        0.6900
  subject   28      1     -0.8383      2.1017        0.1591        0.6900
  subject   29      1     -0.8383      2.1017        0.1591        0.6900
  subject   30      1     -0.8383      2.1017        0.1591        0.6900
  subject   31      1     -0.8383      2.1017        0.1591        0.6900
  subject   32      1     -0.8383      2.1017        0.1591        0.6900
  subject   33      1     -0.8383      2.1017        0.1591        0.6900
  subject   34      1     -0.8383      2.1017        0.1591        0.6900
  subject   35      1     -0.8383      2.1017        0.1591        0.6900
  subject   36      1     -0.8383      2.1017        0.1591        0.6900
  subject   37      1     -0.8383      2.1017        0.1591        0.6900
  subject   38      1     -0.8383      2.1017        0.1591        0.6900
  subject   39      1     -0.8383      2.1017        0.1591        0.6900
  subject   40      1     -0.8383      2.1017        0.1591        0.6900
  subject   41      1     -0.8383      2.1017        0.1591        0.6900
  subject   42      1     -0.8383      2.1017        0.1591        0.6900
  subject   43      1     -0.8383      2.1017        0.1591        0.6900
  subject   44      1     -0.8383      2.1017        0.1591        0.6900
  subject   45      1     -0.8383      2.1017        0.1591        0.6900
  subject   46      1     -0.8383      2.1017        0.1591        0.6900
  subject   47      1     -0.8383      2.1017        0.1591        0.6900
  subject   48      1     -0.8383      2.1017        0.1591        0.6900
  subject   49      1     -0.8383      2.1017        0.1591        0.6900
  subject   50      1     -0.8383      2.1017        0.1591        0.6900
  subject   51      1     -0.8383      2.1017        0.1591        0.6900
  subject   52      1     -0.8383      2.1017        0.1591        0.6900
  subject   53      1     -0.8383      2.1017        0.1591        0.6900
  subject   54      1     -0.8383      2.1017        0.1591        0.6900
  subject   55      1     -0.8383      2.1017        0.1591        0.6900
  subject   56      1     -0.8383      2.1017        0.1591        0.6900
  subject   57      1     -0.8383      2.1017        0.1591        0.6900
  subject   58      1     -0.8383      2.1017        0.1591        0.6900
  subject   59      1     -0.8383      2.1017        0.1591        0.6900
  subject   60      1     -0.8383      2.1017        0.1591        0.6900
  subject   61      1     -0.8383      2.1017        0.1591        0.6900
  subject   62      1     -0.8383      2.1017        0.1591        0.6900
  subject   63      1    4.95E-18      2.0000        0.0000        1.0000
  subject   64      1    4.95E-18      2.0000        0.0000        1.0000
  subject   65      1    4.95E-18      2.0000        0.0000        1.0000
  subject   66      1    4.95E-18      2.0000        0.0000        1.0000
  subject   67      1    4.95E-18      2.0000        0.0000        1.0000
  subject   68      1    4.95E-18      2.0000        0.0000        1.0000
  subject   69      1    4.95E-18      2.0000        0.0000        1.0000
  subject   70      1    4.95E-18      2.0000        0.0000        1.0000
  subject   71      1    4.95E-18      2.0000        0.0000        1.0000
  subject   72      1    4.95E-18      2.0000        0.0000        1.0000
  subject   73      1    4.95E-18      2.0000        0.0000        1.0000
  subject   74      1    4.95E-18      2.0000        0.0000        1.0000
  subject   75      1    4.95E-18      2.0000        0.0000        1.0000
  subject   76      1    4.95E-18      2.0000        0.0000        1.0000
  subject   77      1    4.95E-18      2.0000        0.0000        1.0000
  subject   78      1    4.95E-18      2.0000        0.0000        1.0000
  subject   79      1    4.95E-18      2.0000        0.0000        1.0000
  subject   80      1    4.95E-18      2.0000        0.0000        1.0000
  subject   81      1    4.95E-18      2.0000        0.0000        1.0000
  subject   82      1    4.95E-18      2.0000        0.0000        1.0000
  subject   83      1    4.95E-18      2.0000        0.0000        1.0000
  subject   84      1    4.95E-18      2.0000        0.0000        1.0000
  subject   85      1    4.95E-18      2.0000        0.0000        1.0000
  subject   86      1    4.95E-18      2.0000        0.0000        1.0000
  subject   87      1    4.95E-18      2.0000        0.0000        1.0000
  subject   88      1    4.95E-18      2.0000        0.0000        1.0000
  subject   89      1    4.95E-18      2.0000        0.0000        1.0000
  subject   90      1    4.95E-18      2.0000        0.0000        1.0000
  subject   91      1    4.95E-18      2.0000        0.0000        1.0000
  subject   92      1    4.95E-18      2.0000        0.0000        1.0000
  subject   93      1    4.95E-18      2.0000        0.0000        1.0000
  subject   94      1    4.95E-18      2.0000        0.0000        1.0000
  subject   95      1    4.95E-18      2.0000        0.0000        1.0000
  subject   96      1    4.95E-18      2.0000        0.0000        1.0000
  subject   97      1    4.95E-18      2.0000        0.0000        1.0000
  subject   98      1    4.95E-18      2.0000        0.0000        1.0000
  subject   99      1    4.95E-18      2.0000        0.0000        1.0000
  subject   100     1    4.95E-18      2.0000        0.0000        1.0000
  subject   101     1    4.95E-18      2.0000        0.0000        1.0000
  subject   102     1    4.95E-18      2.0000        0.0000        1.0000
  subject   103     1    4.95E-18      2.0000        0.0000        1.0000
  subject   104     1    4.95E-18      2.0000        0.0000        1.0000
  subject   105     1    4.95E-18      2.0000        0.0000        1.0000
  subject   106     1    4.95E-18      2.0000        0.0000        1.0000
  subject   107     1    4.95E-18      2.0000        0.0000        1.0000
  subject   108     1    4.95E-18      2.0000        0.0000        1.0000
  subject   109     1    4.95E-18      2.0000        0.0000        1.0000
  subject   110     1    4.95E-18      2.0000        0.0000        1.0000
  subject   111     1    4.95E-18      2.0000        0.0000        1.0000
  subject   112     1    4.95E-18      2.0000        0.0000        1.0000
  subject   113     1    4.95E-18      2.0000        0.0000        1.0000
  subject   114     1    4.95E-18      2.0000        0.0000        1.0000
  subject   115     1    4.95E-18      2.0000        0.0000        1.0000
  subject   116     1    4.95E-18      2.0000        0.0000        1.0000
  subject   117     1    4.95E-18      2.0000        0.0000        1.0000
  subject   118     1    4.95E-18      2.0000        0.0000        1.0000
  subject   119     1    4.95E-18      2.0000        0.0000        1.0000
  subject   120     1    4.95E-18      2.0000        0.0000        1.0000
  subject   121     1    4.95E-18      2.0000        0.0000        1.0000
  subject   122     1    4.95E-18      2.0000        0.0000        1.0000
  subject   123     1    4.95E-18      2.0000        0.0000        1.0000
  subject   124     1    4.95E-18      2.0000        0.0000        1.0000
  subject   125     1    4.95E-18      2.0000        0.0000        1.0000
  subject   126     1    4.95E-18      2.0000        0.0000        1.0000
  subject   127     1    4.95E-18      2.0000        0.0000        1.0000
  subject   128     1    4.95E-18      2.0000        0.0000        1.0000
  subject   129     1    4.95E-18      2.0000        0.0000        1.0000
  subject   130     1    4.95E-18      2.0000        0.0000        1.0000
  subject   131     1    4.95E-18      2.0000        0.0000        1.0000
  subject   132     1    4.95E-18      2.0000        0.0000        1.0000
  subject   133     1    4.95E-18      2.0000        0.0000        1.0000
  subject   134     1    4.95E-18      2.0000        0.0000        1.0000
  subject   135     1    4.95E-18      2.0000        0.0000        1.0000
  subject   136     1    4.95E-18      2.0000        0.0000        1.0000
  subject   137     1    4.95E-18      2.0000        0.0000        1.0000
  subject   138     1    4.95E-18      2.0000        0.0000        1.0000
  subject   139     1    4.95E-18      2.0000        0.0000        1.0000
  subject   140     1    4.95E-18      2.0000        0.0000        1.0000
  subject   141     1    4.95E-18      2.0000        0.0000        1.0000
  subject   142     1    4.95E-18      2.0000        0.0000        1.0000
  subject   143     1    4.95E-18      2.0000        0.0000        1.0000
  diabetes  1       1      1.6767      0.4231       15.7002        <.0001

                           Odds Ratio Estimates
                                     
                                    Point          95% Wald
          Effect                 Estimate      Confidence Limits

          subject  1   vs 144       0.187       0.003      10.278
          subject  2   vs 144       0.187       0.003      10.278
          subject  3   vs 144       0.187       0.003      10.278
          subject  4   vs 144       0.187       0.003      10.278
          subject  5   vs 144       0.187       0.003      10.278
          subject  6   vs 144       0.187       0.003      10.278
          subject  7   vs 144       0.187       0.003      10.278
          subject  8   vs 144       0.187       0.003      10.278
          subject  9   vs 144       0.187       0.003      10.278
          subject  10  vs 144       0.432       0.007      26.602
          subject  11  vs 144       0.432       0.007      26.602
          subject  12  vs 144       0.432       0.007      26.602
          subject  13  vs 144       0.432       0.007      26.602
          subject  14  vs 144       0.432       0.007      26.602
          subject  15  vs 144       0.432       0.007      26.602
          subject  16  vs 144       0.432       0.007      26.602
          subject  17  vs 144       0.432       0.007      26.602
          subject  18  vs 144       0.432       0.007      26.602
          subject  19  vs 144       0.432       0.007      26.602
          subject  20  vs 144       0.432       0.007      26.602
          subject  21  vs 144       0.432       0.007      26.602
          subject  22  vs 144       0.432       0.007      26.602
          subject  23  vs 144       0.432       0.007      26.602
          subject  24  vs 144       0.432       0.007      26.602
          subject  25  vs 144       0.432       0.007      26.602
          subject  26  vs 144       0.432       0.007      26.602
          subject  27  vs 144       0.432       0.007      26.602
          subject  28  vs 144       0.432       0.007      26.602
          subject  29  vs 144       0.432       0.007      26.602
          subject  30  vs 144       0.432       0.007      26.602
          subject  31  vs 144       0.432       0.007      26.602
          subject  32  vs 144       0.432       0.007      26.602
          subject  33  vs 144       0.432       0.007      26.602
          subject  34  vs 144       0.432       0.007      26.602
          subject  35  vs 144       0.432       0.007      26.602
          subject  36  vs 144       0.432       0.007      26.602
          subject  37  vs 144       0.432       0.007      26.602
          subject  38  vs 144       0.432       0.007      26.602
          subject  39  vs 144       0.432       0.007      26.602
          subject  40  vs 144       0.432       0.007      26.602
          subject  41  vs 144       0.432       0.007      26.602
          subject  42  vs 144       0.432       0.007      26.602
          subject  43  vs 144       0.432       0.007      26.602
          subject  44  vs 144       0.432       0.007      26.602
          subject  45  vs 144       0.432       0.007      26.602
          subject  46  vs 144       0.432       0.007      26.602
          subject  47  vs 144       0.432       0.007      26.602
          subject  48  vs 144       0.432       0.007      26.602
          subject  49  vs 144       0.432       0.007      26.602
          subject  50  vs 144       0.432       0.007      26.602
          subject  51  vs 144       0.432       0.007      26.602
          subject  52  vs 144       0.432       0.007      26.602
          subject  53  vs 144       0.432       0.007      26.602
          subject  54  vs 144       0.432       0.007      26.602
          subject  55  vs 144       0.432       0.007      26.602
          subject  56  vs 144       0.432       0.007      26.602
          subject  57  vs 144       0.432       0.007      26.602
          subject  58  vs 144       0.432       0.007      26.602
          subject  59  vs 144       0.432       0.007      26.602
          subject  60  vs 144       0.432       0.007      26.602
          subject  61  vs 144       0.432       0.007      26.602
          subject  62  vs 144       0.432       0.007      26.602
          subject  63  vs 144       1.000       0.020      50.397
          subject  64  vs 144       1.000       0.020      50.397
          subject  65  vs 144       1.000       0.020      50.397
          subject  66  vs 144       1.000       0.020      50.397
          subject  67  vs 144       1.000       0.020      50.397
          subject  68  vs 144       1.000       0.020      50.397
          subject  69  vs 144       1.000       0.020      50.397
          subject  70  vs 144       1.000       0.020      50.397
          subject  71  vs 144       1.000       0.020      50.397
          subject  72  vs 144       1.000       0.020      50.397
          subject  73  vs 144       1.000       0.020      50.397
          subject  74  vs 144       1.000       0.020      50.397
          subject  75  vs 144       1.000       0.020      50.397
          subject  76  vs 144       1.000       0.020      50.397
          subject  77  vs 144       1.000       0.020      50.397
          subject  78  vs 144       1.000       0.020      50.397
          subject  79  vs 144       1.000       0.020      50.397
          subject  80  vs 144       1.000       0.020      50.397
          subject  81  vs 144       1.000       0.020      50.397
          subject  82  vs 144       1.000       0.020      50.397
          subject  83  vs 144       1.000       0.020      50.397
          subject  84  vs 144       1.000       0.020      50.397
          subject  85  vs 144       1.000       0.020      50.397
          subject  86  vs 144       1.000       0.020      50.397
          subject  87  vs 144       1.000       0.020      50.397
          subject  88  vs 144       1.000       0.020      50.397
          subject  89  vs 144       1.000       0.020      50.397
          subject  90  vs 144       1.000       0.020      50.397
          subject  91  vs 144       1.000       0.020      50.397
          subject  92  vs 144       1.000       0.020      50.397
          subject  93  vs 144       1.000       0.020      50.397
          subject  94  vs 144       1.000       0.020      50.397
          subject  95  vs 144       1.000       0.020      50.397
          subject  96  vs 144       1.000       0.020      50.397
          subject  97  vs 144       1.000       0.020      50.397
          subject  98  vs 144       1.000       0.020      50.397
          subject  99  vs 144       1.000       0.020      50.397
          subject  100 vs 144       1.000       0.020      50.397
          subject  101 vs 144       1.000       0.020      50.397
          subject  102 vs 144       1.000       0.020      50.397
          subject  103 vs 144       1.000       0.020      50.397
          subject  104 vs 144       1.000       0.020      50.397
          subject  105 vs 144       1.000       0.020      50.397
          subject  106 vs 144       1.000       0.020      50.397
          subject  107 vs 144       1.000       0.020      50.397
          subject  108 vs 144       1.000       0.020      50.397
          subject  109 vs 144       1.000       0.020      50.397
          subject  110 vs 144       1.000       0.020      50.397
          subject  111 vs 144       1.000       0.020      50.397
          subject  112 vs 144       1.000       0.020      50.397
          subject  113 vs 144       1.000       0.020      50.397
          subject  114 vs 144       1.000       0.020      50.397
          subject  115 vs 144       1.000       0.020      50.397
          subject  116 vs 144       1.000       0.020      50.397
          subject  117 vs 144       1.000       0.020      50.397
          subject  118 vs 144       1.000       0.020      50.397
          subject  119 vs 144       1.000       0.020      50.397
          subject  120 vs 144       1.000       0.020      50.397
          subject  121 vs 144       1.000       0.020      50.397
          subject  122 vs 144       1.000       0.020      50.397
          subject  123 vs 144       1.000       0.020      50.397
          subject  124 vs 144       1.000       0.020      50.397
          subject  125 vs 144       1.000       0.020      50.397
          subject  126 vs 144       1.000       0.020      50.397
          subject  127 vs 144       1.000       0.020      50.397
          subject  128 vs 144       1.000       0.020      50.397
          subject  129 vs 144       1.000       0.020      50.397
          subject  130 vs 144       1.000       0.020      50.397
          subject  131 vs 144       1.000       0.020      50.397
          subject  132 vs 144       1.000       0.020      50.397
          subject  133 vs 144       1.000       0.020      50.397
          subject  134 vs 144       1.000       0.020      50.397
          subject  135 vs 144       1.000       0.020      50.397
          subject  136 vs 144       1.000       0.020      50.397
          subject  137 vs 144       1.000       0.020      50.397
          subject  138 vs 144       1.000       0.020      50.397
          subject  139 vs 144       1.000       0.020      50.397
          subject  140 vs 144       1.000       0.020      50.397
          subject  141 vs 144       1.000       0.020      50.397
          subject  142 vs 144       1.000       0.020      50.397
          subject  143 vs 144       1.000       0.020      50.397
          diabetes 1 vs 0           5.348       2.333      12.256

       Association of Predicted Probabilities and Observed Responses

             Percent Concordant     39.1    Somers' D    0.238
             Percent Discordant     15.3    Gamma        0.438
             Percent Tied           45.6    Tau-a        0.119
             Pairs                 20736    c            0.619