The MEANS Procedure
Analysis Variable : GPA
N Mean Std Dev Minimum Maximum
400 2.998925 0.3979409 1.9 4
               
The FREQ Procedure
Likelihood of Applying (1 = likely)
Lapply Frequency Percent Cumulative Cumulative
Frequency Percent
0 220 55 220 55
1 180 45 400 100
APPLY Frequency Percent Cumulative Cumulative
Frequency Percent
0 220 55 220 55
1 140 35 360 90
2 40 10 400 100
Parent Has Graduate Degree
parentGD Frequency Percent Cumulative Cumulative
Frequency Percent
0 337 84.25 337 84.25
1 63 15.75 400 100
Student Attends Public University
PUBLIC Frequency Percent Cumulative Cumulative
Frequency Percent
0 343 85.75 343 85.75
1 57 14.25 400 100
               
The GENMOD Procedure
Model Information
Data Set WORK.GRADPLAN  
Distribution Binomial  
Link Function Logit  
Dependent Variable Lapply Likelihood of Applying (1 = likely)
Number of Observations Read 400
Number of Observations Used 400
Number of Events 220
Number of Trials 400
Response Profile
Ordered Lapply Total
Value Frequency
1 0 220
2 1 180
PROC GENMOD is modeling the probability that Lapply='0'. One way to change this to model the probability that Lapply='1' is to specify the DESCENDING option in the PROC statement.
Parameter Information
Parameter Effect
Prm1 Intercept
Iteration History For Parameter
Estimates
Iter Ridge LogLikelihood Prm1
0 0 -275.27348 0.2197225
1 0 -275.25553 0.2006514
2 0 -275.25553 0.2006707
Criteria For Assessing Goodness Of Fit
Criterion DF Value Value/DF
Log Likelihood   -275.2555  
Full Log Likelihood   -275.2555  
AIC (smaller is better)   552.5111  
AICC (smaller is better)   552.5211  
BIC (smaller is better)   556.5025  
Last Evaluation Of The
Negative Of The Gradient
and Hessian
  Prm1
Gradient -1.84E-09
Prm1 99
Algorithm converged.
Analysis Of Maximum Likelihood Parameter Estimates
Parameter DF Estimate Standard Error Wald 95% Confidence Limits Wald Chi-Square Pr > ChiSq
Intercept 1 0.2007 0.1005 0.0037 0.3977 3.99 0.0459
Scale 0 1 0 1 1    
The scale parameter was held fixed.
               
The GENMOD Procedure
Model Information
Data Set WORK.GRADPLAN  
Distribution Binomial  
Link Function Logit  
Dependent Variable Lapply Likelihood of Applying (1 = likely)
Number of Observations Read 400
Number of Observations Used 400
Number of Events 180
Number of Trials 400
Response Profile
Ordered Lapply Total
Value Frequency
1 1 180
2 0 220
PROC GENMOD is modeling the probability that Lapply='1'.
Parameter Information
Parameter Effect
Prm1 Intercept
Iteration History For Parameter
Estimates
Iter Ridge LogLikelihood Prm1
0 0 -275.27348 -0.219722
1 0 -275.25553 -0.200651
2 0 -275.25553 -0.200671
Criteria For Assessing Goodness Of Fit
Criterion DF Value Value/DF
Log Likelihood   -275.2555  
Full Log Likelihood   -275.2555  
AIC (smaller is better)   552.5111  
AICC (smaller is better)   552.5211  
BIC (smaller is better)   556.5025  
Last Evaluation Of The
Negative Of The Gradient
and Hessian
  Prm1
Gradient 1.84E-09
Prm1 99
Algorithm converged.
Analysis Of Maximum Likelihood Parameter Estimates
Parameter DF Estimate Standard Error Wald 95% Confidence Limits Wald Chi-Square Pr > ChiSq
Intercept 1 -0.2007 0.1005 -0.3977 -0.0037 3.99 0.0459
Scale 0 1 0 1 1    
The scale parameter was held fixed.
               
The GENMOD Procedure
Model Information
Data Set WORK.GRADPLAN  
Distribution Binomial  
Link Function Logit  
Dependent Variable Lapply Likelihood of Applying (1 = likely)
Number of Observations Read 400
Number of Observations Used 400
Number of Events 220
Number of Trials 400
Response Profile
Ordered Lapply Total
Value Frequency
1 0 220
2 1 180
PROC GENMOD is modeling the probability that Lapply='0'. One way to change this to model the probability that Lapply='1' is to specify the DESCENDING option in the PROC statement.
Parameter Information
Parameter Effect
Prm1 Intercept
Prm2 parentGD
Prm3 GPA3
Prm4 PUBLIC
Iteration History For Parameter Estimates
Iter Ridge LogLikelihood Prm1 Prm2 Prm3 Prm4
0 0 -265.00194 0.3650003 -1.113614 -0.567908 0.2070592
1 0 -264.9624 0.3381472 -1.059362 -0.548005 0.2004713
2 0 -264.9624 0.3382338 -1.059612 -0.548246 0.2005571
3 0 -264.9624 0.3382338 -1.059612 -0.548246 0.2005571
Criteria For Assessing Goodness Of Fit
Criterion DF Value Value/DF
Log Likelihood   -264.9624  
Full Log Likelihood   -264.9624  
AIC (smaller is better)   537.9248  
AICC (smaller is better)   538.0261  
BIC (smaller is better)   553.8907  
Last Evaluation Of The Negative Of The Gradient and Hessian
  Prm1 Prm2 Prm3 Prm4
Gradient -9.77E-08 1.17E-07 1.56E-07 -1.92E-08
Prm1 93.971936 13.525946 0.4546087 13.199123
Prm2 13.525946 13.525946 1.9430187 2.828192
Prm3 0.4546087 1.9430187 14.4641 2.9910389
Prm4 13.199123 2.828192 2.9910389 13.199123
Algorithm converged. 0.583753215
Analysis Of Maximum Likelihood Parameter Estimates
Parameter DF Estimate Standard Error Wald 95% Confidence Limits Wald Chi-Square Pr > ChiSq
Intercept 1 0.3382 0.1187 0.1056 0.5709 8.12 0.0044
parentGD 1 -1.0596 0.2974 -1.6425 -0.4767 12.7 0.0004
GPA3 1 -0.5482 0.2724 -1.0822 -0.0143 4.05 0.0442
PUBLIC 1 0.2006 0.3053 -0.3979 0.799 0.43 0.5113
Scale 0 1 0 1 1    
The scale parameter was held fixed.
0.583753215 1.40242096 2.885216672 0.34659442 1.40242096
0.327084768 0.48607128 0.34659442
GPA3  Logit Odds of 0 Prob = 0
1 -0.210 0.811 0.448
0 0.338 1.402 0.584
-1 0.886 2.426 0.708
-2 1.435 4.198 0.808
Public Logit Odds of 0 Prob = 0
1 0.539 1.714 0.632
0 0.338 1.402 0.584