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The PROBIT Procedure

Example 54.3: Logistic Regression

In this example, a series of people are questioned as to whether or not they would subscribe to a new newspaper. For each person, the variables sex (Female, Male), age, and subs (1=yes,0=no) are recorded. The PROBIT procedure is used to fit a logistic regression model to the probability of a positive response (subscribing) as a function of the variables sex and age. Specifically, the probability of subscribing is modeled as

p = Pr( subs = 1) = F ( b0 + b1 × sex + b2 × age )
where F is the cumulative logistic distribution function.

By default, the PROBIT procedure models the probability of the lower response level for binary data. One way to model Pr( subs = 1) is to format the response variable so that the formatted value corresponding to subs = 1 is the lower level. The following statements format the values of subs as 1 = 'accept' and 0 = 'reject', so that PROBIT models Pr(accept) = Pr( subs = 1).

The following statements produce Output 54.3.1:

   data news;
      input sex $ age subs;
      datalines;
   Female     35    0
   Male       44    0
   Male       45    1
   Female     47    1
   Female     51    0
   Female     47    0
   Male       54    1
   Male       47    1
   Female     35    0
   Female     34    0
   Female     48    0
   Female     56    1
   Male       46    1
   Female     59    1
   Female     46    1
   Male       59    1
   Male       38    1
   Female     39    0
   Male       49    1
   Male       42    1
   Male       50    1
   Female     45    0
   Female     47    0
   Female     30    1
   Female     39    0
   Female     51    0
   Female     45    0
   Female     43    1
   Male       39    1
   Male       31    0
   Female     39    0
   Male       34    0
   Female     52    1
   Female     46    0
   Male       58    1
   Female     50    1
   Female     32    0
   Female     52    1
   Female     35    0
   Female     51    0
   ;

   proc format;
      value subscrib 1 = 'accept' 0 = 'reject';
   run;

   proc probit;
      class subs sex;
      model subs=sex age / d=logistic itprint;
      format subs subscrib.;
      title 'Logistic Regression of Subscription Status';
   run;

Output 54.3.1: Logistic Regression: PROC PROBIT

Logistic Regression of Subscription Status

Probit Procedure

Class Level Information
Name Levels Values
subs 2 accept reject
sex 2 Female Male


Logistic Regression of Subscription Status

Probit Procedure

Iteration History for Parameter Estimates
Iter Ridge Loglikelihood Intercept age sex.1
0 0 -27.725887 0 0 0
1 0 -20.142659 -3.634567629 0.1051634384 -1.648455751
2 0 -19.52245 -5.254865196 0.1506493473 -2.234724956
3 0 -19.490439 -5.728485385 0.1639621828 -2.409827238
4 0 -19.490303 -5.76187293 0.1649007124 -2.422349862
5 0 -19.490303 -5.7620267 0.1649050312 -2.422407743

Model Information
Data Set WORK.NEWS
Dependent Variable subs
Number of Observations 40
Name of Distribution LOGISTIC
Log Likelihood -19.49030281

Weighted Frequency
Counts for the Ordered
Response Categories
Level Count
accept 20
reject 20


Logistic Regression of Subscription Status

Probit Procedure

Last Evaluation of the Negative of the Gradient
Intercept sex.1 age
-5.95379E-12 8.76834E-10 -1.636692E-8

Last Evaluation of the Negative of the Hessian
  Intercept sex.1 age
Intercept 6.4597397447 4.6042218284 292.04051848
sex.1 4.6042218284 4.6042218284 216.20829515
age 292.04051848 216.20829515 13487.329973

Algorithm converged.


Logistic Regression of Subscription Status

Probit Procedure

Analysis of Parameter Estimates
Variable DF Estimate Standard Error Chi-Square Pr > ChiSq Label
Intercept 1 -5.76203 2.76345 4.3476 0.0371 Intercept
sex 1     6.4220 0.0113  
  1 -2.42241 0.95590 6.4220 0.0113 Female
  0 0 0 . . Male
age 1 0.16491 0.06519 6.3992 0.0114  


From Output 54.3.1, there appears to be an effect due to both the variables sex and age. The positive coefficient for age indicates that older people are more likely to subscribe than younger people. The negative coefficient for sex indicates that females are less likely to subscribe than males.

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