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* * * * * * * * * * * * P R O B I T A N A L Y S I S * * * * * * * * * * * *
DATA Information
12473 unweighted cases accepted.
0 cases rejected because of missing data.
18708 cases are in the control group.
MODEL Information
ONLY Logistic Model is requested.
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Parameter estimates converged after 47 iterations.
Optimal solution found.
Parameter Estimates (LOGIT model: (LOG(p/(1-p))) = Intercept + BX):
Regression Coeff. Standard Error Coeff./S.E.
sinc -.02489 .00362 -6.88477
sacc .04634 .02370 1.95532
agegrp -.00248 .03100 -.07999
sex .47620 .13669 3.48383
agegrp2 .00721 .00199 3.61491
agesex -.00720 .04053 -.17754
age2sex -.00508 .00269 -1.88617
agesinc .00152 .00043 3.55777
Intercept Standard Error Intercept/S.E.
-4.47972 .11737 -38.16616
Pearson Goodness-of-Fit Chi Square = 14323.468 DF = 12464 P = .000
Since Goodness-of-Fit Chi square is significant, a heterogeneity
factor is used in the calculation of confidence limits.
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Covariance(below) and Correlation(above) Matrices of Parameter Estimates
sinc sacc agegrp sex agegrp2 agesex
sinc .00001 .13106 .17788 -.02414 .00967 .01452
sacc .00001 .00056 -.01520 .00403 .02091 -.00544
agegrp .00002 -.00001 .00096 .68802 -.95313 -.73389
sex -.00001 .00001 .00292 .01868 -.63256 -.92002
agegrp2 .00000 .00000 -.00006 -.00017 .00000 .73103
agesex .00000 -.00001 -.00092 -.00510 .00006 .00164
age2sex .00000 .00000 .00006 .00030 .00000 -.00011
agesinc .00000 -3.829E-10 .00000 .00000 .00000 .00000
age2sex agesinc
sinc -.00835 -.90211
sacc .00831 -.00004
agegrp .70702 -.19015
sex .82454 .02077
agegrp2 -.73984 -.01999
agesex -.97410 -.01275
age2sex .00001 .00717
agesinc 8.261E-09 .00000
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Observed and Expected Frequencies
Number of Observed Expected
sinc Subjects Responses Responses Residual Prob
15.10 8.0 .0 .109 -.109 .01358
15.10 12.0 .0 .103 -.103 .00858
15.10 9.0 .0 .125 -.125 .01385
LInes missed out
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