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/* BloodpressureTable6.5sent.sas */

optionsls=73;

*-------------------------------------------------

Data from Table 6.5, page 221, Agresti,

second edition. Blood pressure vs heart disease:

disease is the number of heart disease, count is the sampe size

*-------------------------------------------------;

data blood;

input blood disease count @@;

cards;

111.5 3 156 121.5 17 252 131.5 12 284 141.5 16 271

151.5 12 139 161.5 8 85 176.5 16 99 191.5 8 43

;

title'Table 6.5, page 221: Blood pressure and Heart disease';

procprint;

procgenmod;

model disease/count = blood/residualsOBSTATS;

quit;

run;

Table 6.5, page 221: Blood pressure and Heart disease 45

15:54 Wednesday, November 3, 2010

Obs blood disease count

1 111.5 3 1562 121.5 17 252

3 131.5 12 2844 141.5 16 2715 151.5 12 1396 161.5 8 85

7 176.5 16 998 191.5 8 43

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Table 6.5, page 221: Blood pressure and Heart disease 4615:54 Wednesday, November 3, 2010

The GENMOD Procedure

Model Information

Data Set WORK.BLOOD

Distribution BinomialLink Function LogitResponse Variable (Events) disease

Response Variable (Trials) count

Number of Observations Read 8Number of Observations Used 8Number of Events 92Number of Trials 1329

Response Profile

Ordered Binary TotalValue Outcome Frequency

1 Event 922 Nonevent 1237

Parameter Information

Parameter Effect

Prm1 InterceptPrm2 blood

Criteria For Assessing Goodness Of Fit

Criterion DF Value Value/DF

Deviance 6 5.9092 0.9849

Scaled Deviance 6 5.9092 0.9849Pearson Chi-Square 6 6.2899 1.0483Scaled Pearson X2 6 6.2899 1.0483

Log Likelihood -322.3590Full Log Likelihood -19.3052AIC (smaller is better) 42.6104AICC (smaller is better) 45.0104BIC (smaller is better) 42.7693

Algorithm converged.

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Table 6.5, page 221: Blood pressure and Heart disease 4715:54 Wednesday, November 3, 2010

The GENMOD Procedure

Analysis Of Maximum Likelihood Parameter Estimates

Standard Wald 95% Confidence Wald

Parameter DF Estimate Error Limits Chi-Square

Intercept 1 -6.0820 0.7243 -7.5017 -4.6624 70.51

blood 1 0.0243 0.0048 0.0148 0.0338 25.25Scale 0 1.0000 0.0000 1.0000 1.0000

Analysis Of MaximumLikelihood Parameter

Estimates

Parameter Pr > ChiSq

Intercept

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Table 6.5, page 221: Blood pressure and Heart disease 4815:54 Wednesday, November 3, 2010

The GENMOD Procedure

Observation Statistics

Predicted Linear

Observation disease count blood Value PredictorStandardError of

theLinear

Predictor HessWgt LowerRaw Pearson

Upper Residual ResidualStd Std

Deviance Deviance PearsonResidual Residual ResidualLikelihood

Residual Leverage CookDDFBETA_ DFBETA_ DFBETAS_

Intercept blood InterceptDFBETAS_

blood

1 3 156 111.5 0.0333004 -3.3683180.2071411 5.0218745 0.0224380.0491571 -2.194866 -0.979434-1.061683 -1.198648 -1.105788-1.179257 0.2154758 0.1679213-0.385955 0.0023849 -0.5328520.4923991

2 17 252 121.5 0.0420903 -3.1249360.1679419 10.16032 0.0306470.0575529 6.3932374 2.00570531.8501072 2.1903838 2.37459992.2447199 0.2865667 1.13246120.9254622 -0.005537 1.277698

-1.1431623 12 284 131.5 0.053073 -2.881553

0.1348821 14.272782 0.0412524

0.0680403 -3.072737 -0.813338-0.841966 -0.978546 -0.945274-0.970016 0.2596674 0.1567025

-0.284697 0.0015908 -0.3930550.3284438

4 16 271 141.5 0.0667218 -2.6381710.1134615 16.875178 0.05413840.0819765 -2.081617 -0.50673-0.51623 -0.583485 -0.572747-0.581169 0.2172429 0.0455213-0.090187 0.0003954 -0.1245130.0816423

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Table 6.5, page 221: Blood pressure and Heart disease 4915:54 Wednesday, November 3, 2010

The GENMOD Procedure

Observation Statistics

Predicted Linear

Observation disease count blood Value PredictorStandardError of

theLinear

Predictor HessWgt LowerRaw Pearson

Upper Residual ResidualStd Std

Deviance Deviance PearsonResidual Residual ResidualLikelihood

Residual Leverage CookDDFBETA_ DFBETA_ DFBETAS_

Intercept blood InterceptDFBETAS_

blood

5 12 139 151.5 0.0835709 -2.3947890.1106594 10.64557 0.06839070.1017527 0.3836399 0.11758160.1170016 0.1254648 0.12608680.1255461 0.1303602 0.0011916-0.000338 0.0000379 -0.0004670.0078231

6 8 85 161.5 0.1041999 -2.1514070.1277071 7.9340906 0.08304250.1299834 -0.856987 -0.304247-0.308775 -0.330927 -0.326074-0.330303 0.1293979 0.00790150.0348927 -0.000315 0.0481731

-0.0651327 16 99 176.5 0.1435229 -1.786333

0.176639 12.169481 0.1059742

0.1915257 1.791237 0.51347230.5049657 0.6411542 0.6519550.6452766 0.3797042 0.1300923

-0.252581 0.0019415 -0.3487150.4008656

8 8 43 191.5 0.1944641 -1.421260.2380121 6.7358569 0.13150060.2779276 -0.361958 -0.139464-0.140243 -0.178337 -0.177346-0.177959 0.3815848 0.00970340.0816421 -0.000599 0.1127155-0.123772

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