*** loglinear models for contigency tables;

*** relation to logit models;

data newdrug;

input sex $ trtmnt $ response $ count;

datalines;

1 1 1 950

1 1 2 50

1 2 1 9000

1 2 2 1000

2 1 1 5000

2 1 2 5000

2 2 1 5

2 2 2 95

;

run;

** two factors case: X and Y only;

proc genmod data=newdrug;

class trtmnt response;

model count=trtmnt|response/ dist=poisson link=log p r;

run;

proc genmod data=newdrug;

freq count;

class trtmnt;

model response=trtmnt/ dist=bin link=logit p r;

run;

** X, Y, and Z;

** saturated model;

proc genmod data=newdrug;

class sex trtmnt response;

model count=sex|trtmnt|response/ dist=poisson link=log p r;

run;

** homogeneous association;

proc genmod data=newdrug;

class sex trtmnt response;

model count=sex trtmnt response sex*trtmnt sex*response trtmnt*response/ dist=poisson link=log p r;

run;

** the corresponding logit regression model;

proc genmod data=newdrug;

freq count; ** saturated model is different!! Ungrouped;

class sex trtmnt;

model response=sex trtmnt/ dist=bin link=logit p r;

run;

The SAS System 21:36 Sunday, November 8, 2009 13

The GENMOD Procedure

Model Information

Data Set WORK.NEWDRUG

Distribution Poisson

Link Function Log

Dependent Variable count

Number of Observations Read 8

Number of Observations Used 8

Class Level Information

Class Levels Values

trtmnt 2 1 2

response 2 1 2

Criteria For Assessing Goodness Of Fit

Criterion DF Value Value/DF

Deviance 4 22733.4149 5683.3537

Scaled Deviance 4 22733.4149 5683.3537

Pearson Chi-Square 4 17341.6819 4335.4205

Scaled Pearson X2 4 17341.6819 4335.4205

Log Likelihood 148707.7040

Algorithm converged.

Analysis Of Parameter Estimates

Standard Wald 95% Confidence Chi-

Parameter DF Estimate Error Limits Square Pr > ChiSq

Intercept 1 6.3054 0.0302 6.2461 6.3646 43534.6 <.0001

trtmnt 1 1 1.5286 0.0333 1.4633 1.5940 2102.76 <.0001

trtmnt 2 0 0.0000 0.0000 0.0000 0.0000 . .

response 1 1 2.1070 0.0320 2.0443 2.1698 4334.27 <.0001

response 2 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt*response 1 1 1 -1.9430 0.0373 -2.0161 -1.8699 2715.33 <.0001

trtmnt*response 1 2 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt*response 2 1 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt*response 2 2 0 0.0000 0.0000 0.0000 0.0000 . .

Scale 0 1.0000 0.0000 1.0000 1.0000

The SAS System 21:36 Sunday, November 8, 2009 14

The GENMOD Procedure

NOTE: The scale parameter was held fixed.

Observation Statistics

Observation count Pred Xbeta Std HessWgt Resraw

Reschi Resdev StResdev StReschi Reslik

1 950 2975 7.9979993 0.0129641 2975 -2025

-37.12629 -43.37141 -61.33643 -52.5045 -57.09151

2 50 2525 7.8339963 0.014072 2525 -2475

-49.25434 -67.5115 -95.47568 -69.65616 -83.56909

3 9000 4502.5 8.4123881 0.010538 4502.5 4497.5

67.026155 58.920726 83.32649 94.789297 89.242128

4 1000 547.5 6.3053625 0.0302199 547.5 452.5

19.338666 17.314319 24.486144 27.349004 25.957073

5 5000 2975 7.9979993 0.0129641 2975 2025

37.126289 33.792584 47.789931 52.504502 50.20259

6 5000 2525 7.8339963 0.014072 2525 2475

49.254341 43.381661 61.350933 69.656157 65.635041

7 5 4502.5 8.4123881 0.010538 4502.5 -4497.5

-67.02616 -94.48265 -133.6186 -94.7893 -115.8425

8 95 547.5 6.3053625 0.0302199 547.5 -452.5

-19.33867 -23.92107 -33.82951 -27.349 -30.76039

The SAS System 21:36 Sunday, November 8, 2009 15

The GENMOD Procedure

Model Information

Data Set WORK.NEWDRUG

Distribution Binomial

Link Function Logit

Dependent Variable response

Frequency Weight Variable count

Number of Observations Read 8

Number of Observations Used 8

Sum of Frequencies Read 21100

Sum of Frequencies Used 21100

Number of Events 4

Number of Trials 8

Class Level Information

Class Levels Values

trtmnt 2 1 2

Response Profile

Ordered Total

Value response Frequency

1 1 14955

2 2 6145

PROC GENMOD is modeling the probability that response='1'. One way to change this to model the

probability that response='2' is to specify the DESCENDING option in the PROC statement.

Criteria For Assessing Goodness Of Fit

Criterion DF Value Value/DF

Deviance 21E3 22107.9653 1.0479

Scaled Deviance 21E3 22107.9653 1.0479

Pearson Chi-Square 21E3 21099.9973 1.0001

Scaled Pearson X2 21E3 21099.9973 1.0001

Log Likelihood -11053.9827

Algorithm converged.

The SAS System 21:36 Sunday, November 8, 2009 16

The GENMOD Procedure

Analysis Of Parameter Estimates

Standard Wald 95% Confidence Chi-

Parameter DF Estimate Error Limits Square Pr > ChiSq

Intercept 1 2.1070 0.0320 2.0443 2.1698 4334.27 <.0001

trtmnt 1 1 -1.9430 0.0373 -2.0161 -1.8699 2715.33 <.0001

trtmnt 2 0 0.0000 0.0000 0.0000 0.0000 . .

Scale 0 1.0000 0.0000 1.0000 1.0000

NOTE: The scale parameter was held fixed.

Observation Statistics

Observation response count Pred Xbeta Std HessWgt Resraw

Reschi Resdev StResdev StReschi Reslik

1 1 950 0.5409091 0.164003 0.0191334 235.91012 0.4590909

0.9212706 1.1086064 1.1598202 0.9638302 1.144219

2 2 50 0.5409091 0.164003 0.0191334 12.416322 -0.540909

-1.085457 -1.247804 -1.250649 -1.087933 -1.249958

3 1 9000 0.8915841 2.1070253 0.0320045 869.95686 0.1084159

0.3487107 0.479073 1.4516639 1.0566463 1.106532

4 2 1000 0.8915841 2.1070253 0.0320045 96.661873 -0.891584

-2.867707 -2.107976 -2.22078 -3.021167 -2.312416

5 1 5000 0.5409091 0.164003 0.0191334 1241.6322 0.4590909

0.9212706 1.1086064 1.5010601 1.2474063 1.3915067

6 2 5000 0.5409091 0.164003 0.0191334 1241.6322 -0.540909

-1.085457 -1.247804 -1.689534 -1.469716 -1.593381

7 1 5 0.8915841 2.1070253 0.0320045 0.4833094 0.1084159

0.3487107 0.479073 0.4791917 0.348797 0.4791359

8 2 95 0.8915841 2.1070253 0.0320045 9.1828779 -0.891584

-2.867707 -2.107976 -2.11796 -2.881289 -2.126417

The SAS System 21:36 Sunday, November 8, 2009 17

The GENMOD Procedure

Model Information

Data Set WORK.NEWDRUG

Distribution Poisson

Link Function Log

Dependent Variable count

Number of Observations Read 8

Number of Observations Used 8

Class Level Information

Class Levels Values

sex 2 1 2

trtmnt 2 1 2

response 2 1 2

Criteria For Assessing Goodness Of Fit

Criterion DF Value Value/DF

Deviance 0 0.0000 .

Scaled Deviance 0 0.0000 .

Pearson Chi-Square 0 0.0000 .

Scaled Pearson X2 0 0.0000 .

Log Likelihood 160074.4114

Algorithm converged.

Analysis Of Parameter Estimates

Standard Wald 95% Chi-

Parameter DF Estimate Error Confidence Limits Square Pr > ChiSq

Intercept 1 4.5539 0.1026 4.3528 4.7550 1970.09 <.0001

sex 1 1 2.3539 0.1074 2.1435 2.5643 480.70 <.0001

sex 2 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt 1 1 3.9633 0.1036 3.7603 4.1663 1464.42 <.0001

trtmnt 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt 1 1 1 -6.9590 0.1781 -7.3082 -6.6099 1526.44 <.0001

sex*trtmnt 1 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt 2 1 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt 2 2 0 0.0000 0.0000 0.0000 0.0000 . .

response 1 1 -2.9444 0.4588 -3.8437 -2.0451 41.18 <.0001

The SAS System 21:36 Sunday, November 8, 2009 18

The GENMOD Procedure

Analysis Of Parameter Estimates

Standard Wald 95% Chi-

Parameter DF Estimate Error Confidence Limits Square Pr > ChiSq

response 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*response 1 1 1 5.1417 0.4600 4.2400 6.0433 124.92 <.0001

sex*response 1 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*response 2 1 0 0.0000 0.0000 0.0000 0.0000 . .

sex*response 2 2 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt*response 1 1 1 2.9444 0.4593 2.0443 3.8446 41.10 <.0001

trtmnt*response 1 2 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt*response 2 1 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt*response 2 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt*response 1 1 1 1 -2.1972 0.4828 -3.1435 -1.2510 20.71 <.0001

sex*trtmnt*response 1 1 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt*response 1 2 1 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt*response 1 2 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt*response 2 1 1 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt*response 2 1 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt*response 2 2 1 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt*response 2 2 2 0 0.0000 0.0000 0.0000 0.0000 . .

Scale 0 1.0000 0.0000 1.0000 1.0000

NOTE: The scale parameter was held fixed.

Observation Statistics

Observation count Pred Xbeta Std HessWgt Resraw

Reschi Resdev StResdev StReschi Reslik

1 950 950 6.856462 0.0324443 950 -1.14E-13

-3.69E-15 0 . . .

2 50 50 3.912023 0.1414214 50 -6.39E-14

-9.04E-15 -2.281E-9 -0.033642 -1.334E-7 -1.334E-7

3 9000 9000 9.1049799 0.0105409 9000 -3.64E-12

-3.83E-14 -2.296E-8 . . .

4 1000 1000 6.9077553 0.0316228 1000 -6.82E-12

-2.16E-13 -2.356E-8 -0.453515 -4.152E-6 -4.152E-6

5 5000 5000 8.5171932 0.0141421 5000 -1.27E-11

-1.8E-13 -1.054E-8 . . .

6 5000 5000 8.5171932 0.0141421 5000 -3.64E-12

-5.14E-14 0 0 -2.572E-7 -2.572E-7

7 5 5 1.6094379 0.4472136 5 1.319E-11

5.898E-12 6.585E-10 0.0023146 0.0000207 0.0000207

8 95 95 4.5538769 0.1025978 95 1.435E-11

1.473E-12 0 . . .

The SAS System 21:36 Sunday, November 8, 2009 19

The GENMOD Procedure

Model Information

Data Set WORK.NEWDRUG

Distribution Poisson

Link Function Log

Dependent Variable count

Number of Observations Read 8

Number of Observations Used 8

Class Level Information

Class Levels Values

sex 2 1 2

trtmnt 2 1 2

response 2 1 2

Criteria For Assessing Goodness Of Fit

Criterion DF Value Value/DF

Deviance 1 32.9989 32.9989

Scaled Deviance 1 32.9989 32.9989

Pearson Chi-Square 1 28.2187 28.2187

Scaled Pearson X2 1 28.2187 28.2187

Log Likelihood 160057.9120

Algorithm converged.

Analysis Of Parameter Estimates

Standard Wald 95% Confidence Chi-

Parameter DF Estimate Error Limits Square Pr > ChiSq

Intercept 1 4.3483 0.1053 4.1419 4.5546 1706.05 <.0001

sex 1 1 2.5770 0.1085 2.3643 2.7897 564.05 <.0001

sex 2 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt 1 1 4.1725 0.1059 3.9648 4.3801 1551.04 <.0001

trtmnt 2 0 0.0000 0.0000 0.0000 0.0000 . .

response 1 1 -1.2278 0.1452 -1.5124 -0.9432 71.49 <.0001

response 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt 1 1 1 -7.6213 0.1504 -7.9162 -7.3265 2567.00 <.0001

sex*trtmnt 1 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*trtmnt 2 1 0 0.0000 0.0000 0.0000 0.0000 . .

The SAS System 21:36 Sunday, November 8, 2009 20

The GENMOD Procedure

Analysis Of Parameter Estimates

Standard Wald 95% Confidence Chi-

Parameter DF Estimate Error Limits Square Pr > ChiSq

sex*trtmnt 2 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*response 1 1 1 3.4055 0.1442 3.1230 3.6881 557.90 <.0001

sex*response 1 2 0 0.0000 0.0000 0.0000 0.0000 . .

sex*response 2 1 0 0.0000 0.0000 0.0000 0.0000 . .

sex*response 2 2 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt*response 1 1 1 1.2207 0.1448 0.9368 1.5046 71.02 <.0001

trtmnt*response 1 2 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt*response 2 1 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt*response 2 2 0 0.0000 0.0000 0.0000 0.0000 . .

Scale 0 1.0000 0.0000 1.0000 1.0000

NOTE: The scale parameter was held fixed.

Observation Statistics

Observation count Pred Xbeta Std HessWgt Resraw

Reschi Resdev StResdev StReschi Reslik

1 950 967.65696 6.8748776 0.0319629 967.65696 -17.65696

-0.567617 -0.569356 -5.328409 -5.31213 -5.312316

2 50 32.343056 3.4763993 0.1426775 32.343056 17.656944

3.1047384 2.8720164 4.9139446 5.3121259 5.179552

3 9000 8982.343 9.103016 0.0105448 8982.343 17.656956

0.1863035 0.1862425 5.3103906 5.3121296 5.3121274

4 1000 1017.657 6.9252582 0.0311766 1017.657 -17.65696

-0.553497 -0.555109 -5.327603 -5.31213 -5.312298

5 5000 4982.343 8.5136556 0.0141515 4982.343 17.656956

0.2501491 0.2500016 5.3089966 5.3121296 5.3121226

6 5000 5017.657 8.5207184 0.0141017 5017.657 -17.65696

-0.249267 -0.249414 -5.31525 -5.31213 -5.312136

7 5 22.656967 3.1204674 0.1503799 22.656967 -17.65697

-3.709499 -4.494846 -6.436778 -5.312133 -5.887446

8 95 77.343044 4.3482506 0.1052733 77.343044 17.656956

2.0077295 1.9378016 5.1271114 5.3121294 5.2860965

The SAS System 21:36 Sunday, November 8, 2009 21

The GENMOD Procedure

Model Information

Data Set WORK.NEWDRUG

Distribution Binomial

Link Function Logit

Dependent Variable response

Frequency Weight Variable count

Number of Observations Read 8

Number of Observations Used 8

Sum of Frequencies Read 21100

Sum of Frequencies Used 21100

Number of Events 4

Number of Trials 8

Class Level Information

Class Levels Values

sex 2 1 2

trtmnt 2 1 2

Response Profile

Ordered Total

Value response Frequency

1 1 14955

2 2 6145

PROC GENMOD is modeling the probability that response='1'. One way to change this to model the

probability that response='2' is to specify the DESCENDING option in the PROC statement.

Criteria For Assessing Goodness Of Fit

Criterion DF Value Value/DF

Deviance 21E3 20834.3355 0.9875

Scaled Deviance 21E3 20834.3355 0.9875

Pearson Chi-Square 21E3 21418.9779 1.0153

Scaled Pearson X2 21E3 21418.9779 1.0153

Log Likelihood -10417.1678

The SAS System 21:36 Sunday, November 8, 2009 22

The GENMOD Procedure

Algorithm converged.

Analysis Of Parameter Estimates

Standard Wald 95% Confidence Chi-

Parameter DF Estimate Error Limits Square Pr > ChiSq

Intercept 1 -1.2278 0.1452 -1.5124 -0.9432 71.49 <.0001

sex 1 1 3.4055 0.1442 3.1230 3.6881 557.90 <.0001

sex 2 0 0.0000 0.0000 0.0000 0.0000 . .

trtmnt 1 1 1.2207 0.1448 0.9368 1.5046 71.02 <.0001

trtmnt 2 0 0.0000 0.0000 0.0000 0.0000 . .

Scale 0 1.0000 0.0000 1.0000 1.0000

NOTE: The scale parameter was held fixed.

Observation Statistics

Observation response count Pred Xbeta Std HessWgt Resraw

Reschi Resdev StResdev StReschi Reslik

1 1 950 0.9676569 3.398478 0.1437792 29.732141 0.0323431

0.1828226 0.256428 0.4130763 0.2945064 0.3450583

2 2 50 0.9676569 3.398478 0.1437792 1.5648495 -0.967657

-5.469783 -2.619678 -2.663107 -5.560461 -2.804088

3 1 9000 0.8982343 2.1777579 0.0328749 822.68495 0.1017657

0.3365936 0.4633019 1.3913665 1.0108422 1.0597902

4 2 1000 0.8982343 2.1777579 0.0328749 91.409439 -0.898234

-2.970942 -2.137794 -2.251921 -3.129547 -2.353239

5 1 5000 0.4982343 -0.007063 0.0199559 1249.9844 0.5017657

1.0035376 1.1804108 1.6656764 1.4160909 1.5464783

6 2 5000 0.4982343 -0.007063 0.0199559 1249.9844 -0.498234

-0.996475 -1.174412 -1.657212 -1.406125 -1.537358

7 1 5 0.2265697 -1.227783 0.1452136 0.8761794 0.7734303

1.8476073 1.7231963 1.7393392 1.8649157 1.7417414

8 2 95 0.2265697 -1.227783 0.1452136 16.647408 -0.22657

-0.541241 -0.716826 -0.889828 -0.671866 -0.81994