List:  I'm helping a colleague with some Poisson regression modeling.  He 
uses SAS proc GENMOD and I'm using glm() in R.  Note on the SAS and R 
output below that our estimates, standard errors, and deviances are 
identical but what we get for likelihoods differs considerably.  I'm 
assuming that these must differ just by some constant but it would be nice 
to have some confirmation of this. I think I recall that this might have 
been discussed before on this list. 

> atrich01.spatial1<- glm(ATRICH ~  X_COORD_CTR + Y_COORD_CTR 
,data=bigbend.rich[bigbend.rich$YEAR.==0001,],family=poisson,contrasts=list(OBSERVER="contr.sum",VISIB="contr.sum"))

> summary(atrich01.spatial1)

Call:
glm(formula = ATRICH ~ X_COORD_CTR + Y_COORD_CTR, family = poisson, 
    data = bigbend.rich[bigbend.rich$YEAR. == 1, ], contrasts = 
list(OBSERVER = "contr.sum", 
        VISIB = "contr.sum"))

Deviance Residuals: 
   Min      1Q  Median      3Q     Max 
-4.390  -1.921  -0.582   1.574   7.346 

Coefficients:
             Estimate Std. Error z value Pr(>|z|) 
(Intercept)  2.994802   0.026926 111.225  < 2e-16 ***
X_COORD_CTR -0.111983   0.017115  -6.543 6.02e-11 ***
Y_COORD_CTR  0.000121   0.016283   0.007    0.994 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

(Dispersion parameter for poisson family taken to be 1)

    Null deviance: 466.66  on 69  degrees of freedom
Residual deviance: 422.50  on 67  degrees of freedom
AIC: 756.81

Number of Fisher Scoring iterations: 5

> logLik(atrich01.spatial1)
'log Lik.' -375.4041 (df=3)

SAS Output

                                                  The GENMOD Procedure

                                                   Model Information

                              Data Set              WORK.ONE
                              Distribution           Poisson
                              Link Function              Log
                              Dependent Variable      ATRICH    ATRICH

                                        Number of Observations Read   70
                                        Number of Observations Used   70

                                         Criteria For Assessing Goodness 
Of Fit

                              Criterion                 DF           Value 
       Value/DF

                              Deviance                  67        422.5009 
         6.3060
                              Scaled Deviance           67        422.5009 
         6.3060
                              Pearson Chi-Square        67        456.6382 
         6.8155
                              Scaled Pearson X2         67        456.6382 
         6.8155

                              Log Likelihood                     2876.1605 
 LINEAR MODEL

                      Algorithm converged.


                                                 The GENMOD Procedure

                                            Analysis Of Parameter 
Estimates

                                               Standard     Wald 95% 
Confidence       Chi-
                Parameter    DF    Estimate       Error           Limits   
      Square    Pr > ChiSq

                Intercept     1      2.9948      0.0269      2.9420 3.0476 
   12371.0        <.0001
                e                 1     -0.1120      0.0171     -0.1455  
-0.0784      42.81         <.0001
                n                 1      0.0001      0.0163     -0.0318  
0.0320       0.00           0.9941
                Scale          0      1.0000      0.0000      1.0000 
1.0000

NOTE: The scale parameter was held fixed.

Brian

Brian S. Cade

U. S. Geological Survey
Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO  80526-8818

email:  [EMAIL PROTECTED]
tel:  970 226-9326
        [[alternative HTML version deleted]]

______________________________________________
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Reply via email to