Documentation Example 3 for PROC FMM
/****************************************************************/
/* S A S S A M P L E L I B R A R Y */
/* */
/* NAME: fmmex03 */
/* TITLE: Documentation Example 3 for PROC FMM */
/* Mixed Poisson Regression */
/* PRODUCT: STAT */
/* SYSTEM: ALL */
/* KEYS: Partially varying mean functions */
/* Likelihood ratio test */
/* Outlier induces overdispersion */
/* */
/* PROCS: FMM */
/* DATA: Ames salmonella assay data, Margolin et al. (1981) */
/* */
/* SUPPORT: John Castelloe */
/* REF: Wang, P., Puterman, M. L., Cockburn, I., and Le, N.,*/
/* (1996), Mixed Poisson Regression Models With */
/* Covariate Dependent Rates, Biometrics, 52, 381--400.*/
/* MISC: */
/****************************************************************/
data assay;
label dose = 'Dose of quinoline (microg/plate)'
num = 'Observed number of colonies';
input dose @;
logd = log(dose+10);
do i=1 to 3; input num@; output; end;
datalines;
0 15 21 29
10 16 18 21
33 16 26 33
100 27 41 60
333 33 38 41
1000 20 27 42
;
proc fmm data=assay;
model num = dose logd / dist=Poisson;
run;
proc fmm data=assay;
model num = dose logd / dist=Poisson k=2
equate=effects(dose logd);
run;
proc fmm data=assay;
model num = dose logd / dist=Poisson k=2;
restrict 'common dose' dose 1, dose -1;
restrict 'common logd' logd 1, logd -1;
run;
proc fmm data=assay(where=(num ne 60));
model num = dose logd / dist=Poisson k=2
equate=effects(dose logd);
run;
proc fmm data=assay(where=(num ne 60));
model num = dose logd / dist=Poisson;
run;