Modelos Lineares Generalizados em Experimentação Agronômica

38 Clarice G.B. Demétrio
[o] probability distribution is BINOMIAL
[o] and binomial denominator M
[o] link function is LOGIT
[o] scale parameter is 1.000
[o]
[o] linear model:
[o] terms: 1+D
[o] estimate s.e. parameter
[o] 1 -3.226 0.3699 1
[o] 2 0.6051 0.06781 D
[o] scale parameter 1.000
[o]
[o] unit observed out of fitted residual
[o] 1 44 50 47.505 -2.277
[o] 2 42 49 39.567 0.881
[o] 3 24 46 21.398 0.769
[o] 4 16 48 13.618 0.763
[o] 5 6 50 8.040 -0.785
[o] 6 0 49 1.872 -1.395
[o]
[i] ? $stop
Programa SAS para realizar a regressão logística:
options nodate nonumber ps=1000;
Data Doses;
Input dose m y;
datalines;
10.2 50 44
7.7 49 42
5.1 46 24
3.8 48 16
2.6 50 6
0.0 49 0
1.0 ;
proc genmod;
model y/m=dose / dist=b ;
output out=saida p=predito;
run;
Data novo;
set saida;
pobs=y/m;
Yest=m*predito;
run;
proc print data=novo;
run;