> fit <- glm(sumY ~ Base + Age + Trt, data=breslow.dat, family=poisson())

> summary(fit)

Call:

glm(formula = sumY ~ Base + Age + Trt, family = poisson(), data =

breslow.dat)

Deviance Residuals:

Min 1Q Median 3Q Max

-6.057 -2.043 -0.940 0.793 11.006

Coefficients:

Estimate Std. Error z value Pr(>|z|)

(Intercept) 1.948826 0.135619 14.37 < 2e-16 ***

Base 0.022652 0.000509 44.48 < 2e-16 ***

Age 0.022740 0.004024 5.65 1.6e-08 ***

Trtprogabide -0.152701 0.047805 -3.19 0.0014 **

---

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for poisson family taken to be 1)

Null deviance: 2122.73 on 58 degrees of freedom

Residual deviance: 559.44 on 55 degrees of freedom

AIC: 850.7

Number of Fisher Scoring iterations: 5

输出结果列出了偏差、回归参数、标准误和参数为0的检验。注意，此处预测变量在p<0.05

的水平下都非常显著。