Hi all,
running the following code:
n <- 25
y0 <- rpois(n, 0.04)
y1 <- rpois(n, 0.34)
resp <- c(y0, y1)
group <- c(rep(0,n), rep(1,n))
wilcox.test(y0, y1)
Wilcoxon rank sum test with continuity
correction
data: y0 and y1
W = 250, p-value = 0.02074
alternative hypothesis: true mu is not equal to 0
Warning message:
Cannot compute exact p-value with ties in:
wilcox.test.default(y0, y1)
glm.M1 <- glm(resp ~ group, family=poisson())
summary(glm.M1)
Call:
glm(formula = resp ~ group, family = poisson())
Deviance Residuals:
Min 1Q Median 3Q
Max
-0.692820 -0.692820 -0.004968 -0.004968
2.227342
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -11.303 34.531 -0.327 0.743
group 9.875 34.533 0.286 0.775
(Dispersion parameter for poisson family taken to
be 1)
Null deviance: 28.216 on 49 degrees of
freedom
Residual deviance: 19.899 on 48 degrees of
freedom
AIC: 34.512
Number of Fisher Scoring iterations: 9
I would interpretate this that the Wilcoxon detect
a group difference, while glm not. I expected the
beta for the group greater than zero.
Can somebody explain me such an difference of two
methods of rejecting a hypothesis? Where am I
wrong?