データ解析のための統計モデリング入門7章

> d4 <- d7[d7$x == 4,] #葉数4のサブセット
> table(d4$y) #生存数がyiだった個体をカウント

0 1 2 3 4 5 6 7 8 
3 1 4 2 1 1 2 3 3 
> c(mean(d4$y), var(d4$y)) #平均と分散
[1] 4.050000 8.365789
> library(glmmML)
> glmmML(cbind(y, N - y) ~ x, data = d7, family = binomial,  cluster = id) #glmmMLを使う

Call:  glmmML(formula = cbind(y, N - y) ~ x, family = binomial, data = d7,      cluster = id) 


              coef se(coef)      z Pr(>|z|)
(Intercept) -4.190   0.8777 -4.774 1.81e-06
x            1.005   0.2075  4.843 1.28e-06

Scale parameter in mixing distribution:  2.408 gaussian 
Std. Error:                              0.2202 

        LR p-value for H_0: sigma = 0:  2.136e-55 

Residual deviance: 269.4 on 97 degrees of freedom 	AIC: 275.4