3.3 Generalized estimating equations model

Below logistic model takes account of repeat observation by cow. Examine different correlation structures. It is of interest to note that (odds of) high protein content in milk appears to decrease as time since calving increases.

Milk <- Milk |> modify_if(is.character, as.factor);
Milk <- Milk |> tidyr::drop_na()
Milk <- droplevels(Milk);
Milk <- Milk |> dplyr::arrange(Yard, Cow, Time);

rm_mvsum(model=geeglm(HP ~ Diet + Yard + Time, id=c(Cow), data=Milk, family=binomial, corstr="ar1"), data=Milk, showN=T, CIwidth=0.95);

	OR(95%CI)	p-value	N	Event	VIF
Diet			1337	386	1.04
barley	Reference		425	183
barley+lupins	0.47 (0.27, 0.82)	0.008	459	119
lupins	0.31 (0.17, 0.55)	<0.001	453	84
Yard			1337	386	1.02
1	Reference		290	80
2	0.88 (0.44, 1.77)	0.72	317	86
3	1.03 (0.45, 2.34)	0.94	173	53
4	0.93 (0.42, 2.08)	0.86	231	67
5	1.20 (0.63, 2.27)	0.58	326	100
Time	0.92 (0.88, 0.95)	<0.001	1337	386	1.03