Description Author(s) References See Also Examples
Examp2.6.1 is used for inspecting probability distribution and to define a plausible process through linear models and generalized linear models.
Muhammad Yaseen (myaseen208@gmail.com)
Duchateau, L. and Janssen, P. and Rowlands, G. J. (1998).Linear Mixed Models. An Introduction with applications in Veterinary Research. International Livestock Research Institute.
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## Example 2.6.1 p-76
#-------------------------------------------------------------
# PROC MIXED DATA=ex125;
# CLASS drug dose region;
# MODEL pcv=drug dose drug*dose / ddfm=satterth;
# RANDOM region drug*region;
# CONTRAST 'drug dif' drug -1 1 drug*dose -0.5 -0.5 0.5 0.5;
# CONTRAST 'all' drug 1 -1 dose 0 0 drug*dose 0.5 0.5 -0.5 -0.5,
# drug 0 0 dose 1 -1 drug*dose 0.5 -0.5 0.5 -0.5,
# drug 0 0 dose 0 0 drug*dose 0.5 -0.5 -0.5 0.5;
# RUN;
library(lmerTest)
str(ex125)
ex125$Region1 <- factor(ex125$Region)
fm2.14 <-
lmerTest::lmer(
formula = Pcv ~ dose*Drug + (1|Region/Drug)
, data = ex125
, REML = TRUE
, control = lmerControl()
, start = NULL
, verbose = 0L
# , subset
# , weights
# , na.action
# , offset
, contrasts = list(dose = "contr.SAS", Drug = "contr.SAS")
, devFunOnly = FALSE
# , ...
)
summary(fm2.14)
anova(object = fm2.14, ddf = "Satterthwaite")
library(multcomp)
Contrasts3 <-
matrix(c(
0, 0, -1, -0.5
)
, ncol = 4
, byrow = TRUE
, dimnames = list(
c("C1")
, rownames(summary(fm2.14)$coef)
)
)
Contrasts3
summary(glht(fm2.14, linfct=Contrasts3))
if(packageVersion("lmerTest") >= "3.0")
contest(fm2.14, Contrasts3, joint = FALSE)
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