Examp2.6.1 from 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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Description

Examp2.6.1 is used for inspecting probability distribution and to define a plausible process through linear models and generalized linear models.

Author(s)

  1. Muhammad Yaseen (myaseen208@gmail.com)

References

  1. Duchateau, L. and Janssen, P. and Rowlands, G. J. (1998).Linear Mixed Models. An Introduction with applications in Veterinary Research. International Livestock Research Institute.

See Also

ex124

Examples

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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(lme4)
 str(ex125)
 ex125$Region1 <- factor(ex125$Region)
 fm2.14 <- lmerTest::lmer(formula = Pcv ~ dose*Drug + (1|Region/Drug), data=ex125, REML = TRUE, 
                     contrasts = list(dose = "contr.SAS", Drug = "contr.SAS")
                     )
 summary(fm2.14)
 lmerTest::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))
 

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