StroupGLMM (version 0.3.0)

Exam2.B.6: Example 2.B.6 from Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup(p-58)

Description

Exam2.B.6 is related to multi batch regression data assuming different forms of linear models keeping batch effect random.

Author

1. Muhammad Yaseen ()

2. Adeela Munawar ()

References

1. Stroup, W. W. (2012). Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. CRC Press.

See Also

Table1.2

Examples

#-----------------------------------------------------------------------------------
## Nested Model with no intercept
#-----------------------------------------------------------------------------------

data(Table1.2)
Table1.2$Batch <- factor(x = Table1.2$Batch)
library(nlme)
Exam2.B.6fm1 <- lme(
      fixed       = Y ~ X
    , data        = Table1.2
    , random      = list(Batch = pdDiag(~1), X = pdDiag(~1))
    , method      = c("REML", "ML")[1]
    )
Exam2.B.6fm1
library(broom.mixed)
tidy(Exam2.B.6fm1)