Exam2.B.6: Example 2.B.6 from Generalized Linear Mixed Models: Modern...

In myaseen208/StroupGLMM: R Codes and Datasets for Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup

Description

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

Author(s)

1. Muhammad Yaseen ([e-mail])

2. Adeela Munawar ([e-mail])

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)
library(nlme)
Table1.2$Batch <- factor(x = Table1.2$Batch)
Exam2.B.6fm1 <-
  lme(
      fixed       = Y~X
    , data        = Table1.2
    , random      = list(Batch = pdDiag(~1), X = pdDiag(~1))
    , correlation = NULL
    , weights     = NULL
  # , subset
    , method      = "REML" #c("REML", "ML")
    , na.action   = na.fail
  # , control     = list()
    , contrasts   = NULL
    , keep.data   = TRUE
  )

myaseen208/StroupGLMM documentation built on May 10, 2019, 8:28 a.m.