Exam3.5 {StroupGLMM}

Example 3.5 from Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup(p-85)

Description

Exam3.5 fixed location, factorial treatment structure, Gaussian response

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

DataSet3.2

Examples

data(DataSet3.2)
DataSet3.2$A <- factor(x = DataSet3.2$A)
DataSet3.2$B <- factor(x = DataSet3.2$B)
DataSet3.2$loc <- factor(x = DataSet3.2$loc, level = c(8, 1, 2, 3, 4, 5, 6, 7))
Exam3.5.lm <-
  lm(
         formula     =  Y~ A + B +loc
       , data        =  DataSet3.2
    #  , subset
    #  , weights
    #  , na.action
       , method      =  "qr"
       , model       =  TRUE
    #  , x           =  FALSE
    #  , y           =  FALSE
       , qr          =  TRUE
       , singular.ok =  TRUE
       , contrasts   =  NULL
    #  , offset
    #  , ...
  )
  
##---a0 marginal mean
list3.5.a0 <- list(B = c("0" = 1,"1" = 0) )
library(phia)
Test3.5.a0 <-
  summary(testFactors(
      model  =  Exam3.5.lm
    , levels =  list3.5.a0)
    )
    
##---b0 marginal mean
list3.5.b0 <- list(B = c("0" = 1,"1" = 0) )
Test3.5.b0 <-
summary(testFactors(
    model  =  Exam3.5.lm
  , levels =  list3.5.b0)
  )
  
##---Simple effect of A on B0
Test3.5.AB0 <-
  summary(testInteractions(
      model  =  Exam3.5.lm
    , custom =  list3.5.b0
    , across =  "B")
    )
    
##---Simple effect of B on A0
Test3.5.BA0 <-
  summary(testInteractions(
      model  =  Exam3.5.lm
    , custom =  list3.5.a0
    , across =  "A")
    )
    
##---Simple Effect of A over B
(SimpleEffect3.5.AB <-
  summary(testInteractions(
      model  =  Exam3.5.lm
    , fixed  =   "A"
    , across =  "B")
    )
    )
    
##---Simple Effect of B over A
(SimpleEffect3.5.BA <-
  summary(testInteractions(
      model  =  Exam3.5.lm
    , fixed  =   "B"
    , across =  "A")
    )
)
#-------------------------------------------------------------
## Individula least squares treatment means
#-------------------------------------------------------------
(Lsm3.5 <-
  lsmeans::lsmeans(
      object  = Exam3.5.lm
    , specs   = ~A*B
    # , ...
  )
)