Exam2.B.5 {StroupGLMM} | R Documentation |
Example 2.B.5 from Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup(p-57)
Description
Exam2.B.5 is related to multi batch regression data assuming different forms of linear models.
Author(s)
Muhammad Yaseen (myaseen208@gmail.com)
Adeela Munawar (adeela.uaf@gmail.com)
References
Stroup, W. W. (2012). Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. CRC Press.
See Also
Examples
#-----------------------------------------------------------------------------------
## Nested Model with no intercept
#-----------------------------------------------------------------------------------
data(Table1.2)
Table1.2$Batch <- factor(x = Table1.2$Batch)
Exam2.B.5.lm1 <-
lm(
formula = Y~0+Batch+ Batch/X
, data = Table1.2
# , subset
# , weights
# , na.action
, method = "qr"
, model = TRUE
# , x = FALSE
# , y = FALSE
, qr = TRUE
, singular.ok = TRUE
, contrasts = NULL
# , offset
# , ...
)
DesignMatrix.lm1 <- model.matrix (object = Exam2.B.5.lm1)
DesignMatrix.lm1
#-----------------------------------------------------------------------------------
## Interaction Model with intercept
#-----------------------------------------------------------------------------------
Exam2.B.5.lm2 <-
lm(
formula = Y~Batch +X+ Batch*X
, data = Table1.2
# , subset
# , weights
# , na.action
, method = "qr"
, model = TRUE
# , x = FALSE
# , y = FALSE
, qr = TRUE
, singular.ok = TRUE
, contrasts = NULL
# , offset
# , ...
)
DesignMatrix.lm2 <- model.matrix (object = Exam2.B.5.lm2)
DesignMatrix.lm2
#-----------------------------------------------------------------------------------
## Interaction Model with no intercept
#-----------------------------------------------------------------------------------
Exam2.B.5.lm3 <-
lm(
formula = Y~0 + Batch + Batch*X
, data = Table1.2
# , subset
# , weights
# , na.action
, method = "qr"
, model = TRUE
# , x = FALSE
# , y = FALSE
, qr = TRUE
, singular.ok = TRUE
, contrasts = NULL
# , offset
# , ...
)
DesignMatrix.lm3 <- model.matrix(object = Exam2.B.5.lm3)
#-----------------------------------------------------------------------------------
## Interaction Model with intercept but omitting X term as main effect
#-----------------------------------------------------------------------------------
Exam2.B.5.lm4 <-
lm(
formula = Y~Batch + Batch*X
, data = Table1.2
# , subset
# , weights
# , na.action
, method = "qr"
, model = TRUE
# , x = FALSE
# , y = FALSE
, qr = TRUE
, singular.ok = TRUE
, contrasts = NULL
# , offset
# , ...
)
DesignMatrix.lm4 <- model.matrix(object = Exam2.B.5.lm4)
DesignMatrix.lm4
[Package StroupGLMM version 0.1.0 Index]