Example 2.B.5 from Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup(p-57)
Source:R/Exam2.B.5.R
Exam2.B.5.RdExam2.B.5 is related to multi batch regression data assuming different forms of linear models.
References
Stroup, W. W. (2012). Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. CRC Press.
Author
Muhammad Yaseen (myaseen208@gmail.com)
Adeela Munawar (adeela.uaf@gmail.com)
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)
DesignMatrix.lm1 <- model.matrix (object = Exam2.B.5.lm1)
DesignMatrix.lm1
#> Batch1 Batch2 Batch3 Batch4 Batch1:X Batch2:X Batch3:X Batch4:X
#> 1 1 0 0 0 0 0 0 0
#> 2 1 0 0 0 3 0 0 0
#> 3 1 0 0 0 6 0 0 0
#> 4 1 0 0 0 9 0 0 0
#> 5 1 0 0 0 12 0 0 0
#> 6 1 0 0 0 18 0 0 0
#> 7 1 0 0 0 24 0 0 0
#> 8 1 0 0 0 36 0 0 0
#> 9 1 0 0 0 48 0 0 0
#> 10 0 1 0 0 0 0 0 0
#> 11 0 1 0 0 0 3 0 0
#> 12 0 1 0 0 0 6 0 0
#> 13 0 1 0 0 0 9 0 0
#> 14 0 1 0 0 0 12 0 0
#> 15 0 1 0 0 0 18 0 0
#> 16 0 1 0 0 0 24 0 0
#> 17 0 1 0 0 0 36 0 0
#> 18 0 1 0 0 0 48 0 0
#> 19 0 0 1 0 0 0 0 0
#> 20 0 0 1 0 0 0 3 0
#> 21 0 0 1 0 0 0 6 0
#> 22 0 0 1 0 0 0 9 0
#> 23 0 0 1 0 0 0 12 0
#> 24 0 0 1 0 0 0 18 0
#> 25 0 0 1 0 0 0 24 0
#> 26 0 0 1 0 0 0 36 0
#> 27 0 0 1 0 0 0 48 0
#> 28 0 0 0 1 0 0 0 0
#> 29 0 0 0 1 0 0 0 3
#> 30 0 0 0 1 0 0 0 6
#> 31 0 0 0 1 0 0 0 9
#> 32 0 0 0 1 0 0 0 12
#> 33 0 0 0 1 0 0 0 18
#> 34 0 0 0 1 0 0 0 24
#> 35 0 0 0 1 0 0 0 36
#> 36 0 0 0 1 0 0 0 48
#> attr(,"assign")
#> [1] 1 1 1 1 2 2 2 2
#> attr(,"contrasts")
#> attr(,"contrasts")$Batch
#> [1] "contr.treatment"
#>
#-----------------------------------------------------------------------------------
## Interaction Model with intercept
#-----------------------------------------------------------------------------------
Exam2.B.5.lm2 <-lm(formula = Y ~ Batch + X + Batch*X, data = Table1.2)
DesignMatrix.lm2 <- model.matrix (object = Exam2.B.5.lm2)
DesignMatrix.lm2
#> (Intercept) Batch2 Batch3 Batch4 X Batch2:X Batch3:X Batch4:X
#> 1 1 0 0 0 0 0 0 0
#> 2 1 0 0 0 3 0 0 0
#> 3 1 0 0 0 6 0 0 0
#> 4 1 0 0 0 9 0 0 0
#> 5 1 0 0 0 12 0 0 0
#> 6 1 0 0 0 18 0 0 0
#> 7 1 0 0 0 24 0 0 0
#> 8 1 0 0 0 36 0 0 0
#> 9 1 0 0 0 48 0 0 0
#> 10 1 1 0 0 0 0 0 0
#> 11 1 1 0 0 3 3 0 0
#> 12 1 1 0 0 6 6 0 0
#> 13 1 1 0 0 9 9 0 0
#> 14 1 1 0 0 12 12 0 0
#> 15 1 1 0 0 18 18 0 0
#> 16 1 1 0 0 24 24 0 0
#> 17 1 1 0 0 36 36 0 0
#> 18 1 1 0 0 48 48 0 0
#> 19 1 0 1 0 0 0 0 0
#> 20 1 0 1 0 3 0 3 0
#> 21 1 0 1 0 6 0 6 0
#> 22 1 0 1 0 9 0 9 0
#> 23 1 0 1 0 12 0 12 0
#> 24 1 0 1 0 18 0 18 0
#> 25 1 0 1 0 24 0 24 0
#> 26 1 0 1 0 36 0 36 0
#> 27 1 0 1 0 48 0 48 0
#> 28 1 0 0 1 0 0 0 0
#> 29 1 0 0 1 3 0 0 3
#> 30 1 0 0 1 6 0 0 6
#> 31 1 0 0 1 9 0 0 9
#> 32 1 0 0 1 12 0 0 12
#> 33 1 0 0 1 18 0 0 18
#> 34 1 0 0 1 24 0 0 24
#> 35 1 0 0 1 36 0 0 36
#> 36 1 0 0 1 48 0 0 48
#> attr(,"assign")
#> [1] 0 1 1 1 2 3 3 3
#> attr(,"contrasts")
#> attr(,"contrasts")$Batch
#> [1] "contr.treatment"
#>
#-----------------------------------------------------------------------------------
## Interaction Model with no intercept
#-----------------------------------------------------------------------------------
Exam2.B.5.lm3 <- lm(formula = Y ~ 0 + Batch + Batch*X, data = Table1.2)
DesignMatrix.lm3 <- model.matrix(object = Exam2.B.5.lm3)
DesignMatrix.lm3
#> Batch1 Batch2 Batch3 Batch4 X Batch2:X Batch3:X Batch4:X
#> 1 1 0 0 0 0 0 0 0
#> 2 1 0 0 0 3 0 0 0
#> 3 1 0 0 0 6 0 0 0
#> 4 1 0 0 0 9 0 0 0
#> 5 1 0 0 0 12 0 0 0
#> 6 1 0 0 0 18 0 0 0
#> 7 1 0 0 0 24 0 0 0
#> 8 1 0 0 0 36 0 0 0
#> 9 1 0 0 0 48 0 0 0
#> 10 0 1 0 0 0 0 0 0
#> 11 0 1 0 0 3 3 0 0
#> 12 0 1 0 0 6 6 0 0
#> 13 0 1 0 0 9 9 0 0
#> 14 0 1 0 0 12 12 0 0
#> 15 0 1 0 0 18 18 0 0
#> 16 0 1 0 0 24 24 0 0
#> 17 0 1 0 0 36 36 0 0
#> 18 0 1 0 0 48 48 0 0
#> 19 0 0 1 0 0 0 0 0
#> 20 0 0 1 0 3 0 3 0
#> 21 0 0 1 0 6 0 6 0
#> 22 0 0 1 0 9 0 9 0
#> 23 0 0 1 0 12 0 12 0
#> 24 0 0 1 0 18 0 18 0
#> 25 0 0 1 0 24 0 24 0
#> 26 0 0 1 0 36 0 36 0
#> 27 0 0 1 0 48 0 48 0
#> 28 0 0 0 1 0 0 0 0
#> 29 0 0 0 1 3 0 0 3
#> 30 0 0 0 1 6 0 0 6
#> 31 0 0 0 1 9 0 0 9
#> 32 0 0 0 1 12 0 0 12
#> 33 0 0 0 1 18 0 0 18
#> 34 0 0 0 1 24 0 0 24
#> 35 0 0 0 1 36 0 0 36
#> 36 0 0 0 1 48 0 0 48
#> attr(,"assign")
#> [1] 1 1 1 1 2 3 3 3
#> attr(,"contrasts")
#> attr(,"contrasts")$Batch
#> [1] "contr.treatment"
#>
#-----------------------------------------------------------------------------------
## Interaction Model with intercept but omitting X term as main effect
#-----------------------------------------------------------------------------------
Exam2.B.5.lm4 <- lm(formula = Y ~ Batch + Batch*X, data = Table1.2)
DesignMatrix.lm4 <- model.matrix(object = Exam2.B.5.lm4)
DesignMatrix.lm4
#> (Intercept) Batch2 Batch3 Batch4 X Batch2:X Batch3:X Batch4:X
#> 1 1 0 0 0 0 0 0 0
#> 2 1 0 0 0 3 0 0 0
#> 3 1 0 0 0 6 0 0 0
#> 4 1 0 0 0 9 0 0 0
#> 5 1 0 0 0 12 0 0 0
#> 6 1 0 0 0 18 0 0 0
#> 7 1 0 0 0 24 0 0 0
#> 8 1 0 0 0 36 0 0 0
#> 9 1 0 0 0 48 0 0 0
#> 10 1 1 0 0 0 0 0 0
#> 11 1 1 0 0 3 3 0 0
#> 12 1 1 0 0 6 6 0 0
#> 13 1 1 0 0 9 9 0 0
#> 14 1 1 0 0 12 12 0 0
#> 15 1 1 0 0 18 18 0 0
#> 16 1 1 0 0 24 24 0 0
#> 17 1 1 0 0 36 36 0 0
#> 18 1 1 0 0 48 48 0 0
#> 19 1 0 1 0 0 0 0 0
#> 20 1 0 1 0 3 0 3 0
#> 21 1 0 1 0 6 0 6 0
#> 22 1 0 1 0 9 0 9 0
#> 23 1 0 1 0 12 0 12 0
#> 24 1 0 1 0 18 0 18 0
#> 25 1 0 1 0 24 0 24 0
#> 26 1 0 1 0 36 0 36 0
#> 27 1 0 1 0 48 0 48 0
#> 28 1 0 0 1 0 0 0 0
#> 29 1 0 0 1 3 0 0 3
#> 30 1 0 0 1 6 0 0 6
#> 31 1 0 0 1 9 0 0 9
#> 32 1 0 0 1 12 0 0 12
#> 33 1 0 0 1 18 0 0 18
#> 34 1 0 0 1 24 0 0 24
#> 35 1 0 0 1 36 0 0 36
#> 36 1 0 0 1 48 0 0 48
#> attr(,"assign")
#> [1] 0 1 1 1 2 3 3 3
#> attr(,"contrasts")
#> attr(,"contrasts")$Batch
#> [1] "contr.treatment"
#>