# Exam2.B.5: Example 2.B.5 from Generalized Linear Mixed Models: Modern... In StroupGLMM: R Codes and Datasets for Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup

## Description

Exam2.B.5 is related to multi batch regression data assuming different forms of linear models.

## References

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

`Table1.2`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89``` ```#----------------------------------------------------------------------------------- ## 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 ```