Description Author(s) References See Also Examples
Exam3.3 use RCBD data with fixed location effect and different forms of estimable functions are shown in this example.
Muhammad Yaseen (myaseen208@gmail.com)
Adeela Munawar (adeela.uaf@gmail.com)
Stroup, W. W. (2012). Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. CRC Press.
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## linear model for Gaussian data
#-----------------------------------------------------------------------------------
data(DataSet3.2)
DataSet3.2$trt <- factor(x = DataSet3.2$trt, level = c(3,0,1,2))
DataSet3.2$loc <- factor(x = DataSet3.2$loc, level = c(8, 1, 2, 3, 4, 5, 6, 7))
Exam3.3.lm1 <-
lm(
formula = Y~ trt+loc
, data = DataSet3.2
# , subset
# , weights
# , na.action
, method = "qr"
, model = TRUE
# , x = FALSE
# , y = FALSE
, qr = TRUE
, singular.ok = TRUE
, contrasts = NULL
# , offset
# , ...
)
summary( Exam3.3.lm1 )
#-------------------------------------------------------------
## Individula least squares treatment means
#-------------------------------------------------------------
library(lsmeans)
(Lsm3.3 <-
lsmeans::lsmeans(
object = Exam3.3.lm1
, specs = "trt"
# , ...
)
)
#---------------------------------------------------
## Pairwise treatment means estimate
#---------------------------------------------------
contrast( object = Lsm3.3 , method = "pairwise")
#---------------------------------------------------
## Repairwise treatment means estimate
#---------------------------------------------------
## contrast( object = Lsm3.3 , method = "repairwise")
#-------------------------------------------------------
## LSM Trt0 (This term is used in Walter Stroups' book)
#-------------------------------------------------------
library(phia)
list3.3.1 <- list(trt=c("0" = 1 ) )
Test3.3.1 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.1)
)
#-------------------------------------------------------
## LSM Trt0 alt(This term is used in Walter Stroups' book)
#-------------------------------------------------------
list3.3.2 <-
list(trt=c("0" = 1 )
, loc=c("1" = 0,"2" = 0,"3" = 0,"4" = 0,"5" = 0,"6" = 0,"7" = 0)
)
Test3.3.2 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.2)
)
#-------------------------------------------------------
## Trt0 Vs Trt1
#-------------------------------------------------------
list3.3.3 <- list(trt=c("0" = 1,"1" = -1))
Test3.3.3 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.3)
)
#-------------------------------------------------------
## average Trt0+1
#-------------------------------------------------------
list3.3.4 <- list(trt=c("0" = 0.5 , "1" = 0.5))
Test3.3.4 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.4)
)
#-------------------------------------------------------
## average Trt0+2+3
#-------------------------------------------------------
list3.3.5 <- list(trt=c("0" = 0.33333,"2" = 0.33333,"3" = 0.33333))
Test3.3.5 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.5)
)
#-------------------------------------------------------
## Trt 2 Vs 3 difference
#-------------------------------------------------------
list3.3.6 <- list(trt=c("2" = 1,"3" = -1))
Test3.3.6 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.6)
)
#-------------------------------------------------------
## Trt 1 Vs 2 difference
#-------------------------------------------------------
list3.3.7 <- list(trt=c("1" = 1,"2" = -1))
Test3.3.7 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.7)
)
#-------------------------------------------------------
## Trt 1 Vs 3 difference
#-------------------------------------------------------
list3.3.8 <- list(trt=c("1" = 1,"3" = -1))
Test3.3.8 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.8)
)
#-------------------------------------------------------
## Average trt0+1 vs Average Trt2+3
#-------------------------------------------------------
list3.3.9 <- list(trt=c("0" = 0.5,"1" = 0.5,"2" = -0.5,"3" = -0.5))
Test3.3.9 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.9)
)
#-------------------------------------------------------
## Trt1 vs Average Trt0+1+2
#-------------------------------------------------------
list3.3.10 <- list(trt=c("0" = 0.33333,"1" = -1,"2" = 0.33333,"3" = 0.33333))
Test3.3.10 <-
summary(testFactors(
model = Exam3.3.lm1
, levels = list3.3.10)
)
#-------------------------------------------------------
## Sidak Multiplicity adjustment for p-values
#-------------------------------------------------------
library(mutoss)
PValues3.3 <-
c(
Test3.3.3[[7]][1, 4]
, Test3.3.6[[7]][1, 4]
, Test3.3.7[[7]][1, 4]
, Test3.3.8[[7]][1, 4]
, Test3.3.9[[7]][1, 4]
, Test3.3.10[[7]][1, 4]
)
AdjPValues3.3 <- sidak(PValues3.3)
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