StroupGLMM (version 0.3.0)

Exam4.1: Example 4.1 from Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup(p-138)

Description

Exam4.1 REML vs ML criterion is used keeping block effects random

Author

1. Muhammad Yaseen ()

2. Adeela Munawar ()

References

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

See Also

DataSet4.1

Examples

DataSet4.1$trt   <- factor(x =  DataSet4.1$trt)
DataSet4.1$block <- factor(x =  DataSet4.1$block)

#---REML estimates on page 138(article 4.4.3.3)
library(lmerTest)

Exam4.1REML  <- lmer(formula = y~ trt +( 1|block ), data = DataSet4.1)
library(parameters)
model_parameters(Exam4.1REML)
print(VarCorr(x = Exam4.1REML), comp = c("Variance"))

##---ML estimates on page 138(article 4.4.3.3)
Exam4.1ML  <- lmer(formula = y ~ trt + (1|block), data = DataSet4.1, REML = FALSE)
model_parameters(Exam4.1ML)
print(VarCorr(x =  Exam4.1ML), comp = c("Variance"))

Exam4.1.lm <- lm(formula  = y~ trt + block, data = DataSet4.1)
anova(object = Exam4.1.lm)