Exam3.2: Example 3.2 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

Example 3.2 from Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup(p-73)

Description

Exam3.2 used binomial data, two treatment samples

Author(s)

1. Muhammad Yaseen ([e-mail])

2. Adeela Munawar ([e-mail])

References

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

See Also

DataSet3.1

Examples

#-------------------------------------------------------------
## Linear Model and results discussed in Article 1.2.1 after Table1.1
#-------------------------------------------------------------
data(DataSet3.1)
DataSet3.1$trt <- factor(x =  DataSet3.1$trt)
Exam3.2.glm <- glm(formula =  F/N~trt, family =  quasibinomial(link = "logit"), data =  DataSet3.1)
summary(Exam3.2.glm)
library(parameters)
model_parameters(Exam3.2.glm)

#-------------------------------------------------------------
## Individula least squares treatment means
#-------------------------------------------------------------
library(emmeans)
emmeans(object  = Exam3.2.glm, specs   = "trt")
emmeans(object  = Exam3.2.glm, specs   = "trt", type = "response")

#---------------------------------------------------
## Over all mean
#---------------------------------------------------
library(phia)
list3.2 <-   list(trt = c("0" = 0.5, "1" = 0.5 ))
testFactors(model  =  Exam3.2.glm, levels =  list3.2 )

#---------------------------------------------------
## Repairwise treatment means estimate
#---------------------------------------------------
contrast(emmeans(object  = Exam3.2.glm, specs   = "trt"))
contrast(emmeans(object  = Exam3.2.glm, specs   = "trt", type = "response"))

StroupGLMM documentation built on Oct. 2, 2024, 1:07 a.m.