Exam4.3 {eda4treeR} | R Documentation |
Example 4.3 from Experimental Design and Analysis for Tree Improvement
Description
Exam4.3 presents the germination count data for 4 Pre-Treatments and 6 Seedlots.
Author(s)
Muhammad Yaseen (myaseen208@gmail.com)
Sami Ullah (samiullahuos@gmail.com)
References
E.R. Williams, C.E. Harwood and A.C. Matheson (2023). Experimental Design and Analysis for Tree Improvement. CSIRO Publishing (https://www.publish.csiro.au/book/3145/).
See Also
Examples
library(car)
library(dae)
library(dplyr)
library(emmeans)
library(ggplot2)
library(lmerTest)
library(magrittr)
library(predictmeans)
library(supernova)
data(DataExam4.3)
# Pg. 50
fm4.2 <-
aov(
formula = Percent ~ Repl + Contcomp + SeedLot +
Treat/Contcomp + Contcomp /SeedLot +
Treat/ Contcomp/SeedLot
, data = DataExam4.3
)
# Pg. 54
anova(fm4.2)
# Pg. 54
model.tables(x = fm4.2, type = "means")
emmeans(object = fm4.2, specs = ~ Contcomp)
emmeans(object = fm4.2, specs = ~ SeedLot)
emmeans(object = fm4.2, specs = ~ Contcomp + Treat)
emmeans(object = fm4.2, specs = ~ Contcomp + SeedLot)
emmeans(object = fm4.2, specs = ~ Contcomp + Treat + SeedLot)
DataExam4.3 %>%
dplyr::group_by(Treat, Contcomp, SeedLot) %>%
dplyr::summarize(Mean=mean(Percent))
RESFIT <- data.frame(residualvalue=residuals(fm4.2),fittedvalue=fitted.values(fm4.2))
ggplot(mapping = aes(x = fitted.values(fm4.2), y = residuals(fm4.2)))+
geom_point(size = 2)+
labs(
x = "Fitted Values"
, y = "Residuals"
) +
theme_classic()
[Package eda4treeR version 0.6.0 Index]