Exam5.2 {eda4treeR}

Example 5.2 from Experimental Design and Analysis for Tree Improvement

Description

Exam5.2 presents the height of 37 seedlots from 6 sites.

Author(s)

1. Muhammad Yaseen ([e-mail])

2. Sami Ullah ([e-mail])

References

1. 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

DataExam5.2

Examples

library(car)
library(dae)
library(dplyr)
library(emmeans)
library(ggplot2)
library(lmerTest)
library(magrittr)
library(predictmeans)
library(supernova)

data(DataExam5.2)

fm5.7 <- lm(formula = Ht ~ Site*SeedLot, data = DataExam5.2)

# Pg. 77
anova(fm5.7)

fm5.9 <- lm(formula = Ht ~ Site*SeedLot, data = DataExam5.2)
# Pg. 77
anova(fm5.9)

ANOVAfm5.9 <- anova(fm5.9)

ANOVAfm5.9[4, 1:3] <- c(384, 384*964, 964)
ANOVAfm5.9[3, 4]   <- ANOVAfm5.9[3, 3]/ANOVAfm5.9[4, 3]
ANOVAfm5.9[3, 5]   <- pf(
                            q = ANOVAfm5.9[3, 4]
                        , df1 = ANOVAfm5.9[3, 1]
                        , df2 = ANOVAfm5.9[4, 1]
                        , lower.tail = FALSE
                        )
# Pg. 77
ANOVAfm5.9


Tab5.14 <-
  DataExam5.2 %>%
      summarise(Mean = mean(Ht, na.rm = TRUE), .by = SeedLot) %>%
    left_join(
      DataExam5.2 %>%
        nest_by(SeedLot) %>%
        mutate(fm2 = list(lm(Ht ~ SiteMean, data = data))) %>%
        summarise(Slope = coef(fm2)[2])
    , by = "SeedLot"
      )

# Pg. 81
Tab5.14


DevSS2 <-
        DataExam5.2 %>%
        nest_by(SeedLot) %>%
        mutate(fm2 = list(lm(Ht ~ SiteMean, data = data))) %>%
        summarise(SSE = anova(fm2)[2, 2]) %>%
        ungroup() %>%
        summarise(Dev = sum(SSE)) %>%
        as.numeric()


ANOVAfm5.9.1 <-
  rbind(
     ANOVAfm5.9[1:3, ]
   , c(
        ANOVAfm5.9[2, 1]
      , ANOVAfm5.9[3, 2] - DevSS2
      , (ANOVAfm5.9[3, 2] - DevSS2)/ANOVAfm5.9[2, 1]
      , NA
      , NA
      )
   , c(
        ANOVAfm5.9[3, 1]-ANOVAfm5.9[2, 1]
      , DevSS2
      , DevSS2/(ANOVAfm5.9[3, 1]-ANOVAfm5.9[2, 1])
      , DevSS2/(ANOVAfm5.9[3, 1]-ANOVAfm5.9[2, 1])/ANOVAfm5.9[4, 3]
      , pf(
              q = DevSS2/(ANOVAfm5.9[3, 1]-ANOVAfm5.9[2, 1])/ANOVAfm5.9[4, 3]
          , df1 = ANOVAfm5.9[3, 1]-ANOVAfm5.9[2, 1]
          , df2 = ANOVAfm5.9[4, 1]
          , lower.tail = FALSE
          )
      )
   , ANOVAfm5.9[4, ]
  )
rownames(ANOVAfm5.9.1) <-
  c("Site", "SeedLot", "Site:SeedLot", "  regressions", "  deviations", "Residuals")
# Pg. 82
ANOVAfm5.9.1

Code <- c("a","a","a","a","b","b","b","b","c","d","d","d","d","e","f","g",
     "h","h","i","i","j","k","l","m","n","n","n","o","p","p","q","r",
     "s","t","t","u","v")

Tab5.14$Code <- Code

ggplot(data = Tab5.14, mapping = aes(x = Mean, y = Slope))+
 geom_point(size = 2) +
 geom_text(aes(label = Code), hjust = -0.5, vjust = -0.5)+
 theme_bw() +
 labs(
     x = "SeedLot Mean"
   , y = "Regression Coefficient"
   )