Exam3.1: Data for Example 3.1 from Experimental Design and Analysis...

In eda4treeR: Experimental Design and Analysis for Tree Improvement

Data for Example 3.1 from Experimental Design and Analysis for Tree Improvement

Description

Exam3.1 is part of data from Australian Centre for Agricultural Research (ACIAR) in Queensland, Australia (Experiment 309).

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

DataExam3.1

Examples

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

data(DataExam3.1)

# Pg. 28
fmtab3.3 <-
          lm(
              formula = ht ~ repl*seedlot
            , data    = DataExam3.1
            )


fmtab3.3ANOVA1 <-
  anova(fmtab3.3) %>%
  mutate(
  "F value" =
         c(
           anova(fmtab3.3)[1:2, 3]/anova(fmtab3.3)[3, 3]
         , anova(fmtab3.3)[3, 4]
         , NA
         )
          )

 # Pg. 33 (Table 3.3)
fmtab3.3ANOVA1 %>%
  mutate(
  "Pr(>F)"  =
       c(
         NA
       , pf(
            q   = fmtab3.3ANOVA1[2, 4]
          , df1 = fmtab3.3ANOVA1[2, 1]
          , df2 = fmtab3.3ANOVA1[3, 1], lower.tail = FALSE
          )
       , NA
       , NA
       )
       )

 # Pg. 33  (Table 3.3)
 emmeans(object  = fmtab3.3, specs = ~ seedlot)

 # Pg. 34  (Figure 3.2)
 ggplot(
    mapping = aes(
                  x = fitted.values(fmtab3.3)
                , y = residuals(fmtab3.3)
                )
                ) +
 geom_point(size = 2) +
 labs(
    x = "Fitted Values"
  , y = "Residual"
   ) +
 theme_classic()


# Pg. 33 (Table 3.4)
DataExam3.1m <- DataExam3.1
DataExam3.1m[c(28, 51, 76), 5] <- NA
DataExam3.1m[c(28, 51, 76), 6] <- NA


fmtab3.4 <-
          lm(
              formula   = ht ~ repl*seedlot
            , data      = DataExam3.1m
            )

fmtab3.4ANOVA1 <-
  anova(fmtab3.4) %>%
  mutate(
      "F value" =
            c(
               anova(fmtab3.4)[1:2, 3]/anova(fmtab3.4)[3, 3]
             , anova(fmtab3.4)[3, 4]
             , NA
             )
             )

# Pg. 33 (Table 3.4)
fmtab3.4ANOVA1 %>%
  mutate(
  "Pr(>F)"  =
       c(
         NA
       , pf(
            q   = fmtab3.4ANOVA1[2, 4]
          , df1 = fmtab3.4ANOVA1[2, 1]
          , df2 = fmtab3.4ANOVA1[3, 1], lower.tail = FALSE
          )
       , NA
       , NA
       )
       )

 # Pg. 33  (Table 3.4)
 emmeans(object  = fmtab3.4, specs = ~ seedlot)

eda4treeR documentation built on Sept. 14, 2024, 1:08 a.m.