Exam3.1.1 is part of data from Australian Centre for Agricultural Research (ACIAR) in Queensland, Australia (Experiment 309).

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

Author

  1. Muhammad Yaseen (myaseen208@gmail.com)

  2. Sami Ullah (samiullahuos@gmail.com)

Examples

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

data(DataExam3.1.1)

# Pg. 36
fm3.8 <- lm(formula  = Mean ~ Repl + SeedLot, data = DataExam3.1.1)

# Pg. 40
anova(fm3.8)
#> Analysis of Variance Table
#> 
#> Response: Mean
#>           Df Sum Sq Mean Sq F value   Pr(>F)   
#> Repl       1  2.538  2.5376  3.4197 0.138108   
#> SeedLot    4 63.234 15.8084 21.3035 0.005851 **
#> Residuals  4  2.968  0.7421                    
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

# Pg. 40
emmeans(object = fm3.8, specs = ~ SeedLot)
#>  SeedLot      emmean    SE df lower.CL upper.CL
#>  Acacia        10.29 0.609  4     8.60    11.98
#>  Angophora      7.10 0.609  4     5.41     8.79
#>  Casuarina      5.51 0.609  4     3.82     7.20
#>  Melaleuca      4.94 0.609  4     3.25     6.63
#>  Petalostigma   2.73 0.609  4     1.04     4.42
#> 
#> Results are averaged over the levels of: Repl 
#> Confidence level used: 0.95 
emmip(object = fm3.8, formula  = ~ SeedLot) +
 theme_classic()