#===============================================================================
#. Título: Análise de variância experimentos
#. Curso : CET076 - Metodologia e Estatística Experimental - Agronomia
# Autor : José Cláudio Faria
# Data  : 19/10/2022 22:39:57
#===============================================================================
# Objetivos
#===============================================================================
# - Exemplificar, através do R, as análises e determinações numéricas do curso
#   de MEE, referentes a análise de variância via pacote: easyanova
#===============================================================================

#. Package [easyanova]: Analysis of variance in simple designs
require(easyanova)

# Kaps and Lamberson(2009)
data(data1)
data(data2)
data(data3)
data(data4)

#. Analysis in completely randomized design - DIC
an_1 <- ea1(data1,
            design=1)
names(an_1)
an_1
an_1[1]
an_1$Means$snk

#. Analysis in randomized block design - DBC
an_2 <- ea1(data2,
            design=2)
an_2
an_2[1]

#. Analysis in latin square design - DQL
an_3 <- ea1(data3,
            design=3)
an_3
an_3[1]

#. Analysis in several latin squares design
an_4 <- ea1(data4,
            design=4)
an_4
an_4[1]

#. Analysis in unbalanced randomized block design
response <- ifelse(data2$Gain>850,
                   NA,
                   data2$Gain)

ndata <- data.frame(data2[-3],
                    response)
ndata

an_5 <- ea1(ndata,
            design=2 )
an_5

#. Multivariable response (list argument = TRUE)
tt <- c('a', 'a', 'a', 'b', 'b', 'b', 'c', 'c', 'c')
r1 <- c(10, 12, 12.8, 4, 6, 8, 14, 15, 16)
r2 <- c(102, 105, 106, 125, 123, 124, 99, 95, 96)
r3 <- c(560, 589, 590, 658, 678, 629, 369, 389, 378)

nd <- data.frame(tt, r1, r2, r3)

results <- ea1(nd,
               design=1,
               list=TRUE)
names(results)
results

results[1][[1]]

names(results[1][[1]])

#. Analysis with a covariate
# Kaps and Lamberson (2009)
data(data10)

#.. Analysis in completely randomized design
an_6 <- ea1(data10[-3],
            design=5)
an_6

#.. Incomplete blocks type I and II
# Pimentel Gomes and Garcia (2002)
data(data11)
data(data12)

an_7 <- ea1(data11,
            design=7)
an_7

an_8 <- ea1(data12,
            design=7)
an_8

#.. Incomplete blocks type III or augmented blocks
# Cruz and Carneiro (2006)
data(data13)

an_9 <- ea1(data13,
           design=8)
an_9

#.. incomplete blocks type III in animal experiments
# Sampaio (2010)
data(data14)

an_10 <- ea1(data14,
            design=9)
an_10

# lattice 
# Pimentel Gomes and Garcia (2002)
data(data15)

an_11 <- ea1(data15,
            design=10) # intra-block analysis
an_11

an_12 <- ea1(data15,
            design=11) # inter-block analysis
an_12

#.. switchback design
# Sampaio (2010)
data(data16)
an_13 <- ea1(data16,
            design=12)
an_13

#.. switchback design in blocks
# Sanders and Gaynor (1987)
data(data17)
an_14 <- ea1(data17,
            design=13)
an_14

#. Kruskal-Wallis Rank Sum Test
an_15 <- ea1(data1,
            design=14)
an_15

#. Friedman Rank Sum Test
an_16 <- ea1(data2,
            design=15)
an_16