conjdic: Analysis: Joint analysis of experiments in completely randomized design

Description

Function of the AgroR package for joint analysis of experiments conducted in a completely randomized design with a qualitative or quantitative factor with balanced data.

Usage

conjdic(
  trat,
  repet,
  local,
  response,
  transf = 1,
  constant = 0,
  norm = "sw",
  homog = "bt",
  mcomp = "tukey",
  homog.value = 7,
  quali = TRUE,
  alpha.f = 0.05,
  alpha.t = 0.05,
  grau = NA,
  theme = theme_classic(),
  ylab = "response",
  title = "",
  xlab = "",
  color = "rainbow",
  fill = "lightblue",
  angulo = 0,
  textsize = 12,
  dec = 3,
  family = "sans",
  errorbar = TRUE
)

Value

Returns the assumptions of the analysis of variance, the assumption of the joint analysis by means of a QMres ratio matrix, the analysis of variance, the multiple comparison test or regression.

Arguments

trat: Numerical or complex vector with treatments
repet: Numerical or complex vector with repetitions
local: Numeric or complex vector with locations or times
response: Numerical vector containing the response of the experiment.
transf: Applies data transformation (default is 1; for log consider 0)
constant: Add a constant for transformation (enter value)
norm: Error normality test (default is Shapiro-Wilk)
homog: Homogeneity test of variances (default is Bartlett)
mcomp: Multiple comparison test (Tukey (default), LSD, Scott-Knott and Duncan)
homog.value: Reference value for homogeneity of experiments. By default, this ratio should not be greater than 7
quali: Defines whether the factor is quantitative or qualitative (default is qualitative)
alpha.f: Level of significance of the F test (default is 0.05)
alpha.t: Significance level of the multiple comparison test (default is 0.05)
grau: Degree of polynomial in case of quantitative factor (default is 1)
theme: ggplot2 theme (default is theme_classic())
ylab: Variable response name (Accepts the expression() function)
title: Graph title
xlab: Treatments name (Accepts the expression() function)
color: When the columns are different colors (Set fill-in argument as "trat")
fill: Defines chart color (to generate different colors for different treatments, define fill = "trat")
angulo: x-axis scale text rotation
textsize: Font size
dec: Number of cells
family: Font family
errorbar: Plot the standard deviation bar on the graph (In the case of a segment and column graph) - default is TRUE

Author

Gabriel Danilo Shimizu, shimizu@uel.br

Leandro Simoes Azeredo Goncalves

Rodrigo Yudi Palhaci Marubayashi

References

Ferreira, P. V. Estatistica experimental aplicada a agronomia. Edufal, 2018.

Principles and procedures of statistics a biometrical approach Steel, Torry and Dickey. Third Edition 1997

Multiple comparisons theory and methods. Departament of statistics the Ohio State University. USA, 1996. Jason C. Hsu. Chapman Hall/CRC.

Practical Nonparametrics Statistics. W.J. Conover, 1999

Ramalho M.A.P., Ferreira D.F., Oliveira A.C. 2000. Experimentacao em Genetica e Melhoramento de Plantas. Editora UFLA.

Scott R.J., Knott M. 1974. A cluster analysis method for grouping mans in the analysis of variance. Biometrics, 30, 507-512.

Examples

Run this code

library(AgroR)
data(mirtilo)
with(mirtilo, conjdic(trat, bloco, exp, resp))

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