STRIPLOT.RdAnalysis of an experiment conducted in a block randomized design in a strit-plot scheme using fixed effects analysis of variance.
STRIPLOT(
f1,
f2,
block,
response,
norm = "sw",
alpha.f = 0.05,
transf = 1,
textsize = 12,
labelsize = 4,
constant = 0
)Numeric or complex vector with plot levels
Numeric or complex vector with subplot levels
Numeric or complex vector with blocks
Numeric vector with responses
Error normality test (default is Shapiro-Wilk)
Level of significance of the F test (default is 0.05)
Applies data transformation (default is 1; for log consider 0)
Font size (default is 12)
Label size (default is 4)
Add a constant for transformation (enter value)
The table of analysis of variance, the test of normality of errors (Shapiro-Wilk, Lilliefors, Anderson-Darling, Cramer-von Mises, Pearson and Shapiro-Francia), the test of homogeneity of variances (Bartlett). The function also returns a standardized residual plot.
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.
#===================================
# Example tomate
#===================================
# Obs. Consider that the "tomato" experiment is a block randomized design in strip-plot.
library(AgroR)
data(tomate)
with(tomate, STRIPLOT(parc, subp, bloco, resp))
#>
#> -----------------------------------------------------------------
#> Normality of errors
#> -----------------------------------------------------------------
#> Method Statistic p.value
#> Shapiro-Wilk normality test(W) 0.9851279 0.3522956
#>
#> As the calculated p-value is greater than the 5% significance level, hypothesis H0 is not rejected. Therefore, errors can be considered normal
#>
#>
#> -----------------------------------------------------------------
#> Homogeneity of Variances
#> -----------------------------------------------------------------
#> Interaction
#> Method Statistic p.value
#> Bartlett test(Bartlett's K-squared) 37.60184 0.0280913
#>
#> As the calculated p-value is less than the 5% significance level, H0 is rejected. Therefore, the variances are not homogeneous
#>
#> -----------------------------------------------------------------
#> Additional Information
#> -----------------------------------------------------------------
#>
#> CV1 (%) = 8.64
#> CV2 (%) = 4.78
#> CV3 (%) = 6.36
#> Mean = 0.2433
#> Median = 0.2402
#>
#>
#> -----------------------------------------------------------------
#> Analysis of Variance
#> -----------------------------------------------------------------
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Block 1 0.0010326353 0.0010326353 3.056282 0.140844575
#> F1 5 0.0127791593 0.0025558319 5.781571 0.038403336
#> Error A 5 0.0022103264 0.0004420653
#> F2 3 0.0333335724 0.0111111908 81.994663 0.002237162
#> Error B 3 0.0004065334 0.0001355111
#> F1:F2 15 0.0040128492 0.0002675233 1.116060 0.361356071
#> Residuals 63 0.0151013155 0.0002397034
#>
#>
#> Your analysis is not valid, suggests using a try to transform the data
#>