Split-plots in CRD

Description

Analyses experiments in Split-plot scheme in balanced Completely Randomized Design, considering a fixed model.

Usage

1
split2.crd(factor1, factor2, repet, resp, quali = c(TRUE, TRUE), mcomp = "tukey", fac.names = c("F1", "F2"), sigT = 0.05, sigF = 0.05)

Arguments

factor1

Numeric or complex vector containing the factor 1 levels.

factor2

Numeric or complex vector containing the factor 2 levels.

repet

Numeric or complex vector containing the replications.

resp

Numeric or complex vector containing the response variable.

quali

Logic. If TRUE (default), the treatments are assumed qualitative, if FALSE, quantitatives.

mcomp

Allows choosing the multiple comparison test; the default is the test of Tukey, however, the options are: the LSD test ('lsd'), the LSD test with Bonferroni protection ('lsdb'), the test of Duncan ('duncan'), the test of Student-Newman-Keuls ('snk'), the test of Scott-Knott ('sk') and bootstrap multiple comparison's test ('ccboot').

fac.names

Allows labeling the factors 1 and 2.

sigT

The signficance to be used for the multiple comparison test; the default is 5%.

sigF

The signficance to be used for the F test of ANOVA; the default is 5%.

Details

The arguments sigT and mcomp will be used only when the treatment are qualitative.

Value

The output contains the ANOVA of the referred CRD, the Shapiro-Wilk normality test for the residuals of the model, the fitted regression models (when the treatments are quantitative) and/or the multiple comparison tests (when the treatments are qualitative).

Author(s)

Denismar Alves Nogueira

Eric Batista Ferreira

Portya Piscitelli Cavalcanti

References

BANZATTO, D. A.; KRONKA, S. N. Experimentacao Agricola. 4 ed. Jaboticabal: Funep. 2006. 237 p.

Examples

1
2
3
data(ex9)
attach(ex9)
split2.crd(cobertura, prof, rep, pH, quali = c(TRUE, TRUE), mcomp = "lsd", fac.names = c("Cover", "Depth"), sigT = 0.05, sigF = 0.05)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.