split2.crd
Analyses experiments in Split-plot scheme
in balanced Completely Randomized Design, considering a
fixed model.
split2.crd(
factor1,
factor2,
repet,
resp,
quali = c(TRUE, TRUE),
mcomp = "tukey",
fac.names = c("F1", "F2"),
sigT = 0.05,
sigF = 0.05,
unfold = NULL
)
Numeric or complex vector containing the factor 1 levels.
Numeric or complex vector containing the factor 2 levels.
Numeric or complex vector containing the replications.
Numeric or complex vector containing the response variable.
Logic. If TRUE (default), the treatments are assumed qualitative, if FALSE, quantitatives.
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'), the Calinski and Corsten test ('ccF') and bootstrap multiple comparison's test ('ccboot').
Allows labeling the factors 1 and 2.
The signficance to be used for the multiple comparison test; the default is 5%.
The signficance to be used for the F test of ANOVA; the default is 5%.
Says what must be done after the ANOVA. If NULL (default), recommended tests are performed; if '0', just ANOVA is performed; if '1', the simple effects are tested; if '2', the double interaction is unfolded.
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).
The arguments sigT and mcomp will be used only when the treatment are qualitative.
BANZATTO, D. A.; KRONKA, S. N. Experimentacao Agricola. 4 ed. Jaboticabal: Funep. 2006. 237 p.
split2.rbd
and strip
.
# NOT RUN {
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, unfold=NULL)
# }
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