fat3.crd {ExpDes}

Triple factorial scheme in CRD

Description

fat3.crd Analyses experiments in balanced Completely Randomized Design in triple factorial scheme, considering a fixed model.

Usage

fat3.crd(
  factor1,
  factor2,
  factor3,
  resp,
  quali = c(TRUE, TRUE, TRUE),
  mcomp = "tukey",
  fac.names = c("F1", "F2", "F3"),
  sigT = 0.05,
  sigF = 0.05,
  unfold = NULL
)

Arguments

factor1

Numeric or complex vector containing the factor 1 levels.

factor2

Numeric or complex vector containing the factor 2 levels.

factor3

Numeric or complex vector containing the factor 3 levels.

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'), the Calinski and Corsten test ('ccF') and bootstrap multiple comparison's test ('ccboot').

fac.names

Allows labeling the factors 1, 2 and 3.

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%.

unfold

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 '2.1', '2.2' or '2.3', the double interactions are unfolded; if '3', the triple interaction is unfolded.

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).

Note

The graphics can be used to construct regression plots and plotres for residuals plots.

Author(s)

Eric B Ferreira, [e-mail]

Denismar Alves Nogueira

Portya Piscitelli Cavalcanti

References

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

See Also

fat2.crd, fat2.rbd, fat3.rbd, fat2.ad.crd, fat2.ad.rbd, fat3.ad.crd and fat3.ad.rbd.

Examples

data(ex6)
attach(ex6)
fat3.crd(fatorA, fatorB, fatorC, resp, quali = c(TRUE,
TRUE, TRUE), mcomp = "lsdb", fac.names = c("Factor A",
"Factor B", "Factor C"), sigT = 0.05, sigF = 0.05)