easyanova (version 1.1)

ea5: Analysis of variance in factorial in split.plot designs (mixed model)

Description

Perform analysis of variance and other important complementary analyzes in factorial in split.plot scheme, with balanced and unbalanced data.

Usage

ea5(data, cov, design)

Arguments

data

data is a data.frame

data frame with five columns, factor 1 (plot 1), factor 2 (plot 2), factor 3 (split.plot), repetitions or blocks, and response (split.plot in randomizad design or block design)

cov

Evaluated Structures

1 = Autoregressive

2 = Heterogenius Autoregressive

3 = Continuous Autoregressive Process

4 = Compound Symetry

5 = Unstructured

design

Design

1 = completely randomized design

2 = randomized block design

Value

• Returns analysis of variance, parameters of model fitting, normality test, means (adjusted means), multiple comparisons tests.

Details

The response variable must be numeric. Other variables can be numeric or factors.

References

SAMPAIO, I. B. M. Estatistica aplicada a experimentacao animal. 3nd Edition. Belo Horizonte: Editora FEPMVZ, Fundacao de Ensino e Pesquisa em Medicina Veterinaria e Zootecnia, 2010. 264p.

See Also

ea1, ea2, ea3, ea4, ea6, ea7, ea8, lme, glht

Examples

# Sampaio (2010)
data(data9)

# analysis in completely randomized design (Autoregressive)
r1<-ea5(data9,1,1)

names(r1)

r1