easyanova (version 1.1)

ea2: Analysis of variance in double factorial designs

Description

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

Usage

ea2(data)

Arguments

data

data is a data.frame

data frame with three columns, factor 1, factor 2 and response (factorial in completely randomized design)

data frame with four columns, factor1, factor 2, blocks and response (factorial in randomized block design)

data frame with

Value

• Returns analysis of variance, normality test, test of homogeneity of variance, coefficient of variation, means (adjusted means), multiple comparisons tests.

Details

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

References

KAPS, M. and LAMBERSON, W. R. Biostatistics for Animal Science: an introductory text. 2nd Edition. CABI Publishing, Wallingford, Oxfordshire, UK, 2009. 504p.

PIMENTEL-GOMES, F. and GARCIA C.H. Estatistica aplicada a experimentos agronomicos e florestais: exposicao com exemplos e orientacoes para uso de aplicativos. Editora Fealq, v.11, 2002. 309p.

See Also

ea1, ea3, ea4, ea5, ea6, ea7, ea8, lme, glht

Examples

# Kaps and Lamberson (2009)
data(data5)

# analysis in completely randomized design
r1<-ea2(data5)

names(r1)

r1["Multiple comparison test (factor 1)"]

r1[10]

r1[c(7,8,9)]

r1

# Pimentel Gomes and Garcia (2002)
data(data6)

# analysis in randomized block design
r2<-ea2(data6)

r2

r1[1];r2[1]