gad {GAD}

General analysis of variance design

Description

Fits a general ANOVA design with any combination of orthogonal/nested and fixed/random factors through function estimates.

Usage

gad(object, quasi.f = FALSE)

Arguments

object

an object of class lm, containing the specified design with random and/or fixed factors.

quasi.f

logical, indicating whether to use quasi F-ratio when there is no single error term appropriate in the analysis. Default to FALSE.

Details

Function gad returns an analysis of variance table using estimates to identify the appropriate F-ratios and consequently p-values for any complex model of orthogonal or nested, fixed or random factors as described by Underwood(1997).

Value

A "list" containing an object of class "anova" inheriting from class "data.frame".

Author(s)

Leonardo Sandrini-Neto ([e-mail])

References

Underwood, A.J. 1997. Experiments in Ecology: Their Logical Design and Interpretation Using Analysis of Variance. Cambridge University Press, Cambridge.

See Also

estimates

Examples

# Example 1
library(GAD)
data(rohlf95)
CG <- as.fixed(rohlf95$cages)
MQ <- as.random(rohlf95$mosquito)
model <- lm(wing ~ CG + MQ%in%CG, data = rohlf95)
model.tab <- gad(model)
model.tab

# Example 2
data(rats)
TR <- as.fixed(rats$treat)
RA <- as.random(rats$rat)
LI <- as.random(rats$liver)
model2 <- lm(glycog ~ TR + RA%in%TR + LI%in%RA%in%TR, data = rats)
model2.tab <- gad(model2)
model2.tab

# Example 3
data(snails)
O <- as.random(snails$origin)
S <- as.random(snails$shore)
B <- as.random(snails$boulder)
C <- as.random(snails$cage)
model3 <- lm(growth ~ O + S + O*S + B%in%S + O*(B%in%S) + C%in%(O*(B%in%S)), data = snails)
model3.tab <- gad(model3)
model3.tab # 'no test' for shore
model3.tab2 <- gad(model3, quasi.f = TRUE)
model3.tab2 # suitable test for shore