GAD (version 1.1.1)

gad: General ANOVA Design

Description

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

Usage

gad(object)

Arguments

object

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

Value

Details

Function gad returns an analysis of variance table using the estimates function 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).

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 + CG%in%MQ, data = rohlf95)
gad(model)
##
##
#Example 2
data(rats)
names(rats)
TR <- as.fixed(rats$treat)
RA <- as.random(rats$rat)
LI <- as.random(rats$liver)
model <- lm(glycog ~ TR + RA%in%TR + LI%in%RA%in%TR, data=rats)
gad(model)
##
##
#Example 3
data(snails)
O <- as.random(snails$origin)
S <- as.random(snails$shore)
B <- as.random(snails$boulder)
C <- as.random(snails$cage)
model <- lm(growth ~ O + S + O*S + B%in%S + O*(B%in%S) + C%in%(O*(B%in%S)), 
            data = snails)
gad(model)