snk.test
From GAD v1.1.1
by Leonardo SandriniNeto
StudentNewmanKeuls (SNK) procedure
This function perforns a SNK posthoc test of means on the factors of a chosen term of the model, comparing among levels of one factor within each level of other factor or combination of factors.
 Keywords
 htest
Usage
snk.test(object, term, among = NULL, within = NULL)
Arguments
 object
 An object of class lm, containing the specified design.
 term
 Term of the model to be analysed. Use
estimates
to see the right form to inform it.  among
 Specifies the factor which levels will be compared among. Need to be specified if the term to be analysed envolves more than one factor.
 within
 Specifies the factor or combination of factors that will be compared within level among.
Details
SNK is a stepwise procedure for hypothesis testing. First the sample means are sorted, then the pairwise studentized range (q) is calculated by dividing the differences between means by the standard error, which is based upon the average variance of the two sample.
Value

A list containing the standard error, the degree of freedom and pairwise comparisons among levels of one factor within each level of other(s) factor(s).
References
Underwood, A.J. 1997. Experiments in Ecology: Their Logical Design and Interpretation Using Analysis of Variance. Cambridge University Press, Cambridge.
See Also
Examples
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)
##Check estimates to see model structure
estimates(model)
snk.test(model,term = 'CG:MQ', among = 'MQ', within = 'CG')
##
##
##Example using snails dataset
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)
##Check estimates to see model structure
estimates(model)
snk.test(model, term = 'O')
snk.test(model,term = 'O:S', among = 'S', within = 'O')
#if term O:S:B were significant, we could try
snk.test(model, term = 'O:S:B', among = 'B', within = 'O:S')
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