ANOVA for heteroscedastic data
Univariate ANOVA for heteroscedastic data.
fanova.hetero(object = NULL, formula, pr = FALSE, contrast = NULL, ...)
object |
A data frame with dimension ( |
formula |
as formula. |
pr |
If TRUE, print intermediate results. |
contrast |
List of special contrast to be used, by default no special
contrasts are used ( |
... |
Further arguments passed to or from other methods. |
This function fits a univariate analysis of variance model and allows
calculate special contrasts defined by the user. The list of special
contrast to be used for some of the factors in the formula. Each matrix of
the list has r rows and r-1 columns.
The user can also request special predetermined contrasts, for example using
contr.helmert, contr.sum or
contr.treatment functions.
Return:
ans A list with components including: the Beta estimation Est,
the factor degrees of freedom df1, the residual degrees of freedom
df2 and p-value for each factor.
contrast List of special contrasts.
anova.hetero deprecated
It only works with categorical variables.
Manuel Febrero-Bande, Manuel Oviedo de la Fuente manuel.oviedo@usc.es
Brunner, E., Dette, H., Munk, A. Box-Type Approximations in Nonparametric Factorial Designs. Journal of the American Statistical Association, Vol. 92, No. 440 (Dec., 1997), pp. 1494-1502.
See Also as: fanova.RPm
## Not run:
data(phoneme)
ind=1 # beetwen 1:150
fdataobj=data.frame(phoneme$learn[["data"]][,ind])
n=dim(fdataobj)[1]
group<-factor(phoneme$classlearn)
#ex 1: real factor and random factor
group.rand=as.factor(sample(rep(1:3,n),n))
f=data.frame(group,group.rand)
mm=data.frame(fdataobj,f)
colnames(mm)=c("value","group","group.rand")
out1=fanova.hetero(object=mm[,-2],value~group.rand,pr=FALSE)
out2=fanova.hetero(object=mm[,-3],value~group,pr=FALSE)
out1
out2
#ex 2: real factor, random factor and special contrasts
cr5=contr.sum(5) #each level vs last level
cr3=c(1,0,-1) #first level vs last level
out.contrast=fanova.hetero(object=mm[,-3],value~group,pr=FALSE,
contrast=list(group=cr5))
out.contrast
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