parsons at uoguelph.ca wrote:> Hello all,
>
> I am low down on the learning curve of R but so far I have had little
> trouble using most of the packages. However, recently I have run into
> a wall when it comes to bootstrapping a Levene's test (from the car
> package) and thought you might be able to help. I have not been able
> to find R examples for the "boot" package where the test
statistic
> specifically uses a grouping variable (or at least a simple example
> with this condition). I would like to do a non-parametric bootstrap
> to eventually get 95% confidence intervals using the boot.ci command.
> I have included the coding I have tried on a simple data set below. If
> anyone could provide some help, specifically with regards to how the
> "statistic" arguement should be set up in the boot package, it
would
> be greatly appreciated.
>
>> library(boot)
>> library(car)
>> data<-c(2,45,555,1,77,1,2,1,2,1)
>> group<-c(1,1,1,1,1,2,2,2,2,2)
>> levene.test(data,group)
> Levene's Test for Homogeneity of Variance
> Df F value Pr(>F)
> group 1 1.6929 0.2294
> 8
>> stat<-function(a){levene.test(a,group)}
>> trial1<-boot(data,statistic,100)
> Error in statistic(data, original, ...) : unused argument(s) ( ...)
One problem is that levene.test() returns an ANOVA table, which is not
a statistic. Looking inside levene.test() to see what might be used as
a statistic, for the two-group case it seems like you could do something
like this:
library(boot)
library(car)
set.seed(671969)
df <- data.frame(Y = c(rnorm(100,0,1), rnorm(100,0,1)),
G = rep(c(1,2), each = 100))
boot.levene <- function(data,indices){
levene.diff <- diff(tapply(df$Y[indices],
list(df$G[indices]), mad))
return(levene.diff)
}
first.try <- boot(df, boot.levene, 1000)
first.try
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = df, statistic = boot.levene, R = 1000)
Bootstrap Statistics :
original bias std. error
t1* -0.1944924 0.02439172 0.1753512
boot.ci(first.try, index=1, type="bca")
BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS
Based on 1000 bootstrap replicates
CALL :
boot.ci(boot.out = first.try, type = "bca", index = 1)
Intervals :
Level BCa
95% (-0.5772, 0.1159 )
Calculations and Intervals on Original Scale
> Best regards,
> Kevin
>
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http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Chuck Cleland, Ph.D.
NDRI, Inc.
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