varin sacha
2014-Dec-21 20:02 UTC
[R] Bca confidence intervals for Pearson coefficient, thanks.
Dear Professor FOX, I really thank you lots for all your precisions.?One last precision, now if I want tot calculate the BCa bootstrap CIs for the Cramer's V and the Eta-squared. ## Read in the data file, using headers and Tab separator> test = read.table(file.choose(), header = TRUE, sep = "\t") ## Check the variable names> names(test)[1] "gender"? ? "option"? ? "math.test" "geo.test"? "shopping"? "sports"? ? ## Cramer's V> library(questionr)> tab = table(test$gender, test$option)> cramer.v(tab) ? ? ? ? ? ? ? ? ? ? ? ??[1] 0.1490712 ? ? ? ? ? ? ? ? ? ? ? ? ??## Eta.square> library(lsr)> test.aov = aov(math.test ~ gender, data = test) > etaSquared(test.aov)? ? ? ? ? eta.sq eta.sq.partgender 0.1207154 ? 0.1207154Best Regards, looking forward to reading you once more, Sacha De?: John Fox <jfox at mcmaster.ca> ??: varin sacha <varinsacha at yahoo.fr> Cc?: r-help help <r-help at r-project.org> Envoy? le : Dimanche 21 d?cembre 2014 5h33 Objet?: Re: [R] Bca confidence intervals for Pearson coefficient, thanks. Dear varin sacha, I think that you misunderstand how boot() and boot.ci() work. The boot() function in the simplest case takes two arguments, for the data and indices into the data, while boot.ci() takes as its principal argument the object returned by boot(). All of this seems reasonably clear in ?boot and ?boot.ci. Here's an example with different data (since as far as I can see you didn't supply yours): ------------- snip --------> library(boot) > > x <- longley$Year > y <- longley$Population > > cor(cbind(x, y))? ? ? ? ? x? ? ? ? y x 1.0000000 0.9939528 y 0.9939528 1.0000000> > myCor <- function(data, index){+? cor(data[index, ])[1, 2] + }> > set.seed(12345) > (b <- boot(data=cbind(x, y), statistic=myCor, R=200))ORDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = cbind(x, y), statistic = myCor, R = 200) Bootstrap Statistics : ? ? original? ? ? bias? ? std. error t1* 0.9939528 0.0008263766 0.001850004> boot.ci(b, type="bca")BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS Based on 200 bootstrap replicates CALL : boot.ci(boot.out = b, type = "bca") Intervals : Level? ? ? BCa? ? ? ? ? 95%? ( 0.9895,? 0.9969 )? Calculations and Intervals on Original Scale Warning : BCa Intervals used Extreme Quantiles Some BCa intervals may be unstable Warning message: In norm.inter(t, adj.alpha) : extreme order statistics used as endpoints --------------- snip --------------- Note that 200 bootstrap replications are generally sufficient for bootstrap standard errors (a normal-theory CI would be a poor choice here, unless you transform the correlation coefficient), but really aren't enough for a BCa interval. I hope this helps, John ------------------------------------------------ John Fox, Professor McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/ ??? On Sat, 20 Dec 2014 20:36:57 +0000 (UTC)> Hi to everyone, > I am trying to calculate the Bca bootstrap confidence intervals for the Pearson coefficient. > x=Dataset$math.testy=Dataset$geo.testcor(x,y,method="pearson")[1] 0.6983799 > boot.ci(cor, conf=0.95, type=bca)Erreur dans boot.out$t0 : objet de type 'closure' non indi?able > > I have tried as well to calculate the Pearson coefficient using bootstrap and then to calculate the Bca bootstrap CIs of the Pearson. It doesn't work either.? > boot(data = cbind(x, y), statistic = cor, R = 200) > > ORDINARY NONPARAMETRIC BOOTSTRAP > > > Call: > boot(data = cbind(x, y), statistic = cor, R = 200) > > > Bootstrap Statistics : >? ? ? original? ? bias? ? std. error > t1* -0.6243713 0.6295142? 0.2506267 > t2* -0.1366533 0.1565392? 0.2579134 > > boot.ci(cor, conf=0.95, type=bca) > Erreur dans boot.out$t0 : objet de type 'closure' non indi?able > Many thanks to tell me how to correct my R script to get the Bca CIs for my Pearson coefficient. Best regards, looking forward to reading you, > SV > > ??? [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.??? ??? [[alternative HTML version deleted]]
John Fox
2014-Dec-21 21:22 UTC
[R] Bca confidence intervals for Pearson coefficient, thanks.
Dear Sacha, Simply write a function that takes a data set and index vector as arguments, say statistic(data, index), and have it compute and return either eta^2 or V depending upon the application. Use the function myCor() in the previous example as a model. Best, John> -----Original Message----- > From: varin sacha [mailto:varinsacha at yahoo.fr] > Sent: Sunday, December 21, 2014 3:03 PM > To: John Fox > Cc: r-help help > Subject: Re: [R] Bca confidence intervals for Pearson coefficient, > thanks. > > Dear Professor FOX, > > > I really thank you lots for all your precisions. > One last precision, now if I want tot calculate the BCa bootstrap CIs > for the Cramer's V and the Eta-squared. > > > ## Read in the data file, using headers and Tab separator > > test = read.table(file.choose(), header = TRUE, sep = "\t") > > > ## Check the variable names > > names(test) > [1] "gender" "option" "math.test" "geo.test" "shopping" "sports" > > > ## Cramer's V > > > library(questionr) > > tab = table(test$gender, test$option) > > cramer.v(tab) > [1] 0.1490712 > > ## Eta.square > > > library(lsr) > > test.aov = aov(math.test ~ gender, data = test) > > > etaSquared(test.aov) > eta.sq eta.sq.part > gender 0.1207154 0.1207154 > > > > Best Regards, looking forward to reading you once more, > > Sacha > > ________________________________ > > De : John Fox <jfox at mcmaster.ca> > ? : varin sacha <varinsacha at yahoo.fr> > Cc : r-help help <r-help at r-project.org> > Envoy? le : Dimanche 21 d?cembre 2014 5h33 > Objet : Re: [R] Bca confidence intervals for Pearson coefficient, > thanks. > > > Dear varin sacha, > > I think that you misunderstand how boot() and boot.ci() work. The boot() > function in the simplest case takes two arguments, for the data and > indices into the data, while boot.ci() takes as its principal argument > the object returned by boot(). All of this seems reasonably clear in > ?boot and ?boot.ci. > > Here's an example with different data (since as far as I can see you > didn't supply yours): > > ------------- snip -------- > > > library(boot) > > > > x <- longley$Year > > y <- longley$Population > > > > cor(cbind(x, y)) > x y > x 1.0000000 0.9939528 > y 0.9939528 1.0000000 > > > > myCor <- function(data, index){ > + cor(data[index, ])[1, 2] > + } > > > > set.seed(12345) > > (b <- boot(data=cbind(x, y), statistic=myCor, R=200)) > > ORDINARY NONPARAMETRIC BOOTSTRAP > > > Call: > boot(data = cbind(x, y), statistic = myCor, R = 200) > > > Bootstrap Statistics : > original bias std. error > t1* 0.9939528 0.0008263766 0.001850004 > > > boot.ci(b, type="bca") > BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS > Based on 200 bootstrap replicates > > CALL : > boot.ci(boot.out = b, type = "bca") > > Intervals : > Level BCa > 95% ( 0.9895, 0.9969 ) > Calculations and Intervals on Original Scale > Warning : BCa Intervals used Extreme Quantiles > Some BCa intervals may be unstable > Warning message: > In norm.inter(t, adj.alpha) : extreme order statistics used as endpoints > > --------------- snip --------------- > > Note that 200 bootstrap replications are generally sufficient for > bootstrap standard errors (a normal-theory CI would be a poor choice > here, unless you transform the correlation coefficient), but really > aren't enough for a BCa interval. > > I hope this helps, > John > > > > > ------------------------------------------------ > John Fox, Professor > McMaster University > Hamilton, Ontario, Canada > http://socserv.mcmaster.ca/jfox/ > > On Sat, 20 Dec 2014 20:36:57 +0000 (UTC) > varin sacha <varinsacha at yahoo.fr> wrote: > > Hi to everyone, > > I am trying to calculate the Bca bootstrap confidence intervals for > the Pearson coefficient. > > x=Dataset$math.testy=Dataset$geo.testcor(x,y,method="pearson")[1] > 0.6983799 > > boot.ci(cor, conf=0.95, type=bca)Erreur dans boot.out$t0 : objet de > type 'closure' non indi?able > > > > I have tried as well to calculate the Pearson coefficient using > bootstrap and then to calculate the Bca bootstrap CIs of the Pearson. It > doesn't work either. > > boot(data = cbind(x, y), statistic = cor, R = 200) > > > > ORDINARY NONPARAMETRIC BOOTSTRAP > > > > > > Call: > > boot(data = cbind(x, y), statistic = cor, R = 200) > > > > > > Bootstrap Statistics : > > original bias std. error > > t1* -0.6243713 0.6295142 0.2506267 > > t2* -0.1366533 0.1565392 0.2579134 > > > boot.ci(cor, conf=0.95, type=bca) > > Erreur dans boot.out$t0 : objet de type 'closure' non indi?able > > Many thanks to tell me how to correct my R script to get the Bca CIs > for my Pearson coefficient. Best regards, looking forward to reading > you, > > SV > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > > >
varin sacha
2014-Dec-23 22:59 UTC
[R] Bca confidence intervals for Pearson coefficient, thanks.
Dear Professor Fox,
Once more I really thank you lots for your response. I will try it.
Best regards, and Merry Christmas to you.
SV
De?: John Fox <jfox at mcmaster.ca>
??: 'varin sacha' <varinsacha at yahoo.fr>
Cc?: 'r-help help' <r-help at r-project.org>
Envoy? le : Dimanche 21 d?cembre 2014 22h22
Objet?: RE: [R] Bca confidence intervals for Pearson coefficient, thanks.
Dear Sacha,
Simply write a function that takes a data set and index vector as arguments, say
statistic(data, index), and have it compute and return either eta^2 or V
depending upon the application. Use the function myCor() in the previous example
as a model.
Best,
John
> -----Original Message-----
> From: varin sacha [mailto:varinsacha at yahoo.fr]
> Sent: Sunday, December 21, 2014 3:03 PM
> To: John Fox
> Cc: r-help help
> Subject: Re: [R] Bca confidence intervals for Pearson coefficient,
> thanks.
>
> Dear Professor FOX,
>
>
> I really thank you lots for all your precisions.
> One last precision, now if I want tot calculate the BCa bootstrap CIs
> for the Cramer's V and the Eta-squared.
>
>
> ## Read in the data file, using headers and Tab separator
> > test = read.table(file.choose(), header = TRUE, sep = "\t")
>
>
> ## Check the variable names
> > names(test)
> [1] "gender"? ? "option"? ? "math.test"
"geo.test"? "shopping"? "sports"
>
>
> ## Cramer's V
>
> > library(questionr)
> > tab = table(test$gender, test$option)
> > cramer.v(tab)
> [1] 0.1490712
>
> ## Eta.square
>
> > library(lsr)
> > test.aov = aov(math.test ~ gender, data = test)
>
> > etaSquared(test.aov)
>? ? ? ? ? eta.sq eta.sq.part
> gender 0.1207154? 0.1207154
>
>
>
> Best Regards, looking forward to reading you once more,
>
> Sacha
>
> ________________________________
>
> De : John Fox <jfox at mcmaster.ca>
> ? : varin sacha <varinsacha at yahoo.fr>
> Cc : r-help help <r-help at r-project.org>
> Envoy? le : Dimanche 21 d?cembre 2014 5h33
> Objet : Re: [R] Bca confidence intervals for Pearson coefficient,
> thanks.
>
>
> Dear varin sacha,
>
> I think that you misunderstand how boot() and boot.ci() work. The boot()
> function in the simplest case takes two arguments, for the data and
> indices into the data, while boot.ci() takes as its principal argument
> the object returned by boot(). All of this seems reasonably clear in
> ?boot and ?boot.ci.
>
> Here's an example with different data (since as far as I can see you
> didn't supply yours):
>
> ------------- snip --------
>
> > library(boot)
> >
> > x <- longley$Year
> > y <- longley$Population
> >
> > cor(cbind(x, y))
>? ? ? ? ? x? ? ? ? y
> x 1.0000000 0.9939528
> y 0.9939528 1.0000000
> >
> > myCor <- function(data, index){
> +? cor(data[index, ])[1, 2]
> + }
> >
> > set.seed(12345)
> > (b <- boot(data=cbind(x, y), statistic=myCor, R=200))
>
> ORDINARY NONPARAMETRIC BOOTSTRAP
>
>
> Call:
> boot(data = cbind(x, y), statistic = myCor, R = 200)
>
>
> Bootstrap Statistics :
>? ? original? ? ? bias? ? std. error
> t1* 0.9939528 0.0008263766 0.001850004
>
> > boot.ci(b, type="bca")
> BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS
> Based on 200 bootstrap replicates
>
> CALL :
> boot.ci(boot.out = b, type = "bca")
>
> Intervals :
> Level? ? ? BCa
> 95%? ( 0.9895,? 0.9969 )
> Calculations and Intervals on Original Scale
> Warning : BCa Intervals used Extreme Quantiles
> Some BCa intervals may be unstable
> Warning message:
> In norm.inter(t, adj.alpha) : extreme order statistics used as endpoints
>
> --------------- snip ---------------
>
> Note that 200 bootstrap replications are generally sufficient for
> bootstrap standard errors (a normal-theory CI would be a poor choice
> here, unless you transform the correlation coefficient), but really
> aren't enough for a BCa interval.
>
> I hope this helps,
> John
>
>
>
>
> ------------------------------------------------
> John Fox, Professor
> McMaster University
> Hamilton, Ontario, Canada
> http://socserv.mcmaster.ca/jfox/
>
> On Sat, 20 Dec 2014 20:36:57 +0000 (UTC)
> varin sacha <varinsacha at yahoo.fr> wrote:
> > Hi to everyone,
> > I am trying to calculate the Bca bootstrap confidence intervals for
> the Pearson coefficient.
> >
x=Dataset$math.testy=Dataset$geo.testcor(x,y,method="pearson")[1]
> 0.6983799
> > boot.ci(cor, conf=0.95, type=bca)Erreur dans boot.out$t0 : objet de
> type 'closure' non indi?able
> >
> > I have tried as well to calculate the Pearson coefficient using
> bootstrap and then to calculate the Bca bootstrap CIs of the Pearson. It
> doesn't work either.
> > boot(data = cbind(x, y), statistic = cor, R = 200)
> >
> > ORDINARY NONPARAMETRIC BOOTSTRAP
> >
> >
> > Call:
> > boot(data = cbind(x, y), statistic = cor, R = 200)
> >
> >
> > Bootstrap Statistics :
> >? ? ? original? ? bias? ? std. error
> > t1* -0.6243713 0.6295142? 0.2506267
> > t2* -0.1366533 0.1565392? 0.2579134
> > > boot.ci(cor, conf=0.95, type=bca)
> > Erreur dans boot.out$t0 : objet de type 'closure' non
indi?able
> > Many thanks to tell me how to correct my R script to get the Bca CIs
> for my Pearson coefficient. Best regards, looking forward to reading
> you,
> > SV
>
> >
> >? ? [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
>
>
>
>
>
[[alternative HTML version deleted]]