Re: [R] Power Calculation:2-sided exact equivalence test for Binomial Proportions
Hi again, In fact the pwr package do not provide exact test power. So you should definitely use g*power. Sincerely, Adrien. De : Munjal Patel À : r-help@r-project.org Envoyé le : Mardi 7 juin 2016 18h26 Objet : [R] Power Calculation:2-sided exact equivalence test for Binomial Proportions Dear R-Users, I am an intermediate level R user. I am performing the power calculations for the Binomial proportions (2 sided). I want to find the Power using the Exact test for the Equivalence of Binomial proportions. I do have the SAS code which is generating the Power for me but i am unable to find the Similar code in R. I need help for finding the similar computation in R. My SAS code. proc power; onesamplefreq test = equiv_exact alpha = 0.05 proportion = 0.30 lower = 0.2 upper = 0.4 ntotal = 500 power = .; run; Can somebody help me by providing the R code for the similar calculation ? Thank you. MJ [[alternative HTML version deleted]] __ R-help@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]] __ R-help@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.
Re: [R] Power Calculation: Binomial Proportions (2 sided exact test for equivalence)
Dear Munjal,
You should use the pwr package with the following code :library(pwr)
# lower
pwr.2p.test(h =ES.h(0.3, 0.2), n = 500, sig.level = 0.05, power = NULL,
alternative = c("two.sided"))#upperpwr.2p.test(h =ES.h(0.3, 0.4), n = 500,
sig.level = 0.05, power = NULL, alternative = c("two.sided"))
Maybe you could use G*power :Lower case 1-beta = 0.9557076Upper one 1-beta=
0.9134817
Hope this help,
Adrien Bonache.
De : Munjal Patel
À : r-help@r-project.org
Envoyé le : Mardi 7 juin 2016 18h08
Objet : [R] Power Calculation: Binomial Proportions (2 sided exact test for
equivalence)
Dear R-Sig-teaching users,
I am an intermediate level R user.
I am performing the power calculations for the Binomial proportions (2
sided).
I want to find the Power using the Exact test for the Equivalence of
Binomial proportions.
I do have the SAS code which is generating the Power for me but i am unable
to find the Similar code in R.
I need help for finding the similar computation in R.
My SAS code.
proc power;
onesamplefreq test = equiv_exact
alpha = 0.05
proportion = 0.30
lower = 0.2
upper = 0.4
ntotal = 500
power = .;
run;
Can somebody helkp me by providing the R code for the similar calculation ?
Thank you.
MJ
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Re: [R] Power Calculation:2-sided exact equivalence test for Binomial Proportions
Em Ter 7 jun. 2016, às 13:26, Munjal Patel escreveu: > Dear R-Users, > I am an intermediate level R user. > > I am performing the power calculations for the Binomial proportions (2 > sided). > I want to find the Power using the Exact test for the Equivalence of > Binomial proportions. > I do have the SAS code which is generating the Power for me but i am > unable > to find the Similar code in R. > I need help for finding the similar computation in R. > I'm not a statistician, and I have never hear of power calculation using exact test. On the other hand, with hundreds of observations on each group, does it matter? Maybe you could simply use power.prop.test(), from the loaded-by-default package "stats". Of course, you could look for packages about proportions or binomial in CRAN, or set up a simulation. Hope that helps, Leonardo Ferreira Fontenelle, MD, MPH PhD candidate, Federal University of Pelotas Professor of Medicine, Vila Velha University Legislative consultant, Municipal Chamber of Vitória __ R-help@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.
Re: [R] Power Calculation:2-sided exact equivalence test for Binomial Proportions
Please search before posting, and if your search fails to get what you want, tell us why. I got what appeared to be many relevant hits on rseek.org using the search term "binomial exact power computations" . -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Jun 7, 2016 at 9:26 AM, Munjal Patel wrote: > Dear R-Users, > I am an intermediate level R user. > > I am performing the power calculations for the Binomial proportions (2 > sided). > I want to find the Power using the Exact test for the Equivalence of > Binomial proportions. > I do have the SAS code which is generating the Power for me but i am unable > to find the Similar code in R. > I need help for finding the similar computation in R. > > My SAS code. > > proc power; > onesamplefreq test = equiv_exact > alpha = 0.05 > proportion = 0.30 > lower = 0.2 > upper = 0.4 > ntotal = 500 > power = .; > run; > > Can somebody help me by providing the R code for the similar calculation ? > Thank you. > > MJ > > [[alternative HTML version deleted]] > > __ > R-help@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. __ R-help@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.
Re: [R] Power Calculation: Binomial Proportions (2 sided exact test for equivalence)
Em Ter 7 jun. 2016, às 13:08, Munjal Patel escreveu: > Dear R-Sig-teaching users, > I am an intermediate level R user. You posted both emails to the same mailing list. Please remember that "cross-posting is considered to be impolite" and that "you should configure your e-mail software in such a way as to send only plain text": https://www.r-project.org/mail.html Best regards, Leonardo Ferreira Fontenelle, MD, MPH PhD candidate, Federal University of Pelotas Professor of Medicine, Vila Velha University Legislative consultant, Municipal Chamber of Vitória __ R-help@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.
Re: [R] Power Calculation:2-sided exact equivalence test for Binomial Proportions
MJ: I think the EnvStats package has various power functions for binomial applications (also confidence interval half-widths). Brian Brian S. Cade, PhD U. S. Geological Survey Fort Collins Science Center 2150 Centre Ave., Bldg. C Fort Collins, CO 80526-8818 email: ca...@usgs.gov tel: 970 226-9326 On Tue, Jun 7, 2016 at 10:26 AM, Munjal Patel wrote: > Dear R-Users, > I am an intermediate level R user. > > I am performing the power calculations for the Binomial proportions (2 > sided). > I want to find the Power using the Exact test for the Equivalence of > Binomial proportions. > I do have the SAS code which is generating the Power for me but i am unable > to find the Similar code in R. > I need help for finding the similar computation in R. > > My SAS code. > > proc power; > onesamplefreq test = equiv_exact > alpha = 0.05 > proportion = 0.30 > lower = 0.2 > upper = 0.4 > ntotal = 500 > power = .; > run; > > Can somebody help me by providing the R code for the similar calculation ? > Thank you. > > MJ > > [[alternative HTML version deleted]] > > __ > R-help@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]] __ R-help@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.
[R] Power Calculation: Binomial Proportions (2 sided exact test for equivalence)
Dear R-Sig-teaching users, I am an intermediate level R user. I am performing the power calculations for the Binomial proportions (2 sided). I want to find the Power using the Exact test for the Equivalence of Binomial proportions. I do have the SAS code which is generating the Power for me but i am unable to find the Similar code in R. I need help for finding the similar computation in R. My SAS code. proc power; onesamplefreq test = equiv_exact alpha = 0.05 proportion = 0.30 lower = 0.2 upper = 0.4 ntotal = 500 power = .; run; Can somebody helkp me by providing the R code for the similar calculation ? Thank you. MJ [[alternative HTML version deleted]] __ R-help@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.
[R] Power Calculation:2-sided exact equivalence test for Binomial Proportions
Dear R-Users, I am an intermediate level R user. I am performing the power calculations for the Binomial proportions (2 sided). I want to find the Power using the Exact test for the Equivalence of Binomial proportions. I do have the SAS code which is generating the Power for me but i am unable to find the Similar code in R. I need help for finding the similar computation in R. My SAS code. proc power; onesamplefreq test = equiv_exact alpha = 0.05 proportion = 0.30 lower = 0.2 upper = 0.4 ntotal = 500 power = .; run; Can somebody help me by providing the R code for the similar calculation ? Thank you. MJ [[alternative HTML version deleted]] __ R-help@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.
[R] Power calculation
I am are currently evaluating risk factors associated with a virus A , incidence among patients with a follow-up sample of 312. Overall, the virus incidence rate is estimated at 4.7 per 100 pyr, 95% CI (3.0-7.4), with a total follow-up time of 383.9 person years and 18 incidence cases. How can I do a power calculation based on assumptions of the virus acquisition in patients who have virus B? For a rate that is twice as high, four times as high, and even eight times higher. Virus B Yes- 203 No-109 I have tried using which gives a very suscpicious power? v <- qnorm(0.975) mu <- 0.047 muEst <- 0.094 #for a rate twice as high n <- 312 #top left <- (n*((muEst-mu)^2))/mu left <- sqrt(left) ucalc<-left -v ucalc pnorm(ucalc) The formula used is at Essential Medical Statistics Book by Betty R Kirkwood et al pg 420 formula 2. __ R-help@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.
Re: [R] Power calculation using pwr.t.test()
On Jun 24, 2012, at 11:41 AM, Jokel Meyer wrote: Dear R experts, I have conducted a power calculation in order to estimate the number of subjects needed to detect an effect size of d=0.28 (cohen's d) for a difference between two independent groups (alpha level should be 0.05 and the effect should be detected with 80% probability). The results from the code below indicates that I would need n=400 subjects (200 in each group). This is seems so incredibly high that I mistrust my results & wanted to ask whether I miscalculated n? library(pwr) pwr .t .test (d = 0.28 ,sig.level=0.05,power=0.8,type="two.sample",alternative="two.sided") Your reaction is typical for inexperienced researchers who conduct power analyses. An effect size of .28 is considered a "small effect size" so it should not seem unreasonable that you would need 200 per group. As a quick check I Googled for an online sample size calculator and the first one I used reported the need for 202 per group for a two sided test at those levels. -- David Winsemius, MD West Hartford, CT __ R-help@r-project.org mailing list 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.
Re: [R] Power calculation using pwr.t.test()
On 24.06.2012 17:41, Jokel Meyer wrote: Dear R experts, I have conducted a power calculation in order to estimate the number of subjects needed to detect an effect size of d=0.28 (cohen's d) for a difference between two independent groups (alpha level should be 0.05 and the effect should be detected with 80% probability). The results from the code below indicates that I would need n=400 subjects (200 in each group). This is seems so incredibly high that I mistrust my results & wanted to ask whether I miscalculated n? library(pwr) pwr.t.test(d=0.28,sig.level=0.05,power=0.8,type="two.sample",alternative="two.sided") Good luck this is an open source software where you can easily review the code and check if it is right. If it is not, I'd propose to send a patch to the package maintainer. Best, Uwe Ligges Many thanks for you help! Jokel [[alternative HTML version deleted]] __ R-help@r-project.org mailing list 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. __ R-help@r-project.org mailing list 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.
[R] Power calculation using pwr.t.test()
Dear R experts, I have conducted a power calculation in order to estimate the number of subjects needed to detect an effect size of d=0.28 (cohen's d) for a difference between two independent groups (alpha level should be 0.05 and the effect should be detected with 80% probability). The results from the code below indicates that I would need n=400 subjects (200 in each group). This is seems so incredibly high that I mistrust my results & wanted to ask whether I miscalculated n? library(pwr) pwr.t.test(d=0.28,sig.level=0.05,power=0.8,type="two.sample",alternative="two.sided") Many thanks for you help! Jokel [[alternative HTML version deleted]] __ R-help@r-project.org mailing list 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.
Re: [R] Power calculation for survival analysis
On Sep 21, 2011, at 12:37 PM, Duke wrote: > Thanks for your response, Marc. HG and LG are high-grade/low-grade tumors. > The data has not been collected yet, but will be soon. It's all archived > data that will be pulled from computer records. The IRB wants some mention > of power or sample size, but doing it for this scenario has been a bit of a > head scratcher for me. > If it's not really feasible to do a power analysis for this scenario, I can > work to explain why to the IRB. > > D Hi Derek, My guess is that the IRB wants to have some CYA in terms of the justification for the study. In a design such as this, safety is not the typical concern, since the patients have already been treated and nothing that you are going to do will affect that. More than likely, there may be privacy (e.g. HIPAA) and ethical issues, pertaining to your accessing the medical records of the patients and having a reasonable level of assurance that you will be able to offer some scientific value at the end of the day as a consequence of that access. I don't know the particulars of your IRB, so it may be of value to approach others at Duke who have experience in dealing with them in the setting of a retrospective chart review. You may be able to get a sense for what they are open to in terms of justification and where they may or may not be amenable to a discussion of the pros/cons of this particular approach. It is not uncommon, in my experience, to simply indicate that n = 500 is a "convenience sample", based upon some assessment of time/budget limitations and some attempt to assess the number of patients with some common set of characteristics that are likely to be available within a reasonable time frame. In that setting, power as a discrete quantity is not quoted and you don't have an explicit hypothesis to be tested. You "get what you get" and within the limitations of the study design, can offer some insight into the differences in the two groups. I have seen the same approach even with prospective, non-randomized designs. All of that being said, you can use Frank's cpower() function in Hmisc, if they put a gun to your head. It would not be overly difficult to do that, you just need to be aware of your assumptions and how they can impact the resultant power calculation. Using the function itself is not overly complex. HTH, Marc __ R-help@r-project.org mailing list 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.
Re: [R] Power calculation for survival analysis
Thanks for your response, Marc. HG and LG are high-grade/low-grade tumors. The data has not been collected yet, but will be soon. It's all archived data that will be pulled from computer records. The IRB wants some mention of power or sample size, but doing it for this scenario has been a bit of a head scratcher for me. If it's not really feasible to do a power analysis for this scenario, I can work to explain why to the IRB. D -- View this message in context: http://r.789695.n4.nabble.com/Power-calculation-for-survival-analysis-tp3830031p3830814.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list 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.
Re: [R] Power calculation for survival analysis
On Sep 21, 2011, at 8:54 AM, Duke wrote: > useR's, > I am trying to do a power calculation for a survival analysis using a > logrank test and I need some help properly doing this in R. Here is the > information that I know: > - I have 2 groups, namely HG and LG > - Retrospective analysis with subjects gathered from archival data over 20 > years. No new recruitment of subjects and no estimated time to target > accrual and accrual rate. > - Survival measured in both groups at 1 year, 3 years, 5 years. > - Assume 50% survival for LG and 30% survival for HG at 5 years. > - Assume a 6 month difference in overall survival to be statistically > significant. > - Total sample size is ~ N=500 with 15% of subjects comprising the LG group; > 85% make up the HG group. > > The main hypothesis is that HG group has shorter overall survival than LG > group. > > Can someone please help me out with how to properly calculate the power for > such a situation using R? This is new to me. > > Thanks, > D Short answer, look at the cpower() function in Frank's Hmisc package on CRAN. Longer answer: Have you already performed the data collection and analysis? If so, then performing a post hoc power calculation is highly problematic. Do a Google search on "post hoc power" and you will find a myriad of resources/citations. Given the sizable differences in the two samples and that this is a retrospective analysis, you are almost certainly going to have selection bias issues to deal with in comparing the two groups, since presumably they were not prospectively randomized to group, even with the ratio indicated. Is the "HG" group High Grade Lymphoma and the LG group Low Grade Lymphoma? That would help to explain some of the issues here, since you have two groups with differing diagnoses, differing baseline characteristics and known material differences in prognosis. With a retrospective analysis over this time frame, loss to follow up (LTFU) is likely to be another issue, impacting your available data over time, especially if there is a bias in LTFU between the groups. LTFU is hard enough to manage in a prospective study. Using your numbers, you also have the potential for temporal issues impacting your comparison. If you are looking out to 5 years and the data was collected over a 20 year time frame, that suggests a possible 15 year difference between your first patient Time 0 and your last patient Time 0. What changes in patient and/or treatment profiles occurred over time that might impact your findings? Were the two groups treated concurrently or is there a stagger of some time window? Are the patients a consecutive series in each group or is there other selection bias involved as to why one patient is in the study and another is not. If you are not comfortable with these issues, you have a lot of resources at Duke (eg. DCRI) with some very experienced folks there. HTH, Marc Schwartz __ R-help@r-project.org mailing list 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.
[R] Power calculation for survival analysis
useR's, I am trying to do a power calculation for a survival analysis using a logrank test and I need some help properly doing this in R. Here is the information that I know: - I have 2 groups, namely HG and LG - Retrospective analysis with subjects gathered from archival data over 20 years. No new recruitment of subjects and no estimated time to target accrual and accrual rate. - Survival measured in both groups at 1 year, 3 years, 5 years. - Assume 50% survival for LG and 30% survival for HG at 5 years. - Assume a 6 month difference in overall survival to be statistically significant. - Total sample size is ~ N=500 with 15% of subjects comprising the LG group; 85% make up the HG group. The main hypothesis is that HG group has shorter overall survival than LG group. Can someone please help me out with how to properly calculate the power for such a situation using R? This is new to me. Thanks, D -- View this message in context: http://r.789695.n4.nabble.com/Power-calculation-for-survival-analysis-tp3830031p3830031.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list 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.
Re: [R] Power calculation
On 6/10/2010 8:26 AM, Samuel Okoye wrote:
> Hello,
>
> Is there any R function which does power calculation for unbalanced groups
> (n1 neq n2)? Since power.t.test has n
>
> Number of observations (per group).
>
> Many thanks,
> Samuel
See pwr.t2n.test() in the pwr package.
http://finzi.psych.upenn.edu/R/library/pwr/html/pwr.t2n.test.html
You might have found it by doing the following in R:
RSiteSearch("power analysis", restrict='function')
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> 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.
--
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New York, NY 10010
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[R] Power calculation
Hello, Is there any R function which does power calculation for unbalanced groups (n1 neq n2)? Since power.t.test has n Number of observations (per group). Many thanks, Samuel [[alternative HTML version deleted]] __ R-help@r-project.org mailing list 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.
Re: [R] power calculation for repeated measures ANOVA?
G*Power 3 is free software for Mac and PC, see http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpower3/ Jay On 9/16/07, MATTHEW BRIDGMAN <[EMAIL PROTECTED]> wrote: > Is there a way to calculate power for repeated > measures ANOVA (2 groups x 7 observations)? I have > searched all over, but all I can find is > power.anova.test, but that would not give accurate > results, right? > > Thanks, > Matt Bridgman > > __ > R-help@r-project.org mailing list > 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. > -- *** G. Jay Kerns, Ph.D. Assistant Professor / Statistics Coordinator Department of Mathematics & Statistics Youngstown State University Youngstown, OH 44555-0002 USA Office: 1035 Cushwa Hall Phone: (330) 941-3310 Office (voice mail) -3302 Department -3170 FAX E-mail: [EMAIL PROTECTED] http://www.cc.ysu.edu/~gjkerns/ __ R-help@r-project.org mailing list 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.
Re: [R] power calculation for repeated measures ANOVA?
Mind a book reference instead of a software reference? Look for Bausell and Li's "Power Analysis for Experimental Research" -- cookbook style power calculations, but has explicit RM ANOVA. On 9/16/07, MATTHEW BRIDGMAN <[EMAIL PROTECTED]> wrote: > Is there a way to calculate power for repeated > measures ANOVA (2 groups x 7 observations)? I have > searched all over, but all I can find is > power.anova.test, but that would not give accurate > results, right? > > Thanks, > Matt Bridgman > > __ > R-help@r-project.org mailing list > 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. > -- I can answer any question. "I don't know" is an answer. "I don't know yet" is a better answer. __ R-help@r-project.org mailing list 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.
[R] power calculation for repeated measures ANOVA?
Is there a way to calculate power for repeated measures ANOVA (2 groups x 7 observations)? I have searched all over, but all I can find is power.anova.test, but that would not give accurate results, right? Thanks, Matt Bridgman __ R-help@r-project.org mailing list 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.
