Re: [R] arcsine transformation with metafor
-Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Antonello Preti Sent: Monday, November 24, 2014 00:35 To: r-help@r-project.org Subject: [R] arcsine transformation with metafor # I'm trying to adapt to my own data the double arcsine transformation according to Miller (1978) as described in the metafor site # I've understood all passages (I think) # I'm able to build a forest plot with the correct data # I would like to build a funnel plot and a radial plot # However, the rule that is helpful to build a forest plot does not work for the radial or the funnel plot # When I use the results of the fixed (or random) effects model, as expected, the estimates are wrong (about two times the correct estimates) # How can the radial and funnel plot be built for the double arcsine transformation? # Thank you in advance, Antonello # Here the code I've used library(metafor) # The data used by Miller (1978) to illustrate the transformation and its inversion can be re-created with: dat - data.frame(xi=c(3, 6, 10, 1), ni=c(11, 17, 21, 6)) dat$pi - with(dat, xi/ni) dat - escalc(measure=PFT, xi=xi, ni=ni, data=dat) [SNIP] res - rma(yi, vi, method=FE, data=dat) [SNIP] ### However, this is wrong radial(res) funnel(res) They are not wrong. The double arcsine transformed values are used for the plotting, not the raw proportions. In particular, the plots are based on 'yi' in: dat xi nipi yi vi 1 3 11 0.2727273 0.5695 0.0217 2 6 17 0.3529412 0.6444 0.0143 3 10 21 0.4761905 0.7626 0.0116 4 1 6 0.167 0.4758 0.0385 Best, Wolfgang __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] arcsine transformation with metafor
# I'm trying to adapt to my own data the double arcsine transformation according to Miller (1978) as described in the metafor site # I've understood all passages (I think) # I'm able to build a forest plot with the correct data # I would like to build a funnel plot and a radial plot # However, the rule that is helpful to build a forest plot does not work for the radial or the funnel plot # When I use the results of the fixed (or random) effects model, as expected, the estimates are wrong (about two times the correct estimates) # How can the radial and funnel plot be built for the double arcsine transformation? # Thank you in advance, Antonello # Here the code I've used library(metafor) # The data used by Miller (1978) to illustrate the transformation and its inversion can be re-created with: dat - data.frame(xi=c(3, 6, 10, 1), ni=c(11, 17, 21, 6)) dat$pi - with(dat, xi/ni) dat - escalc(measure=PFT, xi=xi, ni=ni, data=dat) dat # The yi values are the Freeman-Tukey (double arcsine) transformed proportions, # while the vi values are the corresponding sampling variances. # We can check whether the back-transformation works for individual values with: transf.ipft(dat$yi, dat$ni) # As described by Miller (1978), we can aggregate the transformed values, # either by computing an unweighted or a weighted mean (with inverse-variance weights). # The unweighted mean can be obtained with: res - rma(yi, vi, method=FE, data=dat, weighted=FALSE) res # The value reported by Miller for the unweighted mean is again twice as large as the value given above, # which we can confirm with: predict(res, transf=function(x) x*2) # To back-transform the average, a value for the sample size is needed. # Miller suggests to use the harmonic mean of the individual sample sizes in the inversion formula. # This can be accomplished with: predict(res, transf=transf.ipft.hm, targs=list(ni=dat$ni)) # Since the true proportions appear to be homogeneous (e.g., Q(3)=2.18, p=.54), # a more efficient estimate of the true proportion can be obtained by using inverse-variance weights. # For this, we first synthesize the transformed values with: res - rma(yi, vi, method=FE, data=dat) res # Again, the value reported by Miller is twice as large. # We can back-transform the estimated transformed average with: predict(res, transf=transf.ipft.hm, targs=list(ni=dat$ni)) # When using the Freeman-Tukey transformation, # an additional complication arises when using the back-transformation. # To back-transform the individual proportions, we need the individual sample sizes: transf.ipft(dat$yi, dat$ni) # To back-transform the estimated average transformed proportion, # we need to use the harmonic mean of the sample sizes: res - rma(yi, vi, method=FE, data=dat) pred - predict(res, transf=transf.ipft.hm, targs=list(ni=dat$ni)) pred # To build a forest plot we need to first obtain the CI bounds of the individual studies with: dat.back - summary(dat, transf=transf.ipft, ni=dat$ni) # Now the back-transformation is applied to each transformed proportion with the study-specific sample sizes. # The yi values are now the back-transformed values (i.e., the raw proportions) # and the ci.lb and ci.ub values are the back-transformed 95% CI bounds.1) # Finally, we can create the forest plot by directly passing the observed outcomes (i.e., proportions) # and the CI bounds to the function. Then the back-transformed average with the corresponding CI bounds obtained earlier # can be added to the plot with the addpoly() function. We add a couple tweaks to make the final forest plot look nice: forest(dat.back$yi, ci.lb=dat.back$ci.lb, ci.ub=dat.back$ci.ub, xlim=c(-.5,1.8), alim=c(0,1), ylim=c(-1,8), refline=NA, digits=3, xlab=Proportion) addpoly(pred$pred, ci.lb=pred$ci.lb, ci.ub=pred$ci.ub, row=-0.5, digits=3, mlab=FE Model, efac=1.3) abline(h=0.5) text(-0.5, 7, Study, pos=4) text( 1.8, 7, Proportion [95% CI], pos=2) ### However, this is wrong radial(res) funnel(res) ## sessionInfo() R version 3.0.2 (2013-09-25) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=Italian_Italy.1252 LC_CTYPE=Italian_Italy.1252 [3] LC_MONETARY=Italian_Italy.1252 LC_NUMERIC=C [5] LC_TIME=Italian_Italy.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] metafor_1.9-3 Matrix_1.1-0 Formula_1.1-1 loaded via a namespace (and not attached): [1] grid_3.0.2 lattice_0.20-24 [[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] Arcsine transformation
At 02:26 23/09/2013, peake wrote: Thanks for the advice. Like I said, I am still pretty new to R, and stats in general. I tried wading through the search results on google, but I didn't really find anything that I could understand. I am working with percentages as my dependent variable, and I am trying to get my distribution as close to normal as possible. Is an arcsine transformation even the correct choice for my data? Querying R for help usually leaves me even more confused, so I was hoping someone could help me out by walking me through the process. Transforming proportions is something which people involved in meta-analysis of non-comparative studies often do. You might like to look in the manual for metafor (on CRAN) and the function escalc which has a range of options under non-comparative studies. You might also look at betareg (on CRAN). I think you also need to find some local statistical support as your question is now less about R and more about statistics. On Sun, Sep 22, 2013 at 8:00 PM, chuck.01 [via R] ml-node+s789695n4676708...@n4.nabble.com wrote: ?asin also, try Googling anything you might want to do in R... it is there also, google... R cheatsheet you will find several helpful sheets of useful functions. peake wrote I am tryin to perform an arcsine transformation on my data containig percentages as the dep. variable. Does anyone have a code that I could use to do that? I am relatively new to R. Thanks for your help! -- If you reply to this email, your message will be added to the discussion below: http://r.789695.n4.nabble.com/Arcsine-transformation-tp4676706p4676708.html To unsubscribe from Arcsine transformation, click herehttp://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=unsubscribe_by_codenode=4676706code=cGVha2UuMTlAb3N1LmVkdXw0Njc2NzA2fDE4MjEzMDk3MTU= . NAMLhttp://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=macro_viewerid=instant_html%21nabble%3Aemail.namlbase=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespacebreadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml -- View this message in context: http://r.789695.n4.nabble.com/Arcsine-transformation-tp4676706p4676712.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]] Michael Dewey i...@aghmed.fsnet.co.uk http://www.aghmed.fsnet.co.uk/home.html __ 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] Arcsine transformation
I am tryin to perform an arcsine transformation on my data containig percentages as the dep. variable. Does anyone have a code that I could use to do that? I am relatively new to R. Thanks for your help! -- View this message in context: http://r.789695.n4.nabble.com/Arcsine-transformation-tp4676706.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] Arcsine transformation
peake peake.19 at osu.edu writes: I am tryin to perform an arcsine transformation on my data containig percentages as the dep. variable. Does anyone have a code that I could use to do that? I am relatively new to R. Thanks for your help! asin(x/100) ? or asin(x/100)*2/pi if you want the results rescaled to (0,1) curve(asin(x/100)*2/pi,from=0,to=100) __ 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] Arcsine transformation
Tena koe
I think you'll find the arcsine transformation is asin(sqrt(x/100)) where × is
the percentage. However, it might be better to ask whether the data wouldn't
be better analysed using generalised models (e.g., glm).
HTH
Peter Alspach
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Ben Bolker
Sent: Monday, 23 September 2013 12:54 p.m.
To: r-h...@stat.math.ethz.ch
Subject: Re: [R] Arcsine transformation
peake peake.19 at osu.edu writes:
I am tryin to perform an arcsine transformation on my data containig
percentages as the dep. variable. Does anyone have a code that I could
use to do that? I am relatively new to R. Thanks for your help!
asin(x/100)
? or
asin(x/100)*2/pi if you want the results rescaled to (0,1)
curve(asin(x/100)*2/pi,from=0,to=100)
__
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Re: [R] Arcsine transformation
On 13-09-22 09:25 PM, Peter Alspach wrote: Tena koe I think you'll find the arcsine transformation is asin(sqrt(x/100)) where × is the percentage. However, it might be better to ask whether the data wouldn't be better analysed using generalised models (e.g., glm). HTH Good point about arcsine-sqrt, and about GLMs: specifically see Warton, David I., and Francis K. C. Hui. 2011. “The Arcsine Is Asinine: The Analysis of Proportions in Ecology.” Ecology 92 (1) (January): 3–10. doi:10.1890/10-0340.1. http://www.esajournals.org/doi/full/10.1890/10-0340.1. I think the title is a little silly, but it's worth reading. Peter Alspach -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Ben Bolker Sent: Monday, 23 September 2013 12:54 p.m. To: r-h...@stat.math.ethz.ch Subject: Re: [R] Arcsine transformation peake peake.19 at osu.edu writes: I am tryin to perform an arcsine transformation on my data containig percentages as the dep. variable. Does anyone have a code that I could use to do that? I am relatively new to R. Thanks for your help! asin(x/100) ? or asin(x/100)*2/pi if you want the results rescaled to (0,1) curve(asin(x/100)*2/pi,from=0,to=100) __ 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. The contents of this e-mail are confidential and may be subject to legal privilege. If you are not the intended recipient you must not use, disseminate, distribute or reproduce all or any part of this e-mail or attachments. If you have received this e-mail in error, please notify the sender and delete all material pertaining to this e-mail. Any opinion or views expressed in this e-mail are those of the individual sender and may not represent those of The New Zealand Institute for Plant and Food Research Limited. __ 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] Arcsine transformation
Thanks for the advice. Like I said, I am still pretty new to R, and stats in general. I tried wading through the search results on google, but I didn't really find anything that I could understand. I am working with percentages as my dependent variable, and I am trying to get my distribution as close to normal as possible. Is an arcsine transformation even the correct choice for my data? Querying R for help usually leaves me even more confused, so I was hoping someone could help me out by walking me through the process. On Sun, Sep 22, 2013 at 8:00 PM, chuck.01 [via R] ml-node+s789695n4676708...@n4.nabble.com wrote: ?asin also, try Googling anything you might want to do in R... it is there also, google... R cheatsheet you will find several helpful sheets of useful functions. peake wrote I am tryin to perform an arcsine transformation on my data containig percentages as the dep. variable. Does anyone have a code that I could use to do that? I am relatively new to R. Thanks for your help! -- If you reply to this email, your message will be added to the discussion below: http://r.789695.n4.nabble.com/Arcsine-transformation-tp4676706p4676708.html To unsubscribe from Arcsine transformation, click herehttp://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=unsubscribe_by_codenode=4676706code=cGVha2UuMTlAb3N1LmVkdXw0Njc2NzA2fDE4MjEzMDk3MTU= . NAMLhttp://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=macro_viewerid=instant_html%21nabble%3Aemail.namlbase=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespacebreadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml -- View this message in context: http://r.789695.n4.nabble.com/Arcsine-transformation-tp4676706p4676712.html Sent from the R help mailing list archive at Nabble.com. [[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] arcsine transformation
I have been trying to preform both a bartlett's test and an arcsine transformation on some average percentage data. I've tried inputting it different ways and I keep getting the same error message: head(workingdata) DYAD BEFORE AFTER 1 BG-FL 4.606772 5.787520 2 BG-LL 5.467503 7.847395 3 AD-MV 5.333735 11.107380 4 MM-FL 5.578708 12.063500 5 MM-MV 2.037605 6.415303 6 MM-RM 6.158885 11.911080 bartlett.test(BEFORE ~ AFTER) Error in bartlett.test.default(c(4.606772, 5.467503, 5.333735, 5.578708, : there must be at least 2 observations in each group asin(BEFORE) [1] NaN NaN NaN NaN NaN NaN NaN Warning message: In asin(BEFORE) : NaNs produced I'm at a loss here and I would greatly appreciate any guidance that could be given me. Thank you! -- Claire Sheller Department of Anthropology Tulane University New Orleans, LA 70118 615-210-9129 [[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] arcsine transformation
Perhaps you need with(workingdata, asin(BEFORE)) or asin(workingdata$BEFORE) _ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400Charlottesville, VA 22904-4400 Parcels:Room 102Gilmer Hall McCormick RoadCharlottesville, VA 22903 Office:B011+1-434-982-4729 Lab:B019+1-434-982-4751 Fax:+1-434-982-4766 WWW:http://www.people.virginia.edu/~mk9y/ On Apr 30, 2008, at 4:52 PM, Claire Sheller wrote: I have been trying to preform both a bartlett's test and an arcsine transformation on some average percentage data. I've tried inputting it different ways and I keep getting the same error message: head(workingdata) DYAD BEFORE AFTER 1 BG-FL 4.606772 5.787520 2 BG-LL 5.467503 7.847395 3 AD-MV 5.333735 11.107380 4 MM-FL 5.578708 12.063500 5 MM-MV 2.037605 6.415303 6 MM-RM 6.158885 11.911080 bartlett.test(BEFORE ~ AFTER) Error in bartlett.test.default(c(4.606772, 5.467503, 5.333735, 5.578708, : there must be at least 2 observations in each group asin(BEFORE) [1] NaN NaN NaN NaN NaN NaN NaN Warning message: In asin(BEFORE) : NaNs produced I'm at a loss here and I would greatly appreciate any guidance that could be given me. Thank you! -- Claire Sheller Department of Anthropology Tulane University New Orleans, LA 70118 615-210-9129 [[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] arcsine transformation
On 4/30/2008 4:52 PM, Claire Sheller wrote: I have been trying to preform both a bartlett's test and an arcsine transformation on some average percentage data. I've tried inputting it different ways and I keep getting the same error message: head(workingdata) DYAD BEFORE AFTER 1 BG-FL 4.606772 5.787520 2 BG-LL 5.467503 7.847395 3 AD-MV 5.333735 11.107380 4 MM-FL 5.578708 12.063500 5 MM-MV 2.037605 6.415303 6 MM-RM 6.158885 11.911080 bartlett.test(BEFORE ~ AFTER) Error in bartlett.test.default(c(4.606772, 5.467503, 5.333735, 5.578708, : there must be at least 2 observations in each group bartlett.test() expects the second argument to be a vector or factor object giving the group for the corresponding elements of x. You seem to have paired samples instead. asin(BEFORE) [1] NaN NaN NaN NaN NaN NaN NaN Warning message: In asin(BEFORE) : NaNs produced You might divide the values by 100 prior to asin(). I'm at a loss here and I would greatly appreciate any guidance that could be given me. Thank you! -- Chuck Cleland, Ph.D. NDRI, Inc. (www.ndri.org) 71 West 23rd Street, 8th floor New York, NY 10010 tel: (212) 845-4495 (Tu, Th) tel: (732) 512-0171 (M, W, F) fax: (917) 438-0894 __ 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.
