I Achim, I retained the example (so to illustrate the use of the function) - but pointed out to it's nonsensical nature. Credit was mentioned to both you and Allan.
Thanks, Tal ----------------Contact Details:------------------------------------------------------- Contact me: tal.gal...@gmail.com | 972-52-7275845 Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | www.r-statistics.com (English) ---------------------------------------------------------------------------------------------- On Wed, Jul 7, 2010 at 12:31 PM, Achim Zeileis <achim.zeil...@uibk.ac.at>wrote: > On Wed, 7 Jul 2010, Tal Galili wrote: > > Hi Achim and Allan,I updated the post with Allan's example (thanks Allan). >> > > Thanks! > > > Achim, you wrote: >> "Finally, the Poisson model in comparison with the binomial models does >> not >> make much sense, I guess." >> I agree. I wanted something to showcase the function on 3 models (with >> the >> same predictors), and that's the easiest I could think of. If you'd think >> of a smarter example I'd be happy to incorporate it. >> > > You could generate Poisson data and then fit the binomial model to the > threshold version of the response. > > But I guess that would be a bit over the top. Also, one could argue in that > case that a complementary log-log link should be employed. > > Hence, I would simply "say" (verbally) that it works for baysglm, glm, lm, > polr objects and that a default method is available which takes pre-computed > coefficients and associated standard errors from any suitable model. > > Best, > > Z > > Best, >> Tal >> >> >> >> ----------------Contact >> Details:------------------------------------------------------- >> Contact me: tal.gal...@gmail.com | 972-52-7275845 >> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | >> www.r-statistics.com (English) >> >> --------------------------------------------------------------------------- >> ------------------- >> >> >> >> >> On Wed, Jul 7, 2010 at 12:10 PM, Achim Zeileis <achim.zeil...@uibk.ac.at> >> wrote: >> On Wed, 7 Jul 2010, Tal Galili wrote: >> >> Hello David, >> Thanks to your posting I started looking at the >> function in the arm package. >> It appears this function is quite mature, and >> offers (for example) the >> ability to easily overlap coefficients from several >> models. >> >> >> Re: more mature. arm's coefplot() is more flexible in certain >> respects, mine is more convenient in others. The overlay functionality >> is something arm's coefplot() is better in and it also as some further >> options (vertical vs. horizontal etc.). My coefplot() has the >> advantage that it does not need any modification as long as coef() and >> vcov() methods are available. Furthermore, "level" can specify the >> significance level (instead of always using one and two standard >> errors, respectively). >> But it shouldn't be too hard to create a superset of all options. >> >> I updated the post I published on the subject, so at the >> end of it I give an >> example of comparing the coef of several models: >> >> http://www.r-statistics.com/2010/07/visualization-of-regression-coefficient >> >> s-in-r/ >> >> >> As Allan pointed out in his reply, something fully reproducible would >> be nice. Also, if you keep the example with quasi-complete separation, >> it would be worth pointing this out. (Because the maximum likelihood >> estimator is Infinity in this case.) >> >> Finally, the Poisson model in comparison with the binomial models does >> not make much sense, I guess. >> >> Best, >> Z >> >> Thanks again for the pointer. >> >> Best, >> Tal >> >> >> >> >> ----------------Contact >> Details:------------------------------------------------------- >> Contact me: tal.gal...@gmail.com | 972-52-7275845 >> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il >> (Hebrew) | >> www.r-statistics.com (English) >> >> --------------------------------------------------------------------------- >> >> ------------------- >> >> >> >> >> On Wed, Jul 7, 2010 at 12:02 AM, David Atkins >> <datk...@u.washington.edu> >> wrote: >> >> >> FYI, there is already a function coefplot in the arm >> package; >> for example, compare: >> >> > library(arm) >> Loading required package: MASS >> Loading required package: Matrix >> [snip] >> Attaching package: 'arm' >> >> The following object(s) are masked from 'package:coda': >> >> traceplot >> >> > data("Mroz", package = "car") >> > fm <- glm(lfp ~ ., data = Mroz, family = binomial) >> > coefplot(fm) >> >> with version below. >> >> cheeres, Dave >> >> > >> > detach("package:arm") >> >> > coefplot <- function(object, df = NULL, level = 0.95, parm = >> NULL, >> + labels = TRUE, xlab = "Coefficient confidence intervals", >> ylab = >> "", >> + xlim = NULL, ylim = NULL, >> + las = 1, lwd = 1, lty = c(1, 2), pch = 19, col = 1, >> + length = 0, angle = 30, code = 3, ...) >> + { >> + cf <- coef(object) >> + se <- sqrt(diag(vcov(object))) >> + if(is.null(parm)) parm <- seq_along(cf) >> + if(is.numeric(parm) | is.logical(parm)) parm <- >> names(cf)[parm] >> + if(is.character(parm)) parm <- which(names(cf) %in% parm) >> + cf <- cf[parm] >> + se <- se[parm] >> + k <- length(cf) >> + >> + if(is.null(df)) { >> + df <- if(identical(class(object), "lm")) >> df.residual(object) >> else 0 >> + } >> + >> + critval <- if(df > 0 & is.finite(df)) { >> + qt((1 - level)/2, df = df) >> + } else { >> + qnorm((1 - level)/2) >> + } >> + ci1 <- cf + critval * se >> + ci2 <- cf - critval * se >> + >> + lwd <- rep(lwd, length.out = 2) >> + lty <- rep(lty, length.out = 2) >> + pch <- rep(pch, length.out = k) >> + col <- rep(col, length.out = k) >> + >> + if(is.null(xlim)) xlim <- range(c(0, min(ci1), max(ci2))) >> + if(is.null(ylim)) ylim <- c(1 - 0.05 * k, 1.05 * k) >> + >> + if(isTRUE(labels)) labels <- names(cf) >> + if(identical(labels, FALSE)) labels <- "" >> + labels <- rep(labels, length.out = k) >> + >> + plot(0, 0, xlim = xlim, ylim = ylim, xlab = xlab, ylab = >> ylab, >> + axes = FALSE, type = "n", las = las, ...) >> + arrows(ci1, 1:k, ci2, 1:k, lty = lty[1], lwd = lwd[1], col >> = col, >> + length = length, angle = angle, code = code) >> + points(cf, 1:k, pch = pch, col = col) >> + abline(v = 0, lty = lty[2], lwd = lwd[2]) >> + axis(1) >> + axis(2, at = 1:k, labels = labels, las = las) >> + box() >> + } >> > >> > >> > coefplot(fm, parm = -1) >> >> >> >> >> Achim Zeileis wrote: >> >> I've thought about adding a plot() method for the coeftest() >> function >> in >> the "lmtest" package. Essentially, it relies on a coef() and a >> vcov() >> method being available - and that a central limit theorem holds. >> For >> releasing it as a general function in the package the code is >> still >> too >> raw, but maybe it's useful for someone on the list. Hence, I've >> included >> it below. >> >> An example would be to visualize all coefficients except the >> intercept >> for >> the Mroz data: >> >> data("Mroz", package = "car") >> fm <- glm(lfp ~ ., data = Mroz, family = binomial) >> coefplot(fm, parm = -1) >> >> hth, >> Z >> >> coefplot <- function(object, df = NULL, level = 0.95, parm = >> NULL, >> labels = TRUE, xlab = "Coefficient confidence intervals", ylab >> = "", >> xlim = NULL, ylim = NULL, >> las = 1, lwd = 1, lty = c(1, 2), pch = 19, col = 1, >> length = 0, angle = 30, code = 3, ...) >> { >> cf <- coef(object) >> se <- sqrt(diag(vcov(object))) >> if(is.null(parm)) parm <- seq_along(cf) >> if(is.numeric(parm) | is.logical(parm)) parm <- >> names(cf)[parm] >> if(is.character(parm)) parm <- which(names(cf) %in% parm) >> cf <- cf[parm] >> se <- se[parm] >> k <- length(cf) >> >> if(is.null(df)) { >> df <- if(identical(class(object), "lm")) df.residual(object) >> else >> 0 >> } >> >> critval <- if(df > 0 & is.finite(df)) { >> qt((1 - level)/2, df = df) >> } else { >> qnorm((1 - level)/2) >> } >> ci1 <- cf + critval * se >> ci2 <- cf - critval * se >> >> lwd <- rep(lwd, length.out = 2) >> lty <- rep(lty, length.out = 2) >> pch <- rep(pch, length.out = k) >> col <- rep(col, length.out = k) >> >> if(is.null(xlim)) xlim <- range(c(0, min(ci1), max(ci2))) >> if(is.null(ylim)) ylim <- c(1 - 0.05 * k, 1.05 * k) >> >> if(isTRUE(labels)) labels <- names(cf) >> if(identical(labels, FALSE)) labels <- "" >> labels <- rep(labels, length.out = k) >> >> plot(0, 0, xlim = xlim, ylim = ylim, xlab = xlab, ylab = ylab, >> axes = FALSE, type = "n", las = las, ...) >> arrows(ci1, 1:k, ci2, 1:k, lty = lty[1], lwd = lwd[1], col = >> col, >> length = length, angle = angle, code = code) >> points(cf, 1:k, pch = pch, col = col) >> abline(v = 0, lty = lty[2], lwd = lwd[2]) >> axis(1) >> axis(2, at = 1:k, labels = labels, las = las) >> box() >> } >> >> >> On Fri, 2 Jul 2010, Tal Galili wrote: >> >> > Specifically this link: >> > >> http://tables2graphs.com/doku.php?id=04_regression_coefficients >> > >> > Great reference Bernd, thank you. >> > >> > Tal >> > >> > >> > ----------------Contact >> > >> Details:------------------------------------------------------- >> > Contact me: Tal.Galili at gmail.com | 972-52-7275845 >> > Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il >> (Hebrew) | >> > www.r-statistics.com (English) >> >> >-------------------------------------------------------------------------- >> - >> ------------------- >> > >> > >> > >> > >> > On Fri, Jul 2, 2010 at 10:31 AM, Bernd Weiss <bernd.weiss at >> uni-koeln.de>wrote: >> > >> >> Am 02.07.2010 08:10, schrieb Wincent: >> >>> Dear all, >> >>> >> >>> I try to show a subset of coefficients in my presentation. >> It >> seems >> >>> that a "standard" table is not a good way to go. I found >> figure 9 >> >>> (page 9) in this file ( >> >>> >> >> >> http://www.destatis.de/jetspeed/portal/cms/Sites/destatis/Internet/DE/Con >> te >> >> nt/Wissenschaftsforum/Kolloquien/VisualisierungModellierung__Beitrag,proper >> >> ty=file.pdf >> >>> >> >>> >> >> ) looks pretty good. I wonder if there is any function for >> such >> plot? >> >>> Or any suggestion on how to present statistical models in a >> >>> presentation? >> >> >> >> Hi Wincent, >> >> >> >> I guess you are looking for "Using Graphs Instead of Tables >> in >> Political >> >> Science" by Kastellec/Leoni >> <http://tables2graphs.com/doku.php>. >> >> >> >> HTH, >> >> >> >> Bernd >> >> >> >> ______________________________________________ >> >> R-help at 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. >> >> >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help at 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. >> > >> >> -- >> Dave Atkins, PhD >> Research Associate Professor >> Department of Psychiatry and Behavioral Science >> University of Washington >> datk...@u.washington.edu >> >> Center for the Study of Health and Risk Behaviors (CSHRB) >> >> >> 1100 NE 45th Street, Suite 300 >> Seattle, WA 98105 >> 206-616-3879 >> http://depts.washington.edu/cshrb/ >> (Mon-Wed) >> >> Center for Healthcare Improvement, for Addictions, Mental >> Illness, >> Medically Vulnerable Populations (CHAMMP) >> 325 9th Avenue, 2HH-15 >> Box 359911 >> Seattle, WA 98104 >> http://www.chammp.org >> (Thurs) >> >> >> ______________________________________________ >> 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. >> >> >> >> >> >> [[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.
