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




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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/Conte
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
>>
>> ______________________________________________
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>> 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
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> 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

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