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.gal...@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.we...@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/Content/Wissenschaftsforum/Kolloquien/VisualisierungModellierung__Beitrag,property=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@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.
______________________________________________
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.