We will be releasing this bug-fix very soon.
Cheers,
Kosuke
On Wed, 11 Jun 2008, Olivia Lau wrote:
Dear Keith,
I fixed the problem that you identify in plot.ci (a simple if
statement problem), but there's another associated problem in setx
that prevents plot.ci from working with mixed effect models (for now).
As a sidebar, your syntax below doesn't work for plot.ci in general.
Here's why:
What you have below compares expected values for just one change in an
independent variable. These would look like just two bars on the plot
showing the range of the 95% confidence intervals. A more informative
way to present this information would be to do two overlapping density
plots.
To produce this plot, run demo(logit.mixed), then:
s.high <- sim(z.out, x = x.high)
s.low <- sim(z.out, x = x.low)
xlim <- range(c(s.high$qi$ev, s.low$qi$ev))
plot(density(s.high$qi$ev), col = "red", xlim = xlim)
lines(density(s.low$qi$ev), col = "blue")
In contrast, the plot.ci function is intended to show the change in
the dependent variable for more than one change in an independent
variable. For example, if you let age or education vary from 10:20,
you could use plot.ci rather than the procedure above. See
demo(plot.ci) for this example.
Yours,
Olviia
On Wed, Jun 11, 2008 at 9:04 PM, Keith Schnakenberg
<keith.schnakenberg(a)gmail.com> wrote:
Hello all,
I noticed that Olivia posted in January that she added mixed effects models
to plot.ci and that it would be in the next release. Has it been added? I am
having trouble using it on the latest version. A reproducible example is
given below:
data(voteincome)
x.high <- setx(z.out1, education = quantile(voteincome$education, 0.8))
x.low <- setx(z.out1, education = quantile(voteincome$education, 0.2))
s.out1 <- sim(z.out1, x = x.high, x1 = x.low)
plot.ci(s.out1, CI=95, qi="ev")
Error in plot.ci(s.out1, CI = 95, qi =
"ev") :
plot.ci() is valid only for non-categorical, univariate response models.
Thanks,
Keith Schnakenberg
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