Description Usage Arguments Details Value Author(s) See Also Examples
Computes confidence intervals from the profiled likelihood for the standard devation for the random term in a fitted cumulative link mixed model, or plots the associated profile likelihood function.
1 2 3 4 5 6 7 8 9  ## S3 method for class 'profile.clmm2'
confint(object, parm = seq_along(Pnames), level = 0.95, ...)
## S3 method for class 'clmm2'
profile(fitted, alpha = 0.01, range, nSteps = 20, trace = 1, ...)
## S3 method for class 'profile.clmm2'
plot(x, parm = seq_along(Pnames), level = c(0.95, 0.99),
Log = FALSE, relative = TRUE, fig = TRUE, n = 1e3, ..., ylim = NULL)

object 
a fitted 
fitted 
a fitted 
x 
a 
parm 
For For 
level 
the confidence level required. Observe that the model has to be
profiled in the appropriate region; otherwise the limits are

trace 
logical. Should profiling be traced? Defaults to 
alpha 
Determines the range of profiling. By default the likelihood is profiled approximately in the 99% confidence interval region as determined by the Wald approximation. This is usually sufficient for 95% profile likelihood confidence limits. 
range 
if range is specified, this overrules the range
computation based on 
nSteps 
the number of points at which to profile the likelihood function. This determines the resolution and accuracy of the profile likelihood function; higher values gives a higher resolution, but also longer computation times. 
Log 
should the profile likelihood be plotted on the logscale? 
relative 
should the relative or the absolute likelihood be plotted? 
fig 
should the profile likelihood be plotted? 
n 
the no. points used in the spline interpolation of the profile likelihood for plotting. 
ylim 
overrules default ylimits on the plot of the profile likelihood. 
... 
additional argument(s), e.g. graphical parameters for the

A confint.clmm2
method deliberately does not exist due to the
time consuming nature of the computations. The user is required to
compute the profile object first and then call confint
on the
profile object to obtain profile likelihood confidence intervals.
In plot.profile.clm2
: at least one of Log
and
relative
arguments have to be TRUE
.
confint
:
A matrix with columns giving lower and upper confidence
limits. These will be labelled as (1level)/2 and
1  (1level)/2 in % (by default 2.5% and 97.5%).
plot.profile.clm2
invisibly returns the profile object.
Rune Haubo B Christensen
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21  options(contrasts = c("contr.treatment", "contr.poly"))
if(require(lme4)) { ## access cbpp data
cbpp2 < rbind(cbpp[,(2:3)], cbpp[,(2:3)])
cbpp2 < within(cbpp2, {
incidence < as.factor(rep(0:1, each=nrow(cbpp)))
freq < with(cbpp, c(incidence, size  incidence))
})
## Fit with Laplace approximation:
fm1 < clmm2(incidence ~ period, random = herd, weights = freq,
data = cbpp2, Hess = 1)
pr.fm1 < profile(fm1)
confint(pr.fm1)
par(mfrow = c(2,2))
plot(pr.fm1)
plot(pr.fm1, Log=TRUE, relative = TRUE)
plot(pr.fm1, Log=TRUE, relative = FALSE)
}

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