confintOld: Confidence intervals and profile likelihoods for parameters...
In ordinal: Regression Models for Ordinal Data

Description Usage Arguments Details Value Author(s) See Also Examples

Computes confidence intervals from the profiled likelihood for one or more parameters in a fitted cumulative link model, or plots the profile likelihood function.

## S3 method for class 'clm2'
confint(object, parm, level = 0.95, whichL = seq_len(p),
        whichS = seq_len(k), lambda = TRUE, trace = 0, ...)

## S3 method for class 'profile.clm2'
confint(object, parm = seq_along(Pnames), level = 0.95, ...)

## S3 method for class 'clm2'
profile(fitted, whichL = seq_len(p), whichS = seq_len(k),
        lambda = TRUE, alpha = 0.01, maxSteps = 50, delta = LrootMax/10,
        trace = 0, stepWarn = 8, ...)

## S3 method for class 'profile.clm2'
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 `clm2` object or a `profile.clm2` object.
`fitted`	a fitted `clm2` object.
`x`	a `profile.clm2` object.
`parm`	not used in `confint.clm2`. For `confint.profile.clm2`: a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered. For `plot.profile.clm2`: a specification of which parameters the profile likelihood are to be plotted for, either a vector of numbers or a vector of names. If missing, all parameters are considered.
`level`	the confidence level required.
`whichL`	a specification of which location parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all location parameters are considered.
`whichS`	a specification of which scale parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all scale parameters are considered.
`lambda`	logical. Should profile or confidence intervals be computed for the link function parameter? Only used when one of the flexible link functions are used; see the `link`-argument in `clm2`.
`trace`	logical. Should profiling be traced?
`alpha`	Determines the range of profiling. By default the likelihood is profiled in the 99% confidence interval region as determined by the profile likelihood.
`maxSteps`	the maximum number of profiling steps in each direction (up and down) for each parameter.
`delta`	the length of profiling steps. To some extent this parameter determines the degree of accuracy of the profile likelihood in that smaller values, i.e. smaller steps gives a higher accuracy. Note however that a spline interpolation is used when constructing confidence intervals so fairly long steps can provide high accuracy.
`stepWarn`	a warning is issued if the no. steps in each direction (up or down) for a parameter is less than `stepWarn` (defaults to 8 steps) because this indicates an unreliable profile.
`Log`	should the profile likelihood be plotted on the log-scale?
`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.
`ylim`	overrules default y-limits on the plot of the profile likelihood.
`...`	additional argument(s) for methods including `range` (for the hidden function `profileLambda`) that sets the range of values of `lambda` at which the likelihood should be profiled for this parameter.

These confint methods call the appropriate profile method, then finds the confidence intervals by interpolation of the profile traces. If the profile object is already available, this should be used as the main argument rather than the fitted model object itself.

In plot.profile.clm2: at least one of Log and relative arguments have to be TRUE.

confint: A matrix (or vector) with columns giving lower and upper confidence limits for each parameter. These will be labelled as (1-level)/2 and 1 - (1-level)/2 in % (by default 2.5% and 97.5%). The parameter names are preceded with "loc." or "sca." to indicate whether the confidence interval applies to a location or a scale parameter.

plot.profile.clm2 invisibly returns the profile object.

Rune Haubo B Christensen

profile and confint

options(contrasts = c("contr.treatment", "contr.poly"))

## More manageable data set:
(tab26 <- with(soup, table("Product" = PROD, "Response" = SURENESS)))
dimnames(tab26)[[2]] <- c("Sure", "Not Sure", "Guess", "Guess", "Not Sure", "Sure")
dat26 <- expand.grid(sureness = as.factor(1:6), prod = c("Ref", "Test"))
dat26$wghts <- c(t(tab26))

m1 <- clm2(sureness ~ prod, scale = ~prod, data = dat26,
          weights = wghts, link = "logistic")

## profile
pr1 <- profile(m1)
par(mfrow = c(2, 2))
plot(pr1)

m9 <- update(m1, link = "log-gamma")
pr9 <- profile(m9, whichL = numeric(0), whichS = numeric(0))
par(mfrow = c(1, 1))
plot(pr9)

plot(pr9, Log=TRUE, relative = TRUE)
plot(pr9, Log=TRUE, relative = TRUE, ylim = c(-4, 0))
plot(pr9, Log=TRUE, relative = FALSE)

## confint
confint(pr9)
confint(pr1)

## Extend example from polr in package MASS:
## Fit model from polr example:
if(require(MASS)) {
    fm1 <- clm2(Sat ~ Infl + Type + Cont, scale = ~ Cont, weights = Freq,
                data = housing)
    pr1 <- profile(fm1)
    confint(pr1)
    par(mfrow=c(2,2))
    plot(pr1)
}