the segmented variable of interest. If missing all the segmented variables are considered.
level
the confidence level required (default to 0.95).
rev.sgn
vector of logicals. The length should be equal to the length of parm; recycled otherwise.
when TRUE it is assumed that the current parm is `minus' the actual segmented variable,
therefore the sign is reversed before printing. This is useful when a null-constraint has been set on the last slope.
var.diff
logical. If var.diff=TRUE and there is a single segmented variable, the standard error is
based on sandwich-type formula of the covariance matrix. See Details in summary.segmented.
digits
controls the number of digits to print when printing the output.
…
additional parameters
Value
A list of matrices. Each matrix includes point estimate and confidence limits of the breakpoint(s) for each
segmented variable in the model.
Details
Currently confint.segmented computes confidence limits for the breakpoints using the standard error coming from the Delta
method for the ratio of two random variables. This value is an approximation (slightly) better than the
one reported in the `psi' component of the list returned by any segmented method. The resulting
confidence intervals are based on the asymptotic Normal distribution of the breakpoint
estimator which is reliable just for clear-cut kink relationships. See Details in segmented.
See Also
segmented and lines.segmented to plot the estimated breakpoints with corresponding
confidence intervals.