slope {segmented}R Documentation

Slope estimates from segmented relationships

Description

Computes slopes of each `segmented' relationship in the fitted model.

Usage

slope(ogg, parm, conf.level = 0.95, rev.sgn=FALSE)

Arguments

ogg an object of class "segmented", returned by any segmented method.
parm the segmented variable whose slopes have to be computed. If missing all the segmented variables are considered.
conf.level the confidence level required.
rev.sgn vector of logicals. The length should be equal to the length of parm, but it is 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.

Details

To fit broken-line relationships, segmented uses a parameterization whose coefficients are not the slopes. Therefore given an object "segmented", slope computes point estimates, standard errors, t-values and confidence intervals of the slopes of each segmented relationship in the fitted model.

Value

slope returns a list of matrices. Each matrix represents a segmented relationship and its number of rows equal to the number of segments, while five columns summarize the results.

Note

The returned summary is based on limiting Gaussian distribution for the model parameters involved in the computations. Sometimes, even with large sample sizes such approximations are questionable (e.g., with small difference-in-slope parameters) and the results returned by slope might be unreliable. Therefore is responsability of the user to gauge the applicability of such asymptotic approximations. Anyway, the t values may be not assumed for testing purposes and they should be used just as guidelines to assess the estimate uncertainty.

Author(s)

Vito M. R. Muggeo, vmuggeo@dssm.unipa.it

References

Muggeo, V.M.R. (2003) Estimating regression models with unknown break-points. Statistics in Medicine 22, 3055–3071.

See Also

See also davies.test to test for a nonzero differece-in-slope parameter.

Examples


set.seed(16)
x<-1:100
y<-2+1.5*pmax(x-35,0)-1.5*pmax(x-70,0)+rnorm(100,0,3)
out<-glm(y~1)
out.seg<-segmented(out,seg.Z=~x,psi=list(x=c(20,80)))
## the slopes of the three segments....
slope(out.seg)
rm(x,y,out,out.seg)

[Package segmented version 0.2-4 Index]