predict.crrQR: Estimate subdistribution functions from crrQR output
In cmprskQR: Analysis of Competing Risks Using Quantile Regressions

Description Usage Arguments Details Value References See Also

predict method for crrQR

1 2	## S3 method for class 'crrQR' predict(object, x, rearrangement, ...)

`object`	output from crrQR
`x`	vector of covariate values for which the conditional distribution function is to be estimated. The columns of x must be named the same as in the original call to crrQR. Each must be given if present in the original call to crrQR.
`rearrangement`	set rearrangement=TRUE to perform a rearrangement of the predicted probabilities as suggested in Chernozhukov V, Fernández-Val I and Galichon A (2010).
`...`	additional parameters (currently ignored).

Computes the conditional estimate given values of covariates from sup(τ: τ ≤q ζ_(x,j)^(-1)[ln(t)]), for ζ_(x,j)(τ) = x'β_j(τ) (see Dlugosz S, Lo S and Wilke RA (2014) for details)

Returns a matrix with the unique type 1 failure times in the first column, and the other columns giving the estimated subdistribution function corresponding to the covariate combinations in the rows of x, at each failure time (the value that the estimate jumps to at that failure time).

Chernozhukov V, Fernández-Val I and Galichon A (2010) Quantile and probability curves without crossing. Econometrica 78, 1093-1125.

Dlugosz S, Lo S, Wilke RA (2014) Competing risks quantile regression at work: In-depth exploration of the role of public child support for the duration of maternity leave. unpublished.

crrQR plot.predict.crrQR

cmprskQR documentation built on Sept. 15, 2019, 5:02 p.m.