hdslcse.fast: Hazard discrimination summary (local constant) standard error...
In hds: Hazard Discrimination Summary

Description Usage Arguments Details Value

hdslcse.fast calculates an estimate of the variance for the local constant hazard discrimination summary estimator at a time t. The time t is implied by S, betahat, and betahatse

1	hdslcse.fast(S, betahat, m, betahatse)

`S`	A vector of length `nrow(m)` (which is typically the number of observations n), where each value is the subject-specific survival at time t where t is implied by the choice of `betahat`.
`betahat`	A p x 1 vector of coefficient estimates at time t of interest from the local-in-time Cox model. Vector length p is the number of covariates. Typically the output from `hdslc::finda` is passed here.
`m`	A numeric n x p matrix of covariate values, with a column for each covariate and each observation is on a separate row.
`betahatse`	A p x p covariance matrix for betahat at time t

The use will typically not interact with this function directly. Instead this function is wrapped by hdslc.

Variance estimate that has not been normalized. To get a usable standard error estimate, divide the output of this function by the bandwidth and sample size, and then take the square root.

hds documentation built on May 2, 2019, 9:44 a.m.