crr.fit {QHScrnomo}

Fit A Competing Risks Regression Model

Description

Fits a competing risks regression model using the crr function from an existing cph object which can then be used to construct a nomogram.

Usage

crr.fit(fit, cencode = 0, failcode = 1)

Arguments

fit

A Cox proportional hazards regression model constructed from cph (by Frank Harrell)

cencode

The value of the status column that indicates a censored observation

failcode

The value of the status column that indicates the event of interest

Value

Returns a list of class cmprsk, with components:

coef

the estimated regression coefficients

loglik

log pseudo-liklihood evaluated at coef

lscore

derivitives of the log pseudo-likelihood evaluated at coef

inf

-second derivatives of the log pseudo-likelihood

var

estimated variance covariance matrix of coef

res

matrix of residuals giving the contribution to each score (columns) at each unique failure time (rows)

uftime

vector of unique failure times

bfitj

jumps in the Breslow-type estimate of the underlying sub-distribution cumulative hazard (used by predict.crr())

tfs

the tfs matrix (output of tf(), if used)

converged

TRUE if the iterative algorithm converged.

cencode

the value of the status indicator that indicates a censored observation

failcode

the value of the status indicator that indicates an event of interest

cph.f

regular survival model fitted by cph which is saved for function nomogram.crr to adjust lp for competing risks

cphdat

data used for cph model, where all predictors are represented in numeric format, which is used by function tenf.crr to do ten fold cross-validation

Note

This function requires that the rms package is attached

Author(s)

Michael W. Kattan, Ph.D. and Changhong Yu. Department of Quantitative Health Sciences, Cleveland Clinic

References

Michael W. Kattan, Glenn Heller and Murray F. Brennan (2003). A competing-risks nomogram for sarcoma-specific death following local recurrence. Statistics in Medicine. Stat Med. 2003;22:3515-3525.

See Also

cph crr nomogram.crr

Examples

dd <- datadist(prostate.dat)
options(datadist = "dd")
prostate.f <- cph(Surv(TIME_EVENT,EVENT_DOD == 1) ~ TX  + rcs(PSA,3) +
           BX_GLSN_CAT +  CLIN_STG + rcs(AGE,3) +
           RACE_AA, data = prostate.dat,
           x = TRUE, y = TRUE, surv = TRUE,time.inc = 144)
prostate.crr <- crr.fit(prostate.f, cencode = 0, failcode = 1)
prostate.crr