# redrank: Reduced rank proportional hazards model for competing risks... In hputter/mstate: Data Preparation, Estimation and Prediction in Multi-State Models

 redrank R Documentation

## Reduced rank proportional hazards model for competing risks and multi-state models

### Description

This function estimates regression coefficients in reduced rank proportional hazards models for competing risks and multi-state models.

### Usage

``````redrank(
redrank,
full = ~1,
data,
R,
strata = NULL,
Gamma.start,
method = "breslow",
eps = 1e-05,
print.level = 1
)
``````

### Arguments

 `redrank` Survival formula, starting with either Surv(time,status) ~ or with Surv(Tstart,Tstop,status) ~, followed by a formula containing covariates for which a reduced rank estimate is to be found `full` Optional, formula specifying that part which needs to be retained in the model (so not subject to reduced rank) `data` Object of class 'msdata', as prepared for instance by `msprep`, in which to interpret the `redrank` and, optionally, the `full` formulas `R` Numeric, indicating the rank of the solution `strata` Name of covariate to be used inside the `strata` part of `coxph` `Gamma.start` A matrix of dimension K x R, with K the number of transitions and R the rank, to be used as starting value `method` The method for handling ties in `coxph` `eps` Numeric value determining when the iterative algorithm is finished (when for two subsequent iterations the difference in log-likelihood is smaller than `eps`) `print.level` Determines how much output is written to the screen; 0: no output, 1: iterations, for each iteration solutions of Alpha, Gamma, log-likelihood, 2: also the Cox regression results

### Details

For details refer to Fiocco, Putter & van Houwelingen (2005, 2008).

### Value

A list with elements

 `Alpha` the Alpha matrix `Gamma` the Gamma matrix `Beta` the Beta matrix corresponding to `covariates` `Beta2` the Beta matrix corresponding to `fullcovs` `cox.itr1` the `coxph` object resulting from the last call giving `Alpha` `alphaX` the matrix of prognostic scores given by `Alpha`, n x R, with n number of subjects `niter` the number of iterations needed to reach convergence `df` the number of regression parameters estimated `loglik` the log-likelihood

### Author(s)

Marta Fiocco and Hein Putter H.Putter@lumc.nl

### References

Fiocco M, Putter H, van Houwelingen JC (2005). Reduced rank proportional hazards model for competing risks. Biostatistics 6, 465–478.

Fiocco M, Putter H, van Houwelingen HC (2008). Reduced-rank proportional hazards regression and simulation-based prediction for multi-state models. Statistics in Medicine 27, 4340–4358.

Putter H, Fiocco M, Geskus RB (2007). Tutorial in biostatistics: Competing risks and multi-state models. Statistics in Medicine 26, 2389–2430.

### Examples

``````
## Not run:
# This reproduces the results in Fiocco, Putter & van Houwelingen (2005)
# Takes a while to run
data(ebmt2)
# transition matrix for competing risks
tmat <- trans.comprisk(6,names=c("Relapse","GvHD","Bacterial","Viral","Fungal","Other"))
# preparing long dataset
ebmt2\$stat1 <- as.numeric(ebmt2\$status==1)
ebmt2\$stat2 <- as.numeric(ebmt2\$status==2)
ebmt2\$stat3 <- as.numeric(ebmt2\$status==3)
ebmt2\$stat4 <- as.numeric(ebmt2\$status==4)
ebmt2\$stat5 <- as.numeric(ebmt2\$status==5)
ebmt2\$stat6 <- as.numeric(ebmt2\$status==6)
covs <- c("dissub","match","tcd","year","age")
ebmtlong <- msprep(time=c(NA,rep("time",6)),
stat=c(NA,paste("stat",1:6,sep="")),
data=ebmt2,keep=covs,trans=tmat)

# The reduced rank 2 solution
rr2 <- redrank(Surv(Tstart,Tstop,status) ~ dissub+match+tcd+year+age,
data=ebmtlong, R=2)
rr3\$Alpha; rr3\$Gamma; rr3\$Beta; rr3\$loglik
# The reduced rank 3 solution
rr3 <- redrank(Surv(Tstart,Tstop,status) ~ dissub+match+tcd+year+age,
data=ebmtlong, R=3)
rr3\$Alpha; rr3\$Gamma; rr3\$Beta; rr3\$loglik
# The reduced rank 3 solution, with no reduction on age
rr3 <- redrank(Surv(Tstart,Tstop,status) ~ dissub+match+tcd+year, full=~age,
data=ebmtlong, R=3)
rr3\$Alpha; rr3\$Gamma; rr3\$Beta; rr3\$loglik
# The full rank solution
fullrank <- redrank(Surv(Tstart,Tstop,status) ~ dissub+match+tcd+year+age,
data=ebmtlong, R=6)
fullrank\$Beta; fullrank\$loglik

## End(Not run)

``````

hputter/mstate documentation built on July 15, 2024, 11:18 p.m.