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Type: Package
Title: Cox Regression (Proportional Hazards Model) with Multiple Causes and Mixed Effects
Version: 1.1.1
Date: 2015-10-24
Author: Jing Peng
Maintainer: Jing Peng <pengjing@live.com>
Description: A high performance package estimating Cox Model when an even has more than one causes. It also supports random and fixed effects, tied events, and time-varying variables.
License: GPL (≥ 3)
LazyData: TRUE
Depends: R (≥ 3.1.0), Rcpp (≥ 0.12.0)
Imports: methods
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2015-10-24 07:11:57 UTC; Peng
Repository: CRAN
Date/Publication: 2015-10-24 09:32:41

Cox Regression (Proportional Hazards Model) with Multiple Causes and Mixed Effects

Description

A high performance package estimating Proportional Hazards Model when an even can have more than one causes, including support for random and fixed effects, tied events, and time-varying variables.

Usage

fastCox(head, formula, par = list(), data = NULL)

Arguments

head

A data frame with 4~5 columns: start, stop, event, weight, strata (optional).

formula

A formula specifying the independent variables

par

A optional list of parameters controlling the estimation process

data

The dataset, a data frame containing observations on the independent variables

Value

A list containing the estimated parameters

References

1. Jing Peng, Ashish Agarwal, Kartik Hosanagar, and Raghuram Iyengar. Towards Effective Information Diffusion on Social Media Platforms: A Dyadic Analysis of Network Embeddedness. Working Paper.

2. Jing Peng, Ashish Agarwal, Kartik Hosanagar, and Raghuram Iyengar. Toward Effective Social Contagion: A Micro Level Analysis of the Impact of Dyadic Network Relationship. In Proceedings of the 2014 International Conference on Information Systems.

Examples

# Simulate a dataset. lam=exp(x), suvtime depends on lam
x = rnorm(5000)
suvtime = -log(runif(length(x)))/exp(x)
# Censor 80% of events
thd = quantile(suvtime, 0.2)
event = as.numeric(suvtime <= thd)
suvtime[suvtime>thd] = thd

# The estimates of beta should be very close to 1, the true value
head = cbind(start=0,stop=suvtime,event=event,weight=1)
est = fastCox(head,~x)
print(est$result)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.