Simulated Survival and Hazard Analysis for time-dependent

Description

This package generates power for the Cox proportional hazards model by simulating survival events data with time dependent exposure status for subjects. A dichotomous exposure variable is considered with a single transition from unexposed to exposed status during the subject time's in the study.

Details

Author(s)

Danyi Xiong, Teeranan Pokaprakarn, Hiroto Udagawa, Nusrat Rabbee
Maintainer: Nusrat Rabbee <rabbee@berkeley.edu>

Examples

# Simulate a dataset of 600 subjects with time-dependent exposure without
# considering minimum follow-up time or minimum post-exposure follow-up time.
# Specifically, set the duration of the study to be 24 months; the median time to
# event for control group to be 24 months; exposure effect to be 0.3; median time
# to censoring to be 14 months; and exposure proportion to be 20%.

df1 <- tdSim.method1(N = 600, duration = 24, lambda = log(2)/24, rho = 1, 
   beta = 0.3, rateC = log(2)/14, exp.prop = 0.2, 
   prop.fullexp  = 0, maxrelexptime = 1, min.futime = 0,
   min.postexp.futime = 0)
   
# We recommend setting nSim to at least 500. It is set to 10 in the example to
# reduce run time for CRAN submission.

ret <- getpower.method1(nSim = 10, N = 600, b = 0.3, exp.prop = 0.2, 
	type = "td", scenario = " ", maxrelexptime = 1/6, min.futime = 4,
	min.postexp.futime = 4, output.fn = "output.csv")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(SimHaz)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/SimHaz/SimHaz-package.Rd_%03d_medium.png", width=480, height=480)
> ### Name: SimHaz-package
> ### Title: Simulated Survival and Hazard Analysis for time-dependent
> ### Aliases: SimHaz-package SimHaz
> 
> ### ** Examples
> 
> # Simulate a dataset of 600 subjects with time-dependent exposure without
> # considering minimum follow-up time or minimum post-exposure follow-up time.
> # Specifically, set the duration of the study to be 24 months; the median time to
> # event for control group to be 24 months; exposure effect to be 0.3; median time
> # to censoring to be 14 months; and exposure proportion to be 20%.
> 
> df1 <- tdSim.method1(N = 600, duration = 24, lambda = log(2)/24, rho = 1, 
+    beta = 0.3, rateC = log(2)/14, exp.prop = 0.2, 
+    prop.fullexp  = 0, maxrelexptime = 1, min.futime = 0,
+    min.postexp.futime = 0)
>    
> # We recommend setting nSim to at least 500. It is set to 10 in the example to
> # reduce run time for CRAN submission.
> 
> ret <- getpower.method1(nSim = 10, N = 600, b = 0.3, exp.prop = 0.2, 
+ 	type = "td", scenario = " ", maxrelexptime = 1/6, min.futime = 4,
+ 	min.postexp.futime = 4, output.fn = "output.csv")
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>