A dataset from a simulation study assessing the impact of misspecifying the baseline hazard in survival models on regression coefficients.
One thousand datasets were simulated, each containing a binary treatment variable with a log-hazard ratio of -0.50.
Survival data was simulated for two different sample sizes, 50 and 250 individuals, and under two different baseline hazard functions, exponential and Weibull.
Consequently, a Cox model (Cox, 1972), a fully parametric exponential model, and a Royston-Parmar (Royston and Parmar, 2002) model with two degrees of freedom were fit to each simulated dataset.
vignette("B-relhaz", package = "rsimsum") for more information.
A data frame with 1,200 rows and 6 variables:
dataset Simulated dataset number.
n Sample size of the simulate dataset.
baseline Baseline hazard function of the simulated dataset.
model Method used (
theta Point estimate for the log-hazard ratio.
se Standard error of the point estimate.
Cox D.R. 1972. Regression models and life-tables. Journal of the Royal Statistical Society, Series B (Methodological) 34(2):187-220. doi: 10.1007/978-1-4612-4380-9_37
Royston, P. and Parmar, M.K. 2002. Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects. Statistics in Medicine 21(15):2175-2197 doi: 10.1002/sim.1203
data("relhaz", package = "rsimsum")
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