Description Usage Format References Examples
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 loghazard 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 RoystonParmar (Royston and Parmar, 2002) model with two degrees of freedom were fit to each simulated dataset.
1 
A data frame with 12,000 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 (Cox
, Exp
, or RP(2)
).
theta
Point estimate for the loghazard ratio.
se
Standard error of the point estimate.
Cox D.R. 1972. Regression models and lifetables. Journal of the Royal Statistical Society, Series B (Methodological) 34(2):187220. http://www.jstor.org/stable/2985181
Royston, P. and Parmar, M.K. 2002. Flexible parametric proportionalhazards and proportionalodds models for censored survival data, with application to prognostic modelling and estimation of treatment effects. Statistics in Medicine 21(15):21752197 doi: 10.1002/sim.1203
1  data("relhaz", package = "rsimsum")

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