A dataset from a simulation study comparing frailty flexible parametric models fitted using penalised likelihood to semiparametric frailty models. Both models are fitted assuming a Gamma and a log-Normal frailty. One thousand datasets were simulated, each containing a binary treatment variable with a log-hazard ratio of -0.50. Clustered survival data was simulated assuming 50 clusters of 50 individuals each, with a mixture Weibull baseline hazard function and a frailty following either a Gamma or a Log-Normal distribution. The comparison involves estimates of the log-treatment effect, and estimates of heterogeneity (i.e. the estimated frailty variance).

`frailty`

A data frame with 16,000 rows and 6 variables:

`i`

Simulated dataset number.`b`

Point estimate.`se`

Standard error of the point estimate.`par`

The estimand.`trt`

is the log-treatment effect,`fv`

is the variance of the frailty.`fv_dist`

The true frailty distribution.`model`

Method used (`Cox, Gamma`

,`Cox, Log-Normal`

,`RP(P), Gamma`

, or`RP(P), Log-Normal`

).

# NOT RUN { data("frailty", package = "rsimsum") # }