summary.multisimsum: Summarising multisimsum objects

View source: R/summary.multisimsum.R

summary.multisimsumR Documentation

Summarising multisimsum objects


The summary() method for objects of class multisimsum returns confidence intervals for performance measures based on Monte Carlo standard errors.


## S3 method for class 'multisimsum'
summary(object, ci_level = 0.95, df = NULL, stats = NULL, ...)



An object of class multisimsum.


Significance level for confidence intervals based on Monte Carlo standard errors. Ignored if a multisimsum object with control parameter mcse = FALSE is passed.


Degrees of freedom of a t distribution that will be used to calculate confidence intervals based on Monte Carlo standard errors. If NULL (the default), quantiles of a Normal distribution will be used instead.


Summary statistics to include; can be a scalar value or a vector (for multiple summary statistics at once). Possible choices are:

  • nsim, the number of replications with non-missing point estimates and standard error.

  • thetamean, average point estimate.

  • thetamedian, median point estimate.

  • se2mean, average standard error.

  • se2median, median standard error.

  • bias, bias in point estimate.

  • empse, empirical standard error.

  • mse, mean squared error.

  • relprec, percentage gain in precision relative to the reference method.

  • modelse, model-based standard error.

  • relerror, relative percentage error in standard error.

  • cover, coverage of a nominal level\

  • becover, bias corrected coverage of a nominal level\

  • power, power of a (1 - level)\ Defaults to NULL, in which case all possible summary statistics are included.




An object of class summary.multisimsum.

See Also

multisimsum(), print.summary.multisimsum()


ms <- multisimsum(
  data = frailty, par = "par", true = c(
    trt = -0.50,
    fv = 0.75
  ), estvarname = "b", se = "se", methodvar = "model",
  by = "fv_dist"
sms <- summary(ms)

rsimsum documentation built on March 22, 2022, 5:08 p.m.