summary.multisimsum: Summarising multisimsum objects

In rsimsum: Analysis of Simulation Studies Including Monte Carlo Error

Summarising multisimsum objects

Description

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

Usage

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

Arguments

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

Value

An object of class summary.multisimsum.

See Also

multisimsum(), print.summary.multisimsum()

Examples

data(frailty)
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)
sms

rsimsum documentation built on Aug. 17, 2022, 5:07 p.m.