rsimsum (version 0.13.0)

summary.multisimsum: 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 multisimsum
summary(object, ci_level = 0.95, df = NULL, stats = NULL, ...)

Value

An object of class summary.multisimsum.

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.

• rbias, relative (to the true value) 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.

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