summary.simsum: Summarising simsum objects

Description Usage Arguments Value See Also Examples

View source: R/summary.simsum.R

Description

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

Usage

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

Arguments

object

An object of class simsum.

ci_level

Significance level for confidence intervals based on Monte Carlo standard errors. Ignored if a simsum 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. However, using Z-based or t-based confidence intervals is valid only for summary statistics such a bias and coverage. Confidence intervals for other quantities may not be appropriate, therefore their usage is not recommended.

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 variance.

  • se2median, median variance.

  • 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.simsum.

See Also

simsum(), print.summary.simsum()

Examples

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data("MIsim")
object <- simsum(
  data = MIsim, estvarname = "b", true = 0.5, se = "se",
  methodvar = "method"
)
xs <- summary(object)
xs

rsimsum documentation built on May 21, 2021, 5:06 p.m.