| CIsim {mosaic} | R Documentation | 
Compute confidence intervals from (multiple) simulated data sets
Description
This function automates the calculation of coverage rates for exploring the robustness of confidence interval methods.
Usage
CIsim(
  n,
  samples = 100,
  rdist = rnorm,
  args = list(),
  plot = if (samples <= 200) "draw" else "none",
  estimand = 0,
  conf.level = 0.95,
  method = t.test,
  method.args = list(),
  interval = function(x) {
     do.call(method, c(list(x, conf.level = conf.level),
    method.args))$conf.int
 },
  estimate = function(x) {
     do.call(method, c(list(x, conf.level = conf.level),
    method.args))$estimate
 },
  verbose = TRUE
)
Arguments
n | 
 size of each sample  | 
samples | 
 number of samples to simulate  | 
rdist | 
 function used to draw random samples  | 
args | 
 arguments required by   | 
plot | 
 one of   | 
estimand | 
 true value of the parameter being estimated  | 
conf.level | 
 confidence level for intervals  | 
method | 
 function used to compute intervals.  Standard functions that
produce an object of class   | 
method.args | 
 arguments required by   | 
interval | 
 a function that computes a confidence interval from data. Function should return a vector of length 2.  | 
estimate | 
 a function that computes an estimate from data  | 
verbose | 
 print summary to screen?  | 
Value
A data frame with variables
lower,
upper,
estimate,
cover ('Yes' or 'No'),
and
sample
is returned invisibly.  See the examples for a way to use this to display the intervals
graphically.
Examples
# 1000 95% intervals using t.test; population is N(0,1)
CIsim(n = 10, samples = 1000)    
# this time population is Exp(1); fewer samples, so we get a plot 
CIsim(n = 10, samples = 100, rdist = rexp, estimand = 1) 
# Binomial treats 1 like success, 0 like failure
CIsim(n = 30, samples = 100, rdist = rbinom, args = list(size = 1, prob = .7), 
       estimand = .7, method = binom.test, method.args = list(ci = "Plus4"))