Compute confidence intervals from (multiple) simulated data sets
This function automates the calculation of coverage rates for exploring the robustness of confidence interval methods.
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
)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? |
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.
# 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"))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.