Description Usage Arguments Value Author(s) References Examples
Agresti-Coull (1998) intervals are a great way to get a quick and
non-terrible estimate of a proportion. They work by using a 'Wald' interval,
after the addition of 2 successes and 2 failures to the sample (other numbers
can be specified, via the wt
argument). This function creates a
Wald-style standard-error, after adding psuedo-responses.
1 | ac_se(logical_var, wt = 2)
|
logical_var |
A |
wt |
The number of successes and failures to add to the sample before construction of a Wald interval |
numeric
. An estimate of the sample's standard error.
Brendan Rocks rocks.brendan@gmail.com
Agresti, A., & Coull, B. A. (1998). Approximate is better than "exact" for interval estimation of binomial proportions. The American Statistician, 52(2), 119-126.
1 | ac_se(as.logical(round(runif(10))))
|
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