ci.prop.inv

Computes an exact confidence interval for a population proportion
when inverse sampling has been used. An approximate standard error is
recovered from the confidence interval. With inverse sampling, the number
of participants who have the attribute (f) is predetermined and sampling
continues until f attains its prespecified value. With inverse sampling,
the sample size (n) will not be known in advance.

Implements confidence interval and sample size methods that
are especially useful in psychological research. The methods can be
applied in 1-group, 2-group, paired-samples, and multiple-group designs
and to a variety of parameters including means, medians, proportions,
slopes, standardized mean differences, standardized linear contrasts
of means, plus several measures of correlation and association.
Confidence interval and sample size functions are given for single
parameters as well as differences, ratios, and linear contrasts of
parameters. The sample size functions can be used to approximate the
sample size needed to estimate a parameter or function of parameters
with desired confidence interval precision or to perform a variety of
hypothesis tests (directional two-sided, equivalence, superiority,
noninferiority) with desired power. For details see: Statistical Methods
for Psychologists, Volumes 1 – 4, <https://dgbonett.sites.ucsc.edu/>.

Douglas G. Bonett

statpsych

Statistical Methods for Psychologists

Robert J. Calin-Jageman

ci.prop.inv function

<dl><dt>alpha</dt>
<dd>alpha level for 1-alpha confidence</dd>
<dt>f</dt>
<dd>number of participants who have the attribute (fixed)</dd>
<dt>n</dt>
<dd>sample size (random)</dd></dl>

Arguments

Confidence interval for a proportion using inverse sampling — ci.prop.inv

<dl>

<dt>alpha</dt>
<dd>alpha level for 1-alpha confidence</dd>


<dt>f</dt>
<dd>number of participants who have the attribute (fixed)</dd>


<dt>n</dt>
<dd>sample size (random)</dd>

</dl>

ci.prop.inv: Confidence interval for a proportion using inverse sampling

Description

Usage

Value

Arguments

References

Examples