ci.pairs.mult

Computes adjusted Wald confidence intervals for pairwise proportion
differences of a multinomial variable in a single sample. These adjusted
Wald confidence intervals use the same method that is used to compare the
two proportions in a paired-samples design.
For more details, see Section 1.12 of Bonett (2021, Volume 3)

Implements confidence interval and sample size methods that are especially
useful in psychological research but are also useful in educational, social science,
business, and biological research. This package includes more than 100 confidence
interval functions and more than 80 sample size functions for 1-group, 2-group,
paired-samples, and multiple-group designs and for a variety of parameters including
means, medians, proportions, slopes, standardized mean differences, standardized
linear contrasts of means, and several measures of correlation and association. 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 about these methods 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.pairs.mult function

<dl><dt>alpha</dt>
<dd>alpha level for 1-alpha confidence</dd>
<dt>f</dt>
<dd>vector of multinomial frequency counts</dd></dl>

Arguments

Confidence intervals for pairwise proportion differences of a
multinomial variable — ci.pairs.mult

<dl>

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


<dt>f</dt>
<dd>vector of multinomial frequency counts</dd>

</dl>

ci.pairs.mult: Confidence intervals for pairwise proportion differences of a multinomial variable

Description

Usage

Value

Arguments

References

Examples