ci.pairs.prop.bs

Computes adjusted Wald confidence intervals for all pairwise differences
of population proportions in a between-subjects design using a Bonferroni
adjusted alpha level.
For more details, see Section 2.7 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.prop.bs function

<dl><dt>alpha</dt>
<dd>alpha level for simultaneous 1-alpha confidence</dd>
<dt>f</dt>
<dd>vector of frequency counts of participants who have the attribute</dd>
<dt>n</dt>
<dd>vector of sample sizes</dd></dl>

Arguments

Bonferroni confidence intervals for all pairwise proportion differences
in a between-subjects design — ci.pairs.prop.bs

<dl>

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


<dt>f</dt>
<dd>vector of frequency counts of participants who have the attribute</dd>


<dt>n</dt>
<dd>vector of sample sizes</dd>

</dl>

ci.pairs.prop.bs: Bonferroni confidence intervals for all pairwise proportion differences in a between-subjects design

Description

Usage

Value

Arguments

References

Examples