expon.slope

Computes confidence intervals for exp(B) - 1 (as a percent) and exp(B)
where B is a population slope coefficient in a binary logit, ordinal
logit, or log-Poisson model. This function is useful with software that
does not have an option to compute exp(B) and exp(B) - 1.

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

expon.slope function

<dl><dt>alpha</dt>
<dd>alpha level for 1-alpha confidence</dd>
<dt>b</dt>
<dd>estimated slope coefficient</dd>
<dt>se</dt>
<dd>slope standard error</dd></dl>

Arguments

Confidence interval for an exponentiated slope — expon.slope

<dl>

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


<dt>b</dt>
<dd>estimated slope coefficient</dd>


<dt>se</dt>
<dd>slope standard error</dd>

</dl>

expon.slope: Confidence interval for an exponentiated slope

Description

Usage

Value

Arguments

Examples