ci.condslope.log

Computes confidence intervals and test statistics for population
conditional slopes (simple slopes) in a logistic model that
includes a predictor variable (x1), a moderator variable (x2),
and a product predictor variable (x1*x2). Conditional slopes are
computed at low and high values of the moderator variable.

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.condslope.log function

<dl><dt>alpha</dt>
<dd>alpha level for 1-alpha confidence</dd>
<dt>b1</dt>
<dd>estimated slope coefficient for predictor variable</dd>
<dt>b2</dt>
<dd>estimated slope coefficient for product variable</dd>
<dt>se1</dt>
<dd>standard error for predictor coefficient</dd>
<dt>se2</dt>
<dd>standard error for product coefficient</dd>
<dt>cov</dt>
<dd>estimated covariance between predictor and product coefficients</dd>
<dt>lo</dt>
<dd>low value of moderator variable</dd>
<dt>hi</dt>
<dd>high value of moderator variable</dd></dl>

Arguments

Confidence intervals for conditional (simple) slopes in a logistic model — ci.condslope.log

<dl>

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


<dt>b1</dt>
<dd>estimated slope coefficient for predictor variable</dd>


<dt>b2</dt>
<dd>estimated slope coefficient for product variable</dd>


<dt>se1</dt>
<dd>standard error for predictor coefficient</dd>


<dt>se2</dt>
<dd>standard error for product coefficient</dd>


<dt>cov</dt>
<dd>estimated covariance between predictor and product coefficients</dd>


<dt>lo</dt>
<dd>low value of moderator variable</dd>


<dt>hi</dt>
<dd>high value of moderator variable</dd>

</dl>

ci.condslope.log: Confidence intervals for conditional (simple) slopes in a logistic model

Description

Usage

Value

Arguments

Examples