probability_superiority

This function calculates the probability of superiority from
independent samples Cohen's d calculation.

probability

effect

size

superiority

Designed to help the user to determine the sensitivity of an proposed causal effect to unconsidered common causes. Users can create visualizations of sensitivity, effect sizes, and determine which pattern of effects would support a causal claim for between group differences. Number needed to treat formula from Kraemer H.C. & Kupfer D.J. (2006) <doi:10.1016/j.biopsych.2005.09.014>.

Erin M. Buchanan

ViSe

Visualizing Sensitivity

probability_superiority function

<dl><dt>d</dt>
<dd>the effect size</dd>
<dt>m1</dt>
<dd>mean group one</dd>
<dt>m2</dt>
<dd>mean group two</dd>
<dt>sd1</dt>
<dd>standard deviation group one</dd>
<dt>sd2</dt>
<dd>standard deviation group two</dd>
<dt>n1</dt>
<dd>sample size group one</dd>
<dt>n2</dt>
<dd>sample size group two</dd>
<dt>a</dt>
<dd>significance level</dd>
<dt>t</dt>
<dd>optional, calculate d from independent t, you must
include n1 and n2 for degrees of freedom</dd>
<dt>model</dt>
<dd>optional, calculate d from t.test for independent t,
you must still include n1 and n2</dd>
<dt>df</dt>
<dd>optional dataframe that includes the x_col and y_col</dd>
<dt>x_col</dt>
<dd>name of the column that contains the factor levels OR
a numeric vector of group 1 scores</dd>
<dt>y_col</dt>
<dd>name of the column that contains the dependent score OR
a numeric vector of group 2 scores</dd></dl>

Arguments

Probability of Superiority Calculation — probability_superiority

<dl>

<dt>d</dt>
<dd>the effect size</dd>


<dt>m1</dt>
<dd>mean group one</dd>


<dt>m2</dt>
<dd>mean group two</dd>


<dt>sd1</dt>
<dd>standard deviation group one</dd>


<dt>sd2</dt>
<dd>standard deviation group two</dd>


<dt>n1</dt>
<dd>sample size group one</dd>


<dt>n2</dt>
<dd>sample size group two</dd>


<dt>a</dt>
<dd>significance level</dd>


<dt>t</dt>
<dd>optional, calculate d from independent t, you must
include n1 and n2 for degrees of freedom</dd>


<dt>model</dt>
<dd>optional, calculate d from t.test for independent t,
you must still include n1 and n2</dd>


<dt>df</dt>
<dd>optional dataframe that includes the x_col and y_col</dd>


<dt>x_col</dt>
<dd>name of the column that contains the factor levels OR
a numeric vector of group 1 scores</dd>


<dt>y_col</dt>
<dd>name of the column that contains the dependent score OR
a numeric vector of group 2 scores</dd>

</dl>

probability_superiority: Probability of Superiority Calculation

Description

Usage

Value

Arguments

Details

Examples