proportion2percentile

Rounds proportions to significant digits both near 0 and 1,
then converts to percentiles

Calculates a Mahalanobis distance for every row of a set of
outcome variables (Mahalanobis, 1936
<doi:10.1007/s13171-019-00164-5>). The conditional Mahalanobis
distance is calculated using a conditional covariance matrix (i.e., a
covariance matrix of the outcome variables after controlling for a set
of predictors). Plotting the output of the cond_maha() function can
help identify which elements of a profile are unusual after
controlling for the predictors.

W. Joel Schneider

unusualprofile

Calculates Conditional Mahalanobis Distances

Feng Ji

proportion2percentile function

<dl><dt>p</dt>
<dd>probability</dd>
<dt>digits</dt>
<dd>rounding digits. Defaults to 2</dd>
<dt>remove_leading_zero</dt>
<dd>Remove leading zero for small percentiles,
Defaults to TRUE</dd>
<dt>add_percent_character</dt>
<dd>Append percent character. Defaults to FALSE</dd></dl>

Arguments

Rounds proportions to significant digits both near 0 and 1,
then converts to percentiles — proportion2percentile

<dl>

<dt>p</dt>
<dd>probability</dd>


<dt>digits</dt>
<dd>rounding digits. Defaults to 2</dd>


<dt>remove_leading_zero</dt>
<dd>Remove leading zero for small percentiles,
Defaults to TRUE</dd>


<dt>add_percent_character</dt>
<dd>Append percent character. Defaults to FALSE</dd>

</dl>

proportion2percentile: Rounds proportions to significant digits both near 0 and 1, then converts to percentiles

Description

Usage

Value

Arguments

Examples