smahal

This function computes the rank-based Mahalanobis distance matrix
between each pair of observations in the data set. Called by
<code>matches</code> (and ultimately <code>opt_nearfar</code>)
function to set up a distance matrix used to create pair matches.

Near-far matching is a study design technique for preprocessing observational data to mimic a pair-randomized trial. Individuals are matched to be near on measured confounders and far on levels of an instrumental variable. Methods outlined in further detail in Rigdon, Baiocchi, and Basu (2018) <doi:10.18637/jss.v086.c05>.

Joseph Rigdon

nearfar

Near-Far Matching

smahal function

<dl> <dt>X</dt>
<dd>A matrix of observed confounders with n rows (observations) and p columns (variables)</dd></dl>

Arguments

Compute rank-based Mahalanobis distance matrix between each pair — smahal

<dl>

 <dt>X</dt>
<dd>A matrix of observed confounders with n rows (observations) and p columns (variables)</dd>

</dl>

smahal: Compute rank-based Mahalanobis distance matrix between each pair

Description

Usage

Value

Arguments

Examples