# What is distance in Matchit?

Table of Contents

## What is distance in Matchit?

In general, it’s the distance metric used for matching. The difference between the distance metrics for a pair of individuals is the distance between them. The default is the estimated propensity score for each unit. You can set the value of the distance using the distance option.

## What is Mahalanobis distance matching?

Mahalanobis distance matching (MDM) and propensity score matching (PSM) are methods of doing the same thing, which is to find a subset of control units similar to treated units to arrive at a balanced sample (i.e., where the distribution of covariates is the same in both groups).

## What is subclass Matchit?

Description. In matchit() , setting method = “subclass” performs subclassification on the distance measure (i.e., propensity score). Treatment and control units are placed into subclasses based on quantiles of the propensity score in the treated group, in the control group, or overall, depending on the desired estimand …

## What is Caliper matching?

Caliper matching ( caliper ) Calipers are based on the propensity score or other covariates. Two units whose distance on a calipered covariate is larger than the caliper width for that covariate are not allowed to be matched to each other.

## What is coarsened exact matching?

Coarsened Exact Matching (CEM) offers an alternative solution, which is faster and easier to understand. It temporarily coarsens the data according to the researchers ideas (i.e. in coarse age groups rather than exact birthdays) and then finds exact matches.

## What is full matching?

Full matching makes use of all individuals in the data by forming a series of matched sets in which each set has either 1 treated individual and multiple comparison individuals or 1 comparison individual and multiple treated individuals.

## What is Mahalanobis metric matching?

SUMMARY. Monte Carlo methods are used to study the ability of nearest-available, Mahalanobis-metric matching to make the means of matching variables more similar in matched samples than in random samples.

## What is multivariate matching?

Multivariate matching is an analysis tool that is used to match different groups based on particular criteria, without selection bias, and compare them based on the treatment received. Multivariate matching has several beneficial abilities such as: Making data easy to understand.

## What is Matchit Vim?

This plugin provides extended matching for the % operator. This repository maintain the last version from the matchit. vim plugin from the official Vim repository, allowing to use with plugin managers.

## What is a matching method?

Matching is a statistical technique which is used to evaluate the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned).

## What caliper to use in propensity score matching?

The results of Monte Carlo simulations indicate that matching using a caliper width of 0.2 of the pooled standard deviation of the logit of the propensity score affords superior performance in the estimation of treatment effects.

## How does CEM work?

The idea of CEM is to temporarily coarsen each variable into substantively meaningful groups, exact match on these coarsened data and then only retain the original (uncoarsened) values of the matched data.

## How is the matching method implemented in Matchit?

Matching as implemented in MatchIt is a form of subset selection, that is, the pruning and weighting of units to arrive at a (weighted) subset of the units from the original dataset.

## Can a focal group be estimated in Matchit?

Typically, only the average treatment in the treated (ATT) or average treatment in the control (ATC), if the control group is the focal group, can be estimated after distance matching in MatchIt (full matching is an exception, described later).

## How does subset selection take place in Matchit?

In MatchIt, with almost all matching methods, subset selection is performed by stratification; for example, treated units are paired with control units, and unpaired units are then dropped from the matched sample.

## How are stratum memberships used in Matchit methods?

For methods that allow it, MatchIt includes stratum membership as an additional output of each matching specification. How these strata can be used is detailed in vignette (“Estimating Effects”). At the heart of MatchIt are three classes of methods: distance matching, stratum matching, and pure subset selection.