FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference

07/19/2017
by   Sudeepa Roy, et al.
0

A classical problem in causal inference is that of matching, where treatment units need to be matched to control units. Some of the main challenges in developing matching methods arise from the tension among (i) inclusion of as many covariates as possible in defining the matched groups, (ii) having matched groups with enough treated and control units for a valid estimate of Average Treatment Effect (ATE) in each group, and (iii) computing the matched pairs efficiently for large datasets. In this paper we propose a fast and novel method for approximate and exact matching in causal analysis called FLAME (Fast Large-scale Almost Matching Exactly). We define an optimization objective for match quality, which gives preferences to matching on covariates that can be useful for predicting the outcome while encouraging as many matches as possible. FLAME aims to optimize our match quality measure, leveraging techniques that are natural for query processing in the area of database management. We provide two implementations of FLAME using SQL queries and bit-vector techniques.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/06/2021

dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference

dame-flame is a Python package for performing matching for observational...
research
04/17/2023

Asymptotics of Caliper Matching Estimators for Average Treatment Effects

Caliper matching is used to estimate causal effects of a binary treatmen...
research
02/23/2023

From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference

Our goal is to produce methods for observational causal inference that a...
research
05/02/2022

Robust inference for matching under rolling enrollment

Matching in observational studies faces complications when units enroll ...
research
10/09/2021

Group-matching algorithms for subjects and items

We consider the problem of constructing matched groups such that the res...
research
12/05/2018

Hypothesis Tests That Are Robust to Choice of Matching Method

A vast number of causal inference studies test hypotheses on treatment e...
research
09/11/2023

Demystifying Statistical Matching Algorithms for Big Data

Statistical matching is an effective method for estimating causal effect...

Please sign up or login with your details

Forgot password? Click here to reset