[Forum SIS] DEC Statistics Seminar (Bocconi) - December 3rd

[Raffaella Piccarreta]

Dear all, 

We are glad to announce the next: 



DEC - Statistics Seminar 

Thursday, December 3rd 

Università Bocconi, 

Room 3-E4-SR03 

Via Rontgen 1 - 3rd floor 

Time: 1:00 pm ( please note that the seminar will start later than usual ) 



Gary King 

(Harvard University) 



Why Propensity Scores Should Not Be Used For Matching 

Abstract: 

Researchers use propensity score matching (PSM) as a data preprocessing step to selectively prune units prior to applying a model to estimate a causal effect. The goal of PSM is to reduce imbalance in the chosen pre-treatment covariates between the treated and control groups, thereby reducing the degree of model dependence and potential for bias. We show here that PSM often accomplishes the opposite of what is intended – increasing imbalance, inefficiency, model dependence, and bias. The weakness of PSM is that it attempts to approximate a completely randomized experiment, rather than, as with other matching methods, a more powerful fully blocked randomized experiment. PSM, unlike other matching methods, is thus blind to the often large portion of imbalance that could have been eliminated by approximating full blocking. Moreover, in data balanced enough to approximate complete randomization, either to begin with or after pruning some observations, PSM approximates random matching which turns out to increase imbalance. For other matching methods, the point where additional pruning increases imbalance occurs much later in the pruning process, when full blocking is approximated and there is no reason to prune, and so the danger is considerably less. We show that these problems with PSM occur even in data designed for PSM, with as few as two covariates, and in many real applications. Although these results suggest that researchers replace PSM with one of the other available methods when performing matching, propensity scores have many other productive uses. 

The talk summarizes a paper coauthored with Richard Nielsen (2015, in press). 



The DEC seminar calendar is available at http://www.unibocconi.eu/statseminar 




Kind regards, Raffaella Piccarreta and Isadora Antoniano 


-- 
*************************************************** 
Raffaella Piccarreta 
DEC - Department of Decision Sciences, 
Universita' L.Bocconi, via Guglielmo Röntgen 1 (3rd floor, room D1-09). 20136, Milano. 
email: piccarreta a unibocconi.it 
tel. +39-02-58365659 / fax +39-02-58365630 

Web page (ENGLISH VERSION): http://faculty.unibocconi.eu/raffaellapiccarreta/ 
(ITALIAN VERSION): http://faculty.unibocconi.it/raffaellapiccarreta/ 
*************************************************** 
-------------- parte successiva --------------
Un allegato HTML è stato rimosso...
URL: <http://www.stat.unipg.it/pipermail/sis/attachments/20151127/d963fb66/attachment.html>