Cem

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152 discussions

by Gary King

Hi Haakon, thanks for your note. If you match (i.e.,prune further) within and respecting CEM's strata, then you keep all the bias and model dependence reducing properties of CEM. The weights I think would have to be adjusted by using the same formulas we give, with whatever observations that are left after your second stage procedure. see j.mp/CEMweights on weights in general. Gary -- *Gary King* - Albert J. Weatherhead III University Professor - Director, IQSS <http://iq.harvard.edu/> - Harvard University GaryKing.org - King(a)Harvard.edu - @KingGary <https://twitter.com/kinggary> - 617-500-7570 - Assistant <king-assist(a)iq.harvard.edu>: 617-495-9271 On Thu, Feb 8, 2018 at 4:46 PM, Haakon Gjerløw <haakon.gjerlow(a)stv.uio.no> wrote: > Dear all, > > > > I have a question concerning the correct way to combine CEM with other > matching procedures. Specifically, I am trying to match a data set with > CEM, and then apply Entropy balancing to the remaining sample ( > https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1904869). It seems > such two-step balancing is hinted at in both Iacus, King, Porro (2011) and > Hainmuller (2012) > > > > My questions concerns the correct way to us the weights in regressions > after both procedures are done. > > > > My intuition says that this is basically a two-step sampling procedure, > and that the correct way to use the weights is to multiply the weights from > CEM with the weights from Entropy (Solution A). > > However, it might also be that the Entropy Balancing is overriding the > weights from CEM, and the observations should only be weighted by the > weights from Entropy (Solution B) > > > > Have any of you investigated this in a more systematic/formal fashion? > > > > All the best, > > Haakon Gjerløw | Phd fellow > > Department of Political Science | University of Oslo > > > > >

6 years, 3 months

Re: [cem] Cem Digest, Vol 99, Issue 1 Combining matching procedures

by cesare riillo

My feeling is that if you apply Entropy Balancing on CEM matched observations you should combine CEM and Entropy balancing weights. -your solution ( A)-. At least I did so in the case of CEM and complex survey weights in Beyond the question “Does it pay to be green?”: How much green? and when? - ScienceDirect | | | | Beyond the question “Does it pay to be green?”: How much green? and when... | | | please note that there is a typo in page 631, ( the formula for weighted controls after CEM is not reporting "*swi". But I am also really interested to the topic and would appreciate some more formal reference. In any case, if Entropy Balancing balances covariates with respect to the first, second moment and possibly higher moments while BEM bounds all centered absolute moments. In this sense, I expect that applying the two methods separately will provide consistent results. Hope it can help Cesare On Friday, 9 February 2018, 18:00:07 CET, cem-request(a)lists.gking.harvard.edu <cem-request(a)lists.gking.harvard.edu> wrote: Send Cem mailing list submissions to cem(a)lists.gking.harvard.edu To subscribe or unsubscribe via the World Wide Web, visit https://lists.gking.harvard.edu/mailman/listinfo/cem or, via email, send a message with subject or body 'help' to cem-request(a)lists.gking.harvard.edu You can reach the person managing the list at cem-owner(a)lists.gking.harvard.edu When replying, please edit your Subject line so it is more specific than "Re: Contents of Cem digest..." Today's Topics: 1. Combining matching procedures (Haakon Gjerl?w) ---------------------------------------------------------------------- Message: 1 Date: Thu, 8 Feb 2018 21:46:55 +0000 From: Haakon Gjerl?w <haakon.gjerlow(a)stv.uio.no> To: "cem(a)lists.gking.harvard.edu" <cem(a)lists.gking.harvard.edu> Subject: [cem] Combining matching procedures Message-ID: <26d789a592874d86a9c300711e316aa4(a)mail-ex02.exprod.uio.no> Content-Type: text/plain; charset="iso-8859-1" Dear all, I have a question concerning the correct way to combine CEM with other matching procedures. Specifically, I am trying to match a data set with CEM, and then apply Entropy balancing to the remaining sample (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1904869). It seems such two-step balancing is hinted at in both Iacus, King, Porro (2011) and Hainmuller (2012) My questions concerns the correct way to us the weights in regressions after both procedures are done. My intuition says that this is basically a two-step sampling procedure, and that the correct way to use the weights is to multiply the weights from CEM with the weights from Entropy (Solution A). However, it might also be that the Entropy Balancing is overriding the weights from CEM, and the observations should only be weighted by the weights from Entropy (Solution B) Have any of you investigated this in a more systematic/formal fashion? All the best, Haakon Gjerl?w | Phd fellow Department of Political Science | University of Oslo

6 years, 3 months

Combining matching procedures

by Haakon Gjerløw

Dear all, I have a question concerning the correct way to combine CEM with other matching procedures. Specifically, I am trying to match a data set with CEM, and then apply Entropy balancing to the remaining sample (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1904869). It seems such two-step balancing is hinted at in both Iacus, King, Porro (2011) and Hainmuller (2012) My questions concerns the correct way to us the weights in regressions after both procedures are done. My intuition says that this is basically a two-step sampling procedure, and that the correct way to use the weights is to multiply the weights from CEM with the weights from Entropy (Solution A). However, it might also be that the Entropy Balancing is overriding the weights from CEM, and the observations should only be weighted by the weights from Entropy (Solution B) Have any of you investigated this in a more systematic/formal fashion? All the best, Haakon Gjerløw | Phd fellow Department of Political Science | University of Oslo

6 years, 3 months

Re: [cem] cem_matched ==1 and cem_strata==. <missing>

by Matt Blackwell

Hi there, This was an issue in an earlier version of CEM, but the latest version on SSC should have this fixed. Perhaps you can try to reinstall from the repo and see if it is still an issue? Note that the matching still works and cem_matched is correct in these situations. Hope that helps! Cheers, Matt On Thu, Jan 11, 2018 at 3:43 AM LEE Matthew <matthew.lee(a)insead.edu> wrote: > Dear all, > > I am writing to follow up on a past thread with the same subject line > (original message below). I have encountered the same issue in which after > calling cem in STATA, I have some observations for which cem_matched == 1 > but cem_strata is missing. I have not been able to solve it, but do have > some additional clues and would be interested to know if the community has > any ideas here. > > It seems that the cem command is truncating the assignment of cem_strata > at a fixed limit of 32,740 strata (I don’t know if this value is general or > specific to my data). When executing my original match (which has many > theoretical strata based on the coarsened variables: 28 buckets X 10 X 5 X > 5 X 5 X 5 = 175,000), the assignment of strata stops at 32,740. If I > coarsen further so that the number of theoretical buckets < 32,740 and > re-run CEM, there are no longer missing observations for cem_strata > (unfortunately this further coarsening does not work for my study). > > One more clue: the truncation appears to operate according to ordered > values of the first matching variable called by CEM. In my original > matching attempt described above, the first variable was a year variable, > which ranges from 2009-2013. In the results, the cem_strata values are > defined for 2009 and 2010 and stop somewhere in 2011 — subsequent years > have cem_strata missing. > > It would be great to know if anyone has further ideas about what might be > going wrong here. Does cem in STATA have a theoretical maximum number of > strata? Could it be a working memory issue? > > Many thanks, > > Matthew > > *Matthew Lee* > Assistant Professor of Strategy > INSEAD | 1 Ayer Rajah Avenue, Singapore 138676 > *matthew.lee(a)insead.edu <matthew.lee(a)insead.edu> | matthewscottlee.com > <https://urldefense.proofpoint.com/v2/url?u=http-3A__matthewscottlee.com&d=D…>* > > *--* > > https://lists.gking.harvard.edu/pipermail/cem/2014-September/000154.html > > Ben Hoen bhoen at lbl.gov > <https://urldefense.proofpoint.com/v2/url?u=http-3A__lbl.gov&d=DwMGaQ&c=WO-R…> > > Tue Sep 9 15:42:53 EDT 2014 > > Hi all, > > > > I had been using a cem matching output to run regressions and have just now > found that a large set of the output has the variable "cem_matched" ==1 > while the "cem_strata" ==. (a.k.a. missing). For those cases, there is > also > a weight stored in "cem_weights". > > > > Is this a common occurance? If so, would you be able to explain when/why > this occurs? > > > > Ben > > > > Ben Hoen > > Staff Research Associate > > Lawrence Berkeley National Laboratory > > Office: 845-758-1896 > > Cell: 718-812-7589 > > bhoen at lbl.gov > <https://urldefense.proofpoint.com/v2/url?u=http-3A__lbl.gov&d=DwMGaQ&c=WO-R…> > > <http://emp.lbl.gov/staff/ben-hoen > <https://urldefense.proofpoint.com/v2/url?u=http-3A__emp.lbl.gov_staff_ben-2…>> > http://emp.lbl.gov/staff/ben-hoen > <https://urldefense.proofpoint.com/v2/url?u=http-3A__emp.lbl.gov_staff_ben-2…> > > -- ----- Matthew Blackwell http://www.mattblackwell.org

6 years, 4 months

Re: [cem] n:n matching imbalance and large weights

by Gary King

Hi Scott, if the coarsening is reasonable then large weights just indicate lots of matches. It may be however that this is an opportunity to use more fine grained coarsening since the larger of the two treatment regimes isn't helping you that much. The reason is that the variance of a difference in means is mostly a function of the smaller of the two means. --- GaryKing.org 617-500-7570 <(617)%20500-7570> On Dec 29, 2017 9:16 AM, "Scott Smith" <scott.al.smith(a)gmail.com> wrote: In n:n coarsened exact matching, is there ever a situation where it makes more sense to exclude study members and their respective control members that have extremely large weights? For example, 500 study members match to just 25 control members. Might it be better to exclude both study and control members rather than introduce such large weights and variance to the rest of the study population? Thanks, -- Scott Smith

6 years, 4 months

n:n matching imbalance and large weights

by Scott Smith

In n:n coarsened exact matching, is there ever a situation where it makes more sense to exclude study members and their respective control members that have extremely large weights? For example, 500 study members match to just 25 control members. Might it be better to exclude both study and control members rather than introduce such large weights and variance to the rest of the study population? Thanks, -- Scott Smith

6 years, 4 months

Re: [cem] FDA Qualified for Scientific Use

by Gary King

Hi Carrie, The contact we have at the FDA is Richard A. Forshee, who is the Associate Director for Research at the Office of Biostatistics & Epidemiology, in the Center for Biologics Evaluation and Research. He arranged for the FDA to do this evaluation of CEM. They then evaluated the software, quizzed us about various features and processes, and they made their decision. Best of luck with your research, Gary -- *Gary King* - Albert J. Weatherhead III University Professor - Director, IQSS <http://iq.harvard.edu/> - Harvard University GaryKing.org - King(a)Harvard.edu - @KingGary <https://twitter.com/kinggary> - 617-500-7570 - Assistant <king-assist(a)iq.harvard.edu>: 617-495-9271 On Mon, Aug 28, 2017 at 1:18 PM, Carrie Bennette <cb11(a)uw.edu> wrote: > Hello, > > I'm very interested in using CEM for some projects evaluating oncology > therapies, some of which may be submitted to the FDA. Could someone provide > more context regarding the note on the CEM website that CEM has officially > been "Qualified for Scientific Use" by the U.S. Food and Drug > Administration as I've not seen this designation used before? I'm > particularly interested in understanding what criteria the FDA used in > granting this designation and, if applicable, which group within the FDA > (e.g. CDER, CBER, CDRH) granted it. > > Thanks! > Carrie > -- > *Carrie Bennette, PhD, MPH* > *Senior Methodologist, Quantitative Sciences, Flatiron Health* > *Affiliate Assistant Professor, Department of Pharmacy, University of > Washington* > >

6 years, 8 months

FDA Qualified for Scientific Use

by Carrie Bennette

Hello, I'm very interested in using CEM for some projects evaluating oncology therapies, some of which may be submitted to the FDA. Could someone provide more context regarding the note on the CEM website that CEM has officially been "Qualified for Scientific Use" by the U.S. Food and Drug Administration as I've not seen this designation used before? I'm particularly interested in understanding what criteria the FDA used in granting this designation and, if applicable, which group within the FDA (e.g. CDER, CBER, CDRH) granted it. Thanks! Carrie -- *Carrie Bennette, PhD, MPH* *Senior Methodologist, Quantitative Sciences, Flatiron Health* *Affiliate Assistant Professor, Department of Pharmacy, University of Washington*

6 years, 8 months

How to use CEM wisely on low-frequency events?

by fang zhang

Hi All, Could anybody provide some insights about CEM on low frequency events? We observe the results can be sensitive to how we match (quarterly event or annual) and the event rates is almost always lower for both (intervention and control) groups after match? Thanks, Fang

6 years, 10 months

Questions about CEM

by fang zhang

Hi All, I am really excited about the CEM and want to use it for a lot of future studies. I have two questions: 1. Which software performs the fastest comparing R, STATA and SAS macro? 2. I want to get a matched id so that I know which pair (case and control 1to 1 match) are matched together? Is it possible to obtain a data set has that column in the SAS macro or STATA? Thanks a lot! Fang

7 years, 1 month

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