m.out <- matchit(treat ~ re74+re75, data=lalonde, ratio=2)

table(m.out$treat, m.out$weights)

table(lalonde$treat, lalonde$married)

m.out <- matchit(treat ~ re74+re75, data=lalonde, ratio=2)

table(m.out$treat, m.out$weights)

table(m.out$treat, m.out$weights)

table(m.out$treat, m.out$weights)

Hi Katerina, I believe this page will give you the details: http://r.iq.harvard.edu/docs/matchit/2.4-20/How_Exactly_are.html Liz ------------------------------------------------------ Elizabeth A. Stuart Associate Dean for Education Professor Department of Mental Health Department of Biostatistics Department of Health Policy and Management Johns Hopkins Bloomberg School of Public Health estuart(a)jhu.edu www.biostat.jhsph.edu/~estuart On Jan 30, 2017, at 10:43 AM, Aikaterini Passa &lt;ap7014(a)gmail.com&gt; wrote: Dear Liz, Many thanks, again, for your input. If I can make one more question about the weights obtained by the R program as a result of incomplete 1-to-many matched pairs, how (what are the formulas) the program calculates them? Using the Lalonde data, and do 1-to-3 matching without replacement and without having an exact match, several matched pairs are incomplete because there are not enough control units. In SAS, gmatch and PSmatching are 2 macros to perform 1-to-many matching without replacement, but they do not calculate weights for you when matched pairs are incomplete. If you could share the formulas/rationale how one can manually calculate them it would be very appreciated. Many thanks for the help, Katerina m.out <- matchit(treat ~ re74+re75, data=lalonde, ratio=3, m.order="random") Warning message: In matchit2nearest(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, : Not enough control units for 3 matches for each treated unit when matching without replacement. Not all treated units will receive 3 matches 0.78 1 1.16 0 177 0 252 1 0 185 0 On Sun, Jan 29, 2017 at 1:26 PM, Elizabeth Stuart &lt;estuart(a)jhu.edu&gt; wrote: > Hi Katerina, > The reason those weights end up being 0.75 and 1.51 is that there aren’t > two times as many unmarried people in the control group as in the treatment > group; so 2:1 matching isn’t possible within both “married” groups, which > means matchit then provides those weights to account for that. (In other > words, because of the exact match, some people end up getting 1 match and > others get 2 matches, depending on their marital status), and so then the > weights account for that. > > > table(lalonde$treat, lalonde$married) > > 0 1 > 0 209 220 > 1 150 35 > > So short answer is that yes, the weights should definitely be used; > otherwise you won’t be reflecting the structure underlying the match and > your analyses won’t be accurate. > > Liz > > > ------------------------------------------------------ > Elizabeth A. Stuart > Associate Dean for Education > Professor > Department of Mental Health > Department of Biostatistics > Department of Health Policy and Management > Johns Hopkins Bloomberg School of Public Health > > estuart(a)jhu.edu > www.biostat.jhsph.edu/~estuart > > > > > > > > > > On Jan 29, 2017, at 12:22 PM, Aikaterini Passa &lt;ap7014(a)gmail.com&gt; wrote: > > Many thanks, Liz, for the response. > > In my case I also include an exact match on a variable when I perform the > 1-to-many without replacement matching. I also tried to incorporate an > exact match in your code, and as a result of that, the weights of the > control matched cases take different values. While I was rying to find an > explanation I came across Austin's 2008 article " *Assessing balance in > measured baseline covariates when using many-to-one matching on the > propensity-score". Because of the exact match there are several incomplete > 1-to-many (in our case 1-to-2) matched pairs and based on Austin's article > ignoring for incomplete matching can result into misleading balance > diagnostics. I am wondering if these weights should be also used in the > analyses. * > > *Many thanks for any feedback,* > > *Katerina* > > m.out <- matchit(treat ~ re74+re75, data=lalonde, ratio=2, > m.order="random", exact=c("married")) > 0 0.75 1 1.51 > 0 150 188 0 91 > 1 0 0 185 0 > > On Sat, Jan 28, 2017 at 12:32 PM, Elizabeth Stuart &lt;estuart(a)jhu.edu&gt; > wrote: > >> Dear Katerina, >> I’m not sure why you are getting weights that are not 0 or 1 for that. >> Here is some sample code using the lalonde data, which shows weights of >> only 0 or 1. >> >> > m.out <- matchit(treat ~ re74+re75, data=lalonde, ratio=2) >> >>>> >> 0 1 >> 0 59 370 >> 1 0 185 >> >> Liz >> >> >> >> >> On Jan 26, 2017, at 2:00 PM, Aikaterini Passa &lt;ap7014(a)gmail.com&gt; wrote: >> >> I have a similar question pertaining to the weights of matched groups. >> When performing *1-to-many* *matching without replacement*, the program >> gives weights to the matched controls other than 1. What these weights >> resemble in this scenario (1-to-many matching without replacement), and >> should they be incorporated in the analyses? Many thanks for your input. >> >> Katerina Passa >> >> On Thu, Jan 12, 2017 at 10:41 AM, Gary King &lt;king(a)harvard.edu&gt; wrote: >> >>> Hi Ignacio, here's the simplest explanation of weights I could come up >>> with for one method (CEM), but it applies more generally to matching with >>> replacement: j.mp/CEMweights >>> >>> >>> Gary >>> -- >>> *Gary King* - Albert J. Weatherhead III University Professor - >>> Director, IQSS <http://iq.harvard.edu/> - Harvard University >>> GaryKing.org <http://garyking.org/> - King(a)Harvard.edu - @KingGary >>> <https://twitter.com/kinggary> - 617-500-7570 <(617)%20500-7570> - >>> Assistant &lt;king-assist(a)iq.harvard.edu&gt;du>: 617-495-9271 <(617)%20495-9271> >>> >>> On Thu, Jan 12, 2017 at 9:59 AM, Ignacio Martinez &lt;ignacio82(a)gmail.com&gt; >>> wrote: >>> >>>> Hi everyone, >>>> >>>> >>>> When you do matching with replacement you have to use weights because >>>> some observations are used multiple times. Can somebody explain what would >>>> be the consequences of ignoring those weights when running OLS? My >>>> intuition is that I would end up with bias estimator. Is this correct? Is >>>> it possible to sign the bias? Is there a paper that discuss this? >>>> >>>> >>>> Thanks, >>>> >>>> >>>> Ignacio >>>> >>>> >>> >>> - >>> --- >>> MatchIt mailing list served by HUIT >>> List Address: matchit(a)lists.gking.harvard.edu >>> Subscribe/Unsubscribe: http://lists.gking.harvard.edu >>> /mailman/listinfo/ei >>> MatchIt Software and Documentation: http://gking.harvard.edu/matchit/ >>> Browse/Search <http://gking.harvard.edu/matchit/Browse/Search> List >>> Archive: http://lists.gking.harvard.edu/mailman/private/matchit/ >>> Matchit mailing list >>> Matchit(a)lists.gking.harvard.edu >>> >>> To unsubscribe from this list or get other information: >>> >>> https://lists.gking.harvard.edu/mailman/listinfo/matchit >>> >> >> - >> --- >> MatchIt mailing list served by HUIT >> List Address: matchit(a)lists.gking.harvard.edu >> Subscribe/Unsubscribe: http://lists.gking.harvard.edu >> /mailman/listinfo/ei >> MatchIt Software and Documentation: http://gking.harvard.edu/matchit/ >> Browse/Search List Archive: http://lists.gking.harvard.edu >> /mailman/private/matchit/ >> Matchit mailing list >> Matchit(a)lists.gking.harvard.edu >> >> To unsubscribe from this list or get other information: >> >> https://lists.gking.harvard.edu/mailman/listinfo/matchit >> >> >> > <Austin-2008-Pharmacoepidemiology_and_Drug_Safety.pdf> > > > - --- MatchIt mailing list served by HUIT List Address: matchit(a)lists.gking.harvard.edu Subscribe/Unsubscribe: http://lists.gking.harvard.edu/mailman/listinfo/ei MatchIt Software and Documentation: http://gking.harvard.edu/matchit/ Browse/Search List Archive: http://lists.gking.harvard. edu/mailman/private/matchit/ Matchit mailing list Matchit(a)lists.gking.harvard.edu To unsubscribe from this list or get other information: https://lists.gking.harvard.edu/mailman/listinfo/matchit