<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stefano M. Iacus</style></author><author><style face="normal" font="default" size="100%">Gary King</style></author><author><style face="normal" font="default" size="100%">Giuseppe Porro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multivariate Matching Methods That are Monotonic Imbalance Bounding</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of the American Statistical Association</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">106</style></volume><pages><style face="normal" font="default" size="100%">345-361</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We introduce a new &quot;Monotonic Imbalance Bounding&quot; (MIB) class of matching methods for causal inference with a surprisingly large number of attractive statistical properties. MIB generalizes and extends in several new directions the only existing class, &quot;Equal Percent Bias Reducing&quot; (EPBR), which is designed to satisfy weaker properties and only in expectation. We also offer strategies to obtain specific members of the MIB class, and analyze in more detail a member of this class, called Coarsened Exact Matching, whose properties we analyze from this new perspective. We offer a variety of analytical results and numerical simulations that demonstrate how members of the MIB class can dramatically improve inferences relative to EPBR-based matching methods.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">493</style></issue></record></records></xml>