{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T15:36:02Z","timestamp":1778945762967,"version":"3.51.4"},"reference-count":41,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2016,12,14]],"date-time":"2016-12-14T00:00:00Z","timestamp":1481673600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"VA Office of Geriatrics and Extended Care","award":["3620160"],"award-info":[{"award-number":["3620160"]}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Health Services Research"],"published-print":{"date-parts":[[2018,2]]},"abstract":"<jats:sec><jats:title>Objective<\/jats:title><jats:p>To provide an alternative to propensity scoring (<jats:styled-content style=\"fixed-case\">PS<\/jats:styled-content>) for the common situation where there are interacting covariates.<\/jats:p><\/jats:sec><jats:sec><jats:title>Setting<\/jats:title><jats:p>We used 1.3 million assessments of residents of the United States Veterans Affairs nursing homes, collected from January 1, 2000, through October 9, 2012.<\/jats:p><\/jats:sec><jats:sec><jats:title>Design<\/jats:title><jats:p>In stratified covariate balancing (<jats:styled-content style=\"fixed-case\">SCB<\/jats:styled-content>), data are divided into naturally occurring strata, where each stratum is an observed combination of the covariates. Within each stratum, cases with, and controls without, the target event are counted; controls are weighted to be as frequent as cases. This weighting procedure guarantees that covariates, or combination of covariates, are balanced, meaning they occur at the same rate among cases and controls. Finally, impact of the target event is calculated in the weighted data. We compare the performance of<jats:styled-content style=\"fixed-case\">SCB<\/jats:styled-content>, logistic regression (<jats:styled-content style=\"fixed-case\">LR<\/jats:styled-content>), and propensity scoring (<jats:styled-content style=\"fixed-case\">PS<\/jats:styled-content>) in simulated and real data. We examined the calibration of<jats:styled-content style=\"fixed-case\">SCB<\/jats:styled-content>and<jats:styled-content style=\"fixed-case\">PS<\/jats:styled-content>in predicting 6\u2010month mortality from inability to eat, controlling for age, gender, and nine other disabilities for 296,051 residents in Veterans Affairs nursing homes. We also performed a simulation study, where outcomes were randomly generated from treatment, 10 covariates, and increasing number of covariate interactions. The accuracy of<jats:styled-content style=\"fixed-case\">SCB<\/jats:styled-content>,<jats:styled-content style=\"fixed-case\">PS<\/jats:styled-content>, and<jats:styled-content style=\"fixed-case\">LR<\/jats:styled-content>in recovering the simulated treatment effect was reported.<\/jats:p><\/jats:sec><jats:sec><jats:title>Findings<\/jats:title><jats:p>In simulated environment, as the number of interactions among the covariates increased,<jats:styled-content style=\"fixed-case\">SCB<\/jats:styled-content>and properly specified<jats:styled-content style=\"fixed-case\">LR<\/jats:styled-content>remained accurate but pairwise<jats:styled-content style=\"fixed-case\">LR<\/jats:styled-content>and pairwise<jats:styled-content style=\"fixed-case\">PS<\/jats:styled-content>, the most common applications of these tools, performed poorly. In real data, application of<jats:styled-content style=\"fixed-case\">SCB<\/jats:styled-content>was practical.<jats:styled-content style=\"fixed-case\">SCB<\/jats:styled-content>was better calibrated than linear<jats:styled-content style=\"fixed-case\">PS<\/jats:styled-content>, the most common method of<jats:styled-content style=\"fixed-case\">PS<\/jats:styled-content>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>In environments where covariates interact,<jats:styled-content style=\"fixed-case\">SCB<\/jats:styled-content>is practical and more accurate than common methods of applying<jats:styled-content style=\"fixed-case\">LR<\/jats:styled-content>and<jats:styled-content style=\"fixed-case\">PS<\/jats:styled-content>.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1475-6773.12628","type":"journal-article","created":{"date-parts":[[2016,12,15]],"date-time":"2016-12-15T16:41:03Z","timestamp":1481820063000},"page":"273-292","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Covariate Balancing through Naturally Occurring Strata"],"prefix":"10.1111","volume":"53","author":[{"given":"Farrokh","family":"Alemi","sequence":"first","affiliation":[{"name":"Department of Health Administration and Policy George Mason University Fairfax VA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amr","family":"ElRafey","sequence":"additional","affiliation":[{"name":"Department of Health Administration and Policy George Mason University Fairfax VA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ivan","family":"Avramovic","sequence":"additional","affiliation":[{"name":"Department of Computer Science George Mason University Fairfax VA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2016,12,14]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-0262.2006.00655.x"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1198\/jbes.2009.07333"},{"key":"e_1_2_6_4_1","doi-asserted-by":"crossref","unstructured":"Agrawal R. 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