{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T03:30:10Z","timestamp":1792207810352,"version":"4.4.0"},"reference-count":23,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100009827","name":"Laura and John Arnold Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009827","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"National Institute of Mental Health","doi-asserted-by":"publisher","award":["T32MH019733"],"award-info":[{"award-number":["T32MH019733"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Health Services Research"],"published-print":{"date-parts":[[2021,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To formalize comparative interrupted time series (CITS) using the potential outcomes framework; compare two version of CITS\u2014a standard linear version and one that adds postperiod group\u2010by\u2010time parameters\u2014to two versions of difference\u2010in\u2010differences (DID)\u2014a standard version with time fixed effects and one that adds group\u2010specific pretrends; and reanalyze three previously published papers using these models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data Sources<\/jats:title>\n                    <jats:p>Outcome data for reanalyses come from two counties' jail booking and release data, Medicaid prescription drug rebate data from the Centers for Medicare and Medicaid Services (CMS), and acute hepatitis C incidence from the Centers for Disease Control and Prevention.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Design<\/jats:title>\n                    <jats:p>DID and CITS were compared using potential outcomes, and reanalyses were conducted using the four described pre\u2013post study designs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data Collection\/Extraction Methods<\/jats:title>\n                    <jats:p>Data from county jails were provided by sheriffs. Data from CMS are publicly available. Data for the third reanalysis were provided by the authors of the original study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Principal Findings<\/jats:title>\n                    <jats:p>Though written differently and preferred by different research communities, the general version of CITS and DID with group\u2010specific pretrends are the same: they yield the same counterfactuals and identify the same treatment effects. In a reanalysis with evidence of divergent preperiod trends, failing to account for this in standard DID led to an 84% smaller effect estimate than the more flexible models. In a second reanalysis with evidence of nonlinear outcome trends, failing to account for this in linear CITS led to a 28% smaller effect estimate than the more flexible models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We recommend detailing a causal model for treatment selection and outcome generation and the required counterfactuals before choosing an analytical approach. The more flexible versions of DID and CITS can accommodate features often found in real data, namely, nonlinearities and divergent preperiod outcome trends.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/1475-6773.13697","type":"journal-article","created":{"date-parts":[[2021,7,2]],"date-time":"2021-07-02T05:00:36Z","timestamp":1625202036000},"page":"942-952","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Birds of a feather flock together: Comparing controlled pre\u2013post designs"],"prefix":"10.1111","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0661-847X","authenticated-orcid":false,"given":"Carrie E.","family":"Fry","sequence":"first","affiliation":[{"name":"Interfaculty Initiative in Health Policy Harvard University  Cambridge Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura A.","family":"Hatfield","sequence":"additional","affiliation":[{"name":"Department of Health Care Policy Harvard Medical School  Boston Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,7]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-publhealth-040617-013507"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-publhealth-031816-044327"},{"issue":"4","key":"e_1_2_7_4_1","first-page":"604","article-title":"Evaluating the econometric evaluations of training programs with experimental data","volume":"76","author":"LaLonde RJ","year":"1986","journal-title":"Am Econ Rev"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/pam.20375"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1177\/1098214014527337"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2014.10.003"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1086\/689868"},{"key":"e_1_2_7_9_1","volume-title":"The Effects of Medicaid Expansion under the ACA: Updated Findings from a Literature Review","author":"Antonisse L","year":"2019"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1515\/9781400829828"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-economics-080217-053402"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.healthpol.2014.10.006"},{"key":"e_1_2_7_13_1","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyz049"},{"key":"e_1_2_7_14_1","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyz050"},{"key":"e_1_2_7_15_1","doi-asserted-by":"publisher","DOI":"10.5888\/pcd12.150187"},{"key":"e_1_2_7_16_1","doi-asserted-by":"publisher","DOI":"10.1080\/07474938.2017.1348683"},{"key":"e_1_2_7_17_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-0262.2006.00668.x"},{"key":"e_1_2_7_18_1","doi-asserted-by":"crossref","unstructured":"BaickerK SvoronosT.Testing the validity of the single interrupted time series design. 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