{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T04:56:23Z","timestamp":1769144183789,"version":"3.49.0"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Epidemiol Perspect Innov"],"published-print":{"date-parts":[[2006,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In a series of papers, Robins and colleagues describe inverse probability of treatment weighted (IPTW) estimation in marginal structural models (MSMs), a method of causal analysis of longitudinal data based on counterfactual principles. This family of statistical techniques is similar in concept to weighting of survey data, except that the weights are estimated using study data rather than defined so as to reflect sampling design and post-stratification to an external population. Several decades ago Miettinen described an elementary method of causal analysis of case-control data based on indirect standardization. In this paper we extend the Miettinen approach using ideas closely related to IPTW estimation in MSMs. The technique is illustrated using data from a case-control study of oral contraceptives and myocardial infarction.<\/jats:p>","DOI":"10.1186\/1742-5573-3-2","type":"journal-article","created":{"date-parts":[[2006,2,4]],"date-time":"2006-02-04T19:15:09Z","timestamp":1139080509000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Causal analysis of case-control data"],"prefix":"10.1186","volume":"3","author":[{"given":"Stephen C","family":"Newman","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2006,1,27]]},"reference":[{"key":"18_CR1_18","unstructured":"Robins JM: Marginal structural models.\n                  1997 Proceedings of the Section on Bayesian Statistical Science Alexandria, VA, American Statistical Association 1998, 1\u201310."},{"key":"18_CR2_18","first-page":"95","volume-title":"Statistical Models in Epidemiology: the Environment and Clinical Trials","author":"JM Robins","year":"1999","unstructured":"Robins JM: Marginal structural models versus structural nested models as tools for causal inference.\n                  Statistical Models in Epidemiology: the Environment and Clinical Trials\n                  (Edited by: Halloran ME, Berry D). 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