B Bakke Hansen

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In the matched analysis of an observational study, confounding on covariates X is addressed by comparing members of a distinguished group (Z = 1) to controls (Z = 0) only when they belong to the same matched set. The better matchings, therefore, are those whose matched sets exhibit both dispersion in Z and uniformity in X. For dispersion in Z, pair matching(More)
in Observational Studies Ben B. Hansen, Paul R. Rosenbaum, and Dylan S. Small1 Abstract. Clustered treatment assignment occurs when individuals are grouped into clusters prior to treatment and whole clusters, not individuals, are assigned to treatment or control. In randomized trials, clustered assignments may be required because the treatment must be(More)
The spatial segregation of the US population by socioeconomic position and especially race/ethnicity suggests that the social contexts or "neighborhoods" in which people live may substantially contribute to social disparities in hypertension. The Chicago Community Adult Health Study did face-to-face interviews, including direct measurement of blood(More)
We attempt to clarify, and suggest how to avoid, several serious misunderstandings about and fallacies of causal inference in experimental and observational research. These issues concern some of the most basic advantages and disadvantages of each basic research design. Problems include improper use of hypothesis tests for covariate balance between the(More)
We address a major discrepancy in matching methods for causal inference in observational data. Since these data are typically plentiful, the goal of matching is to reduce bias and only secondarily to keep variance low. However, most matching methods seem designed for the opposite problem, guaranteeing sample size ex ante but limiting bias by controlling for(More)
The relation between functional and structural renal changes induced by lithium was studied in rats during long-term treatment and after withdrawal of lithium. Administration of LiCl in the diet for up to 21 weeks caused marked polyuria associated with a significant lowering of renal concentrating ability assessed by dehydration and vasopressin tests.(More)
In randomized experiments, treatment and control groups should be roughly the same—balanced—in their distributions of pretreatment variables. But how nearly so? Can descriptive comparisons meaningfully be paired with significance tests? If so, should there be several such tests, one for each pretreatment variable, or should there be a single, omnibus test?(More)
Omitted variable bias can affect treatment effect estimates obtained from observational data due to the lack of random assignment to treatment groups. Sensitivity analyses adjust these estimates to quantify the impact of potential omitted variables. This paper presents methods of sensitivity analysis to adjust interval estimates of treatment effect — both(More)
BACKGROUND The role of vascular closure devices (VCDs) in patients having percutaneous coronary intervention (PCI) is controversial, and recommendations for use vary. OBJECTIVE To examine the use of and outcomes associated with VCDs in real-world practice. DESIGN Observational cohort study. SETTING 32 hospitals in Michigan that participate in a large(More)