title: Sensitivity analysis for causal inference using inverse probability weighting.
abstract: Evaluation of impact of potential uncontrolled confounding is an important component for causal inference based on observational studies. In this article, we introduce a general framework of sensitivity analysis that is based on inverse probability weighting. We propose a general methodology that allows both non-parametric and parametric analyses, which are driven by two parameters that govern the magnitude of the variation of the multiplicative errors of the propensity score and their correlations with the potential outcomes. We also introduce a specific parametric model that offers a mechanistic view on how the uncontrolled confounding may bias the inference through these parameters. Our method can be readily applied to both binary and continuous outcomes and depends on the covariates only through the propensity score that can be estimated by any parametric or non-parametric method. We illustrate our method with two medical data sets.
authors.affiliation: Division of Biostatistics, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA. chashen@iupui.edu
authors.forename: Changyu
authors.initials: C
authors.lastname: Shen
authors.forename: Xiaochun
authors.initials: X
authors.lastname: Li
authors.forename: Lingling
authors.initials: L
authors.lastname: Li
authors.forename: Martin C
authors.initials: MC
authors.lastname: Were
mesh_terms: D000077284:Abciximab; D000328:Adult; D017130:Angioplasty; D000911:Antibodies, Monoclonal / Q000191:economics / Q000627:therapeutic use; D015704:CD4 Antigens / Q000032:analysis; D019963:Clinical Chemistry Tests; D002986:Clinical Trials as Topic / Q000379:methods*; D003327:Coronary Disease / Q000188:drug therapy / Q000401:mortality / Q000628:therapy; D006679:HIV Seropositivity / Q000188:drug therapy; D006295:Health Resources / Q000706:statistics & numerical data; D006801:Humans; D007140:Immunoglobulin Fab Fragments / Q000191:economics / Q000627:therapeutic use; D011336:Probability; D012984:Software; D018709:Statistics, Nonparametric
chemical_list: D000911:Antibodies, Monoclonal; D015704:CD4 Antigens; D007140:Immunoglobulin Fab Fragments; D000077284:Abciximab