Literature DB >> 25866704

Identification, estimation and approximation of risk under interventions that depend on the natural value of treatment using observational data.

Jessica G Young, Miguel A Herńan, James M Robins.   

Abstract

Entities:  

Year:  2014        PMID： 25866704      PMCID： PMC4387917          DOI： 10.1515/em-2012-0001

Source DB:  PubMed          Journal:  Epidemiol Methods        ISSN： 2161-962X


× No keyword cloud information.
  14 in total

1.  Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part I: main content.

Authors:  Liliana Orellana; Andrea Rotnitzky; James M Robins
Journal:  Int J Biostat       Date:  2010       Impact factor: 0.968

2.  When to start treatment? A systematic approach to the comparison of dynamic regimes using observational data.

Authors:  Lauren E Cain; James M Robins; Emilie Lanoy; Roger Logan; Dominique Costagliola; Miguel A Hernán
Journal:  Int J Biostat       Date:  2010       Impact factor: 0.968

3.  Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part II: proofs of results.

Authors:  Liliana Orellana; Andrea Rotnitzky; James M Robins
Journal:  Int J Biostat       Date:  2010-03-03       Impact factor: 0.968

4.  Diagnosing and responding to violations in the positivity assumption.

Authors:  Maya L Petersen; Kristin E Porter; Susan Gruber; Yue Wang; Mark J van der Laan
Journal:  Stat Methods Med Res       Date:  2010-10-28       Impact factor: 3.021

5.  Intervening on risk factors for coronary heart disease: an application of the parametric g-formula.

Authors:  Sarah L Taubman; James M Robins; Murray A Mittleman; Miguel A Hernán
Journal:  Int J Epidemiol       Date:  2009-04-23       Impact factor: 7.196

6.  Estimation of the effect of interventions that modify the received treatment.

Authors:  S Haneuse; A Rotnitzky
Journal:  Stat Med       Date:  2013-08-02       Impact factor: 2.373

7.  Incidence of adult-onset asthma after hypothetical interventions on body mass index and physical activity: an application of the parametric g-formula.

Authors:  Judith Garcia-Aymerich; Raphaëlle Varraso; Goodarz Danaei; Carlos A Camargo; Miguel A Hernán
Journal:  Am J Epidemiol       Date:  2013-10-09       Impact factor: 4.897

8.  Marginal Mean Models for Dynamic Regimes.

Authors:  S A Murphy; M J van der Laan; J M Robins
Journal:  J Am Stat Assoc       Date:  2001-12-01       Impact factor: 5.033

9.  Population intervention causal effects based on stochastic interventions.

Authors:  Iván Díaz Muñoz; Mark van der Laan
Journal:  Biometrics       Date:  2011-10-06       Impact factor: 2.571

10.  Changes in fish consumption in midlife and the risk of coronary heart disease in men and women.

Authors:  Martin Lajous; Walter C Willett; James Robins; Jessica G Young; Eric Rimm; Dariush Mozaffarian; Miguel A Hernán
Journal:  Am J Epidemiol       Date:  2013-06-27       Impact factor: 4.897
View more
  25 in total

1.  A causal framework for classical statistical estimands in failure-time settings with competing events.

Authors:  Jessica G Young; Mats J Stensrud; Eric J Tchetgen Tchetgen; Miguel A Hernán
Journal:  Stat Med       Date:  2020-01-27       Impact factor: 2.373

2.  Invited commentary: Estimating population impact in the presence of competing events.

Authors:  Ashley I Naimi; Eric J Tchetgen Tchetgen
Journal:  Am J Epidemiol       Date:  2015-03-27       Impact factor: 4.897

3.  Diagnosing Covariate Balance Across Levels of Right-Censoring Before and After Application of Inverse-Probability-of-Censoring Weights.

Authors:  John W Jackson
Journal:  Am J Epidemiol       Date:  2019-12-31       Impact factor: 4.897

4.  CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS.

Authors:  Ilya Shpitser; Eric Tchetgen Tchetgen
Journal:  Ann Stat       Date:  2016-11-23       Impact factor: 4.028

5.  Sensitivity Analyses for Misclassification of Cause of Death in the Parametric G-Formula.

Authors:  Jessie K Edwards; Stephen R Cole; Richard D Moore; W Christopher Mathews; Mari Kitahata; Joseph J Eron
Journal:  Am J Epidemiol       Date:  2018-08-01       Impact factor: 4.897

6.  Comparing the Effectiveness of Dynamic Treatment Strategies Using Electronic Health Records: An Application of the Parametric g-Formula to Anemia Management Strategies.

Authors:  Yi Zhang; Jessica G Young; Mae Thamer; Miguel A Hernán
Journal:  Health Serv Res       Date:  2017-05-30       Impact factor: 3.402

7.  Inverse probability weighted estimation of risk under representative interventions in observational studies.

Authors:  Jessica G Young; Roger W Logan; James M Robins; Miguel A Hernán
Journal:  J Am Stat Assoc       Date:  2018-08-10       Impact factor: 5.033

8.  Occupational radon exposure and lung cancer mortality: estimating intervention effects using the parametric g-formula.

Authors:  Jessie K Edwards; Leah J McGrath; Jessie P Buckley; Mary K Schubauer-Berigan; Stephen R Cole; David B Richardson
Journal:  Epidemiology       Date:  2014-11       Impact factor: 4.822

9.  Mortality under plausible interventions on antiretroviral treatment and depression in HIV-infected women: an application of the parametric g-formula.

Authors:  Catherine R Lesko; Jonathan V Todd; Stephen R Cole; Andrew Edmonds; Brian W Pence; Jessie K Edwards; Wendy J Mack; Peter Bacchetti; Anna Rubtsova; Stephen J Gange; Adaora A Adimora
Journal:  Ann Epidemiol       Date:  2017-09-05       Impact factor: 3.797

10.  Estimating Effects of Dynamic Treatment Strategies in Pharmacoepidemiologic Studies with Time-varying Confounding: A Primer.

Authors:  Xiaojuan Li; Jessica G Young; Sengwee Toh
Journal:  Curr Epidemiol Rep       Date:  2017-10-17
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.