Literature DB >> 23595535

On computing standard errors for marginal structural Cox models.

R Ayesha Ali1, M Adnan Ali, Zhe Wei.   

Abstract

In recent decades, marginal structural models have gained popularity for proper adjustment of time-dependent confounders in longitudinal studies through time-dependent weighting. When the marginal model is a Cox model, using current standard statistical software packages was thought to be problematic because they were not developed to compute standard errors in the presence of time-dependent weights. We address this practical modelling issue by extending the standard calculations for Cox models with case weights to time-dependent weights and show that the coxph procedure in R can readily compute asymptotic robust standard errors. Through a simulation study, we show that the robust standard errors are rather conservative, though corresponding confidence intervals have good coverage. A second contribution of this paper is to introduce a Cox score bootstrap procedure to compute the standard errors. We show that this method is efficient and tends to outperform the non-parametric bootstrap in small samples.

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Year:  2013        PMID: 23595535     DOI: 10.1007/s10985-013-9255-7

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  8 in total

1.  Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.

Authors:  M A Hernán; B Brumback; J M Robins
Journal:  Epidemiology       Date:  2000-09       Impact factor: 4.822

2.  Marginal structural models and causal inference in epidemiology.

Authors:  J M Robins; M A Hernán; B Brumback
Journal:  Epidemiology       Date:  2000-09       Impact factor: 4.822

3.  Accuracy of conventional and marginal structural Cox model estimators: a simulation study.

Authors:  Yongling Xiao; Michal Abrahamowicz; Erica E M Moodie
Journal:  Int J Biostat       Date:  2010       Impact factor: 0.968

4.  History-adjusted marginal structural models for estimating time-varying effect modification.

Authors:  Maya L Petersen; Steven G Deeks; Jeffrey N Martin; Mark J van der Laan
Journal:  Am J Epidemiol       Date:  2007-09-17       Impact factor: 4.897

5.  Relation of pooled logistic regression to time dependent Cox regression analysis: the Framingham Heart Study.

Authors:  R B D'Agostino; M L Lee; A J Belanger; L A Cupples; K Anderson; W B Kannel
Journal:  Stat Med       Date:  1990-12       Impact factor: 2.373

6.  Covariance analysis of censored survival data.

Authors:  N Breslow
Journal:  Biometrics       Date:  1974-03       Impact factor: 2.571

7.  Use of a marginal structural model to determine the effect of aspirin on cardiovascular mortality in the Physicians' Health Study.

Authors:  Nancy R Cook; Stephen R Cole; Charles H Hennekens
Journal:  Am J Epidemiol       Date:  2002-06-01       Impact factor: 4.897

8.  Relation between three classes of structural models for the effect of a time-varying exposure on survival.

Authors:  Jessica G Young; Miguel A Hernán; Sally Picciotto; James M Robins
Journal:  Lifetime Data Anal       Date:  2009-11-06       Impact factor: 1.588

  8 in total
  3 in total

1.  Marginal structural Cox models for estimating the association between β-interferon exposure and disease progression in a multiple sclerosis cohort.

Authors:  Mohammad Ehsanul Karim; Paul Gustafson; John Petkau; Yinshan Zhao; Afsaneh Shirani; Elaine Kingwell; Charity Evans; Mia van der Kop; Joel Oger; Helen Tremlett
Journal:  Am J Epidemiol       Date:  2014-06-17       Impact factor: 4.897

2.  Performance of the marginal structural cox model for estimating individual and joined effects of treatments given in combination.

Authors:  Clovis Lusivika-Nzinga; Hana Selinger-Leneman; Sophie Grabar; Dominique Costagliola; Fabrice Carrat
Journal:  BMC Med Res Methodol       Date:  2017-12-04       Impact factor: 4.615

3.  Causal inference in multi-state models-sickness absence and work for 1145 participants after work rehabilitation.

Authors:  Jon Michael Gran; Stein Atle Lie; Irene Øyeflaten; Ørnulf Borgan; Odd O Aalen
Journal:  BMC Public Health       Date:  2015-10-23       Impact factor: 3.295

  3 in total

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