Literature DB >> 19051013

On pseudo-values for regression analysis in competing risks models.

Frederik Graw1, Thomas A Gerds, Martin Schumacher.   

Abstract

For regression on state and transition probabilities in multi-state models Andersen et al. (Biometrika 90:15-27, 2003) propose a technique based on jackknife pseudo-values. In this article we analyze the pseudo-values suggested for competing risks models and prove some conjectures regarding their asymptotics (Klein and Andersen, Biometrics 61:223-229, 2005). The key is a second order von Mises expansion of the Aalen-Johansen estimator which yields an appropriate representation of the pseudo-values. The method is illustrated with data from a clinical study on total joint replacement. In the application we consider for comparison the estimates obtained with the Fine and Gray approach (J Am Stat Assoc 94:496-509, 1999) and also time-dependent solutions of pseudo-value regression equations.

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Year:  2008        PMID: 19051013     DOI: 10.1007/s10985-008-9107-z

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


  5 in total

1.  Increased loosening of cemented straight stem prostheses made from titanium alloys. An analysis and comparison with prostheses made of cobalt-chromium-nickel alloy.

Authors:  T B Maurer; P E Ochsner; G Schwarzer; M Schumacher
Journal:  Int Orthop       Date:  2001       Impact factor: 3.075

2.  Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function.

Authors:  John P Klein; Per Kragh Andersen
Journal:  Biometrics       Date:  2005-03       Impact factor: 2.571

3.  The Kaplan-Meier Estimator as an Inverse-Probability-of-Censoring Weighted Average.

Authors:  Glen A Satten; Somnath Datta
Journal:  Am Stat       Date:  2012-01-01       Impact factor: 8.710

4.  Statistical analysis of failure times in total joint replacement.

Authors:  G Schwarzer; M Schumacher; T B Maurer; P E Ochsner
Journal:  J Clin Epidemiol       Date:  2001-10       Impact factor: 6.437

5.  Non-parametric estimation of the case fatality ratio with competing risks data: an application to Severe Acute Respiratory Syndrome (SARS).

Authors:  Nicholas P Jewell; Xiudong Lei; Azra C Ghani; Christl A Donnelly; Gabriel M Leung; Lai-Ming Ho; Benjamin J Cowling; Anthony J Hedley
Journal:  Stat Med       Date:  2007-04-30       Impact factor: 2.373

  5 in total
  23 in total

1.  Pseudo-observations for competing risks with covariate dependent censoring.

Authors:  Nadine Binder; Thomas A Gerds; Per Kragh Andersen
Journal:  Lifetime Data Anal       Date:  2013-02-22       Impact factor: 1.588

2.  Modeling marginal features in studies of recurrent events in the presence of a terminal event.

Authors:  Per Kragh Andersen; Jules Angst; Henrik Ravn
Journal:  Lifetime Data Anal       Date:  2019-01-29       Impact factor: 1.588

Review 3.  Comparison of stopped Cox regression with direct methods such as pseudo-values and binomial regression.

Authors:  Hans C van Houwelingen; Hein Putter
Journal:  Lifetime Data Anal       Date:  2014-08-02       Impact factor: 1.588

4.  Events per variable for risk differences and relative risks using pseudo-observations.

Authors:  Stefan Nygaard Hansen; Per Kragh Andersen; Erik Thorlund Parner
Journal:  Lifetime Data Anal       Date:  2014-01-14       Impact factor: 1.588

5.  Pseudo-value approach for comparing survival medians for dependent data.

Authors:  Kwang Woo Ahn; Franco Mendolia
Journal:  Stat Med       Date:  2013-12-15       Impact factor: 2.373

Review 6.  Goodness of fit tests for estimating equations based on pseudo-observations.

Authors:  Klemen Pavlič; Torben Martinussen; Per Kragh Andersen
Journal:  Lifetime Data Anal       Date:  2018-02-27       Impact factor: 1.588

7.  Marginal models for clustered time-to-event data with competing risks using pseudovalues.

Authors:  Brent R Logan; Mei-Jie Zhang; John P Klein
Journal:  Biometrics       Date:  2011-03       Impact factor: 2.571

8.  Temporal Prediction of Future State Occupation in a Multistate Model from High-Dimensional Baseline Covariates via Pseudo-Value Regression.

Authors:  Sandipan Dutta; Susmita Datta; Somnath Datta
Journal:  J Stat Comput Simul       Date:  2016-12-20       Impact factor: 1.424

9.  Comparing predictions among competing risks models with time-dependent covariates.

Authors:  Giuliana Cortese; Thomas A Gerds; Per K Andersen
Journal:  Stat Med       Date:  2013-03-13       Impact factor: 2.373

10.  A new approach to regression analysis of censored competing-risks data.

Authors:  Yuxue Jin; Tze Leung Lai
Journal:  Lifetime Data Anal       Date:  2016-08-08       Impact factor: 1.588

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