Literature DB >> 29488163

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

Klemen Pavlič1, Torben Martinussen2, Per Kragh Andersen3.   

Abstract

We study regression models for mean value parameters in survival analysis based on pseudo-observations. Such parameters include the survival probability and the cumulative incidence in a single point as well as the restricted mean life time and the cause-specific number of years lost. Goodness of fit techniques for such models based on cumulative sums of pseudo-residuals are derived including asymptotic results and Monte Carlo simulations. Practical examples from liver cirrhosis and bone marrow transplantation are also provided.

Entities:  

Keywords:  Cumulative incidence function; Goodness-of-fit; Pseudo-observations; Restricted mean life time; Survival probability; Years lost

Mesh:

Year:  2018        PMID: 29488163     DOI: 10.1007/s10985-018-9427-6

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


  12 in total

1.  Model-checking techniques based on cumulative residuals.

Authors:  D Y Lin; L J Wei; Z Ying
Journal:  Biometrics       Date:  2002-03       Impact factor: 2.571

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.  SAS and R functions to compute pseudo-values for censored data regression.

Authors:  John P Klein; Mette Gerster; Per Kragh Andersen; Sergey Tarima; Maja Pohar Perme
Journal:  Comput Methods Programs Biomed       Date:  2008-01-15       Impact factor: 5.428

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

Authors:  Frederik Graw; Thomas A Gerds; Martin Schumacher
Journal:  Lifetime Data Anal       Date:  2008-12-03       Impact factor: 1.588

5.  Decomposition of number of life years lost according to causes of death.

Authors:  P K Andersen
Journal:  Stat Med       Date:  2013-07-09       Impact factor: 2.373

Review 6.  Pseudo-observations in survival analysis.

Authors:  Per Kragh Andersen; Maja Pohar Perme
Journal:  Stat Methods Med Res       Date:  2009-08-04       Impact factor: 3.021

7.  A linear regression model for the analysis of life times.

Authors:  O O Aalen
Journal:  Stat Med       Date:  1989-08       Impact factor: 2.373

8.  Checking Fine and Gray subdistribution hazards model with cumulative sums of residuals.

Authors:  Jianing Li; Thomas H Scheike; Mei-Jie Zhang
Journal:  Lifetime Data Anal       Date:  2014-11-25       Impact factor: 1.588

9.  Checking hazard regression models using pseudo-observations.

Authors:  Maja Pohar Perme; Per Kragh Andersen
Journal:  Stat Med       Date:  2008-11-10       Impact factor: 2.373

10.  Cyclosporin A treatment in primary biliary cirrhosis: results of a long-term placebo controlled trial.

Authors:  M Lombard; B Portmann; J Neuberger; R Williams; N Tygstrup; L Ranek; H Ring-Larsen; J Rodes; M Navasa; C Trepo
Journal:  Gastroenterology       Date:  1993-02       Impact factor: 22.682

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  1 in total

1.  Analyzing differences between restricted mean survival time curves using pseudo-values.

Authors:  Federico Ambrogi; Simona Iacobelli; Per Kragh Andersen
Journal:  BMC Med Res Methodol       Date:  2022-03-18       Impact factor: 4.615

  1 in total

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