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Lifetime Data Analysis

Erschienen in:

27.02.2018

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

verfasst von: Klemen Pavlič, Torben Martinussen, Per Kragh Andersen

Erschienen in: Lifetime Data Analysis | Ausgabe 2/2019

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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.

Nächster Artikel Testing for center effects on survival and competing risks outcomes using pseudo-value regression

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Aalen OO (1989) A linear regression model for the analysis of life times. Stat Med 8:907–925CrossRef

Andersen PK (2013) Decomposition of number of years lost according to causes of death. Stat Med 32:5278–5285MathSciNetCrossRef

Andersen PK, Perme MP (2010) Pseudo-observations in survival analysis. Stat Methods Med Res 19:71–99MathSciNetCrossRef

Andersen PK, Skovgaard LT (2010) Regression with linear predictors. Springer, New YorkCrossRefMATH

Andersen PK, Klein JP, Rosthøj S (2003) Generalized linear models for correlated pseudo-observations, with applications to multi-state models. Biometrika 90:15–27MathSciNetCrossRefMATH

Andersen PK, Hansen MG, Klein JP (2004) Regression analysis of restricted mean survival time based on pseudo-observations. Lifetime Data Anal 10:335–350MathSciNetCrossRefMATH

Cox DR (1972) Regression models and life-tables. J Roy Stat Soc B 34:187–220MathSciNetMATH

Eddelbuettel D, Francois R (2011) Rcpp: seamless R and C++ integration. J Stat Softw 40(8):1–18CrossRef

Graw F, Gerds TA, Schumacher M (2009) On pseudo-values for regression analysis in competing risks models. Lifetime Data Anal 15:241–255MathSciNetCrossRefMATH

Højsgaard S, Halekoh U, Yan J (2005) The R package geepack for generalized estimating equations. J Stat Softw 15(1):1–11

Jacobsen M, Martinussen T (2016) A note on the large sample properties of estimators based on generalized linear models for correlated pseudo-observations. Scand J Stat 43:845–862MathSciNetCrossRefMATH

Klein JP, Andersen PK (2005) Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function. Biometrics 61:223–229MathSciNetCrossRefMATH

Klein JP, Gerster M, Andersen PK, Tarima S, Perme MP (2008) SAS and R functions to compute pseudo-values for censored data regression. Comput Methods Programs Biomed 89:289–300CrossRef

Li J, Scheike TH, Zhang MJ (2015) Checking fine and gray subdistribution hazards model with cumulative sums of residuals. Lifetime Data Anal 21(2):197–217MathSciNetCrossRefMATH

Lin DY, Ying Z (1994) Semiparametric analysis of the additive risk model. Biometrika 81:61–71MathSciNetCrossRefMATH

Lin DY, Wei LJ, Ying Z (1993) Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika 80:557–572MathSciNetCrossRefMATH

Lin DY, Wei LJ, Ying Z (2002) Model-checking techniques based on cumulative residuals. Biometrics 58:1–12MathSciNetCrossRefMATH

Lombard M, Portmann B, Neuberger J, Williams R, Tygstrup N, Ranek L, Larsen HR, Rodes J, Navasa M, Trepo C, Pape G, Schou G, Badsberg JH, Andersen PK (1993) Cyclosporin A treatment in primary biliary cirrhosis. Results of a long-term placebo controlled trial. Gastroenterology 104:519–526CrossRef

Martinussen T, Scheike TH (2006) Dynamic regression models for survival data. Springer, New YorkMATH

McDaniel LS, Henderson NC, Rathouz PJ (2013) Fast pure R implementation of GEE: application of the matrix package. R J 5:181–187

Overgaard M, Parner ET, Pedersen J (2017) Asymptotic theory of generalized estimating equations based on Jack-knife pseudo-observations. Ann Stat 45(5):1988–2015MathSciNetCrossRefMATH

Perme MP, Andersen PK (2008) Checking hazard regression models using pseudo-observations. Stat Med 27:5309–5328MathSciNetCrossRef

Scheike TH, Zhang MJ (2002) An additive-multiplicative Cox–Aalen model. Scand J Stat 28:75–88MathSciNetCrossRefMATH

van der Vaart A (1998) Asymptotic statistics. Cambridge University Press, CambridgeCrossRefMATH

Titel: Goodness of fit tests for estimating equations based on pseudo-observations
verfasst von: Klemen Pavlič
Torben Martinussen
Per Kragh Andersen
Publikationsdatum: 27.02.2018
Verlag: Springer US
Erschienen in: Lifetime Data Analysis / Ausgabe 2/2019
Print ISSN: 1380-7870
Elektronische ISSN: 1572-9249
DOI: https://doi.org/10.1007/s10985-018-9427-6

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