Literature DB >> 15690989

Regression analysis of restricted mean survival time based on pseudo-observations.

Per Kragh Andersen1, Mette Gerster Hansen, John P Klein.   

Abstract

Regression models for survival data are often specified from the hazard function while classical regression analysis of quantitative outcomes focuses on the mean value (possibly after suitable transformations). Methods for regression analysis of mean survival time and the related quantity, the restricted mean survival time, are reviewed and compared to a method based on pseudo-observations. Both Monte Carlo simulations and two real data sets are studied. It is concluded that while existing methods may be superior for analysis of the mean, pseudo-observations seem well suited when the restricted mean is studied.

Mesh:

Substances:

Year:  2004        PMID: 15690989     DOI: 10.1007/s10985-004-4771-0

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


  9 in total

1.  Causal inference on the difference of the restricted mean lifetime between two groups.

Authors:  P Y Chen; A A Tsiatis
Journal:  Biometrics       Date:  2001-12       Impact factor: 2.571

2.  The standard error of an estimate of expectation of life, with special reference to expectation of tumourless life in experiments with mice.

Authors:  J O IRWIN
Journal:  J Hyg (Lond)       Date:  1949-06

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

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

4.  Longitudinal data analysis for discrete and continuous outcomes.

Authors:  S L Zeger; K Y Liang
Journal:  Biometrics       Date:  1986-03       Impact factor: 2.571

5.  Sex, ascites and alcoholism in survival of patients with cirrhosis. Effect of prednisone.

Authors: 
Journal:  N Engl J Med       Date:  1974-08-08       Impact factor: 91.245

6.  Prognostic factors in cirrhosis identified by Cox's regression model.

Authors:  P Schlichting; E Christensen; P K Andersen; L Fauerholdt; E Juhl; H Poulsen; N Tygstrup
Journal:  Hepatology       Date:  1983 Nov-Dec       Impact factor: 17.425

7.  A comparison of several methods of estimating the survival function when there is extreme right censoring.

Authors:  M L Moeschberger; J P Klein
Journal:  Biometrics       Date:  1985-03       Impact factor: 2.571

8.  An application of lifetime models in estimation of expected length of stay of patients in hospital with complexity and age adjustment.

Authors:  J Li
Journal:  Stat Med       Date:  1999-12-15       Impact factor: 2.373

9.  A therapeutic index that predicts the individual effects of prednisone in patients with cirrhosis.

Authors:  E Christensen; P Schlichting; P K Andersen; L Fauerholdt; E Juhl; H Poulsen; N Tygstrup
Journal:  Gastroenterology       Date:  1985-01       Impact factor: 22.682

  9 in total
  51 in total

1.  Estimating differences in restricted mean lifetime using observational data subject to dependent censoring.

Authors:  Min Zhang; Douglas E Schaubel
Journal:  Biometrics       Date:  2010-10-29       Impact factor: 2.571

2.  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

3.  The k-sample problem in a multi-state model and testing transition probability matrices.

Authors:  Prabhanjan N Tattar; H J Vaman
Journal:  Lifetime Data Anal       Date:  2013-05-31       Impact factor: 1.588

4.  Predicting the restricted mean event time with the subject's baseline covariates in survival analysis.

Authors:  Lu Tian; Lihui Zhao; L J Wei
Journal:  Biostatistics       Date:  2013-11-29       Impact factor: 5.899

5.  Deep Neural Networks for Survival Analysis Using Pseudo Values.

Authors:  Lili Zhao; Dai Feng
Journal:  IEEE J Biomed Health Inform       Date:  2020-11-04       Impact factor: 5.772

6.  Contrasting treatment-specific survival using double-robust estimators.

Authors:  Min Zhang; Douglas E Schaubel
Journal:  Stat Med       Date:  2012-07-16       Impact factor: 2.373

7.  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

8.  Adjusted restricted mean survival times in observational studies.

Authors:  Sarah C Conner; Lisa M Sullivan; Emelia J Benjamin; Michael P LaValley; Sandro Galea; Ludovic Trinquart
Journal:  Stat Med       Date:  2019-05-22       Impact factor: 2.373

9.  Possible UIP pattern on high-resolution computed tomography is associated with better survival than definite UIP in IPF patients.

Authors:  Margaret L Salisbury; Leslie B Tolle; Meng Xia; Susan Murray; Nabihah Tayob; Anoop M Nambiar; Shelley L Schmidt; Amir Lagstein; Jeffery L Myers; Barry H Gross; Ella A Kazerooni; Baskaran Sundaram; Aamer R Chughtai; Fernando J Martinez; Kevin R Flaherty
Journal:  Respir Med       Date:  2017-09-12       Impact factor: 3.415

10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.