Locally efficient estimation of the quality-adjusted lifetime distribution with right-censored data and covariates.

Abstract:

:Zhao and Tsiatis (1997) consider the problem of estimation of the distribution of the quality-adjusted lifetime when the chronological survival time is subject to right censoring. The quality-adjusted lifetime is typically defined as a weighted sum of the times spent in certain states up until death or some other failure time. They propose an estimator and establish the relevant asymptotics under the assumption of independent censoring. In this paper we extend the data structure with a covariate process observed until the end of follow-up and identify the optimal estimation problem. Because of the curse of dimensionality, no globally efficient nonparametric estimators, which have a good practical performance at moderate sample sizes, exist. Given a correctly specified model for the hazard of censoring conditional on the observed quality-of-life and covariate processes, we propose a closed-form one-step estimator of the distribution of the quality-adjusted lifetime whose asymptotic variance attains the efficiency bound if we can correctly specify a lower-dimensional working model for the conditional distribution of quality-adjusted lifetime given the observed quality-of-life and covariate processes. The estimator remains consistent and asymptotically normal even if this latter submodel is misspecified. The practical performance of the estimators is illustrated with a simulation study. We also extend our proposed one-step estimator to the case where treatment assignment is confounded by observed risk factors so that this estimator can be used to test a treatment effect in an observational study.

journal_name

Biometrics

journal_title

Biometrics

authors

van der Laan MJ,Hubbard A

doi

10.1111/j.0006-341x.1999.00530.x

subject

Has Abstract

pub_date

1999-06-01 00:00:00

pages

530-6

issue

2

eissn

0006-341X

issn

1541-0420

journal_volume

55

pub_type

杂志文章
  • Two-group Poisson-Dirichlet mixtures for multiple testing.

    abstract::The simultaneous testing of multiple hypotheses is common to the analysis of high-dimensional data sets. The two-group model, first proposed by Efron, identifies significant comparisons by allocating observations to a mixture of an empirical null and an alternative distribution. In the Bayesian nonparametrics literatu...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.13314

    authors: Denti F,Guindani M,Leisen F,Lijoi A,Wadsworth WD,Vannucci M

    更新日期:2020-06-14 00:00:00

  • The analysis of pair-matched case-control studies, a multivariate approach.

    abstract::In matched case-control studies one frequently must consider more than one variable in the analysis and in this paper a log-linear model is presented to meet this objective. A conditional argument yields a method for making inferences on the parameters measuring the association between the variables and disease. The r...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Holford TR

    更新日期:1978-12-01 00:00:00

  • Models for circular-linear and circular-circular data constructed from circular distributions based on nonnegative trigonometric sums.

    abstract::Johnson and Wehrly (1978, Journal of the American Statistical Association 73, 602-606) and Wehrly and Johnson (1980, Biometrika 67, 255-256) show one way to construct the joint distribution of a circular and a linear random variable, or the joint distribution of a pair of circular random variables from their marginal ...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2006.00716.x

    authors: Fernández-Durán JJ

    更新日期:2007-06-01 00:00:00

  • Additive gamma frailty models with applications to competing risks in related individuals.

    abstract::Epidemiological studies of related individuals are often complicated by the fact that follow-up on the event type of interest is incomplete due to the occurrence of other events. We suggest a class of frailty models with cause-specific hazards for correlated competing events in related individuals. The frailties are b...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.12326

    authors: Eriksson F,Scheike T

    更新日期:2015-09-01 00:00:00

  • Bayesian influence measures for joint models for longitudinal and survival data.

    abstract::This article develops a variety of influence measures for carrying out perturbation (or sensitivity) analysis to joint models of longitudinal and survival data (JMLS) in Bayesian analysis. A perturbation model is introduced to characterize individual and global perturbations to the three components of a Bayesian model...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2012.01745.x

    authors: Zhu H,Ibrahim JG,Chi YY,Tang N

    更新日期:2012-09-01 00:00:00

  • A generalized estimating equations approach for spatially correlated binary data: applications to the analysis of neuroimaging data.

    abstract::This paper proposes a generalized estimating equations approach for the analysis of spatially correlated binary data when there are large numbers of spatially correlated observations on a moderate number of subjects. This approach is useful when the scientific focus is on modeling the marginal mean structure. Proper m...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Albert PS,McShane LM

    更新日期:1995-06-01 00:00:00

  • A Markov model for analysing cancer markers and disease states in survival studies.

    abstract::In studies of serial cancer markers or disease states and their relation to survival, data on the marker or state are usually obtained at infrequent time points during follow-up. A Markov model is developed to assess the dependence of risk of death on marker level or disease state and inferences within this model are ...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Kay R

    更新日期:1986-12-01 00:00:00

  • Bayesian dose-finding in phase I/II clinical trials using toxicity and efficacy odds ratios.

    abstract::A Bayesian adaptive design is proposed for dose-finding in phase I/II clinical trials to incorporate the bivariate outcomes, toxicity and efficacy, of a new treatment. Without specifying any parametric functional form for the drug dose-response curve, we jointly model the bivariate binary data to account for the corre...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2006.00534.x

    authors: Yin G,Li Y,Ji Y

    更新日期:2006-09-01 00:00:00

  • Modeling familial association of ages at onset of disease in the presence of competing risk.

    abstract::In genetic family studies, ages at onset of diseases are routinely collected. Often one is interested in assessing the familial association of ages at the onset of a certain disease type. However, when a competing risk is present and is related to the disease of interest, the usual measure of association by treating t...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2009.01372.x

    authors: Shih JH,Albert PS

    更新日期:2010-12-01 00:00:00

  • A two-stage stepwise estimation procedure.

    abstract::This article proposes a two-stage simultaneous confidence procedure for the comparisons of k pairs of population means, without using multiplicity adjustment of more than two populations. The proposed procedure can be broadly applied to parametric or nonparametric models. It is robust and versatile because its derivat...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2007.00902.x

    authors: Chen JT

    更新日期:2008-06-01 00:00:00

  • Effects of exposure misclassification on regression analyses of epidemiologic follow-up study data.

    abstract::In epidemiologic studies, subjects are often misclassified as to their level of exposure. Ignoring this misclassification error in the analysis introduces bias in the estimates of certain parameters and invalidates many hypothesis tests. For situations in which there is misclassification of exposure in a follow-up stu...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Reade-Christopher SJ,Kupper LL

    更新日期:1991-06-01 00:00:00

  • Selecting differentially expressed genes from microarray experiments.

    abstract::High throughput technologies, such as gene expression arrays and protein mass spectrometry, allow one to simultaneously evaluate thousands of potential biomarkers that could distinguish different tissue types. Of particular interest here is distinguishing between cancerous and normal organ tissues. We consider statist...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/1541-0420.00016

    authors: Pepe MS,Longton G,Anderson GL,Schummer M

    更新日期:2003-03-01 00:00:00

  • Nonparametric estimation of ROC curves in the absence of a gold standard.

    abstract::In the evaluation of diagnostic accuracy of tests, a gold standard on the disease status is required. However, in many complex diseases, it is impossible or unethical to obtain such a gold standard. If an imperfect standard is used, the estimated accuracy of the tests would be biased. This type of bias is called imper...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2005.00324.x

    authors: Zhou XH,Castelluccio P,Zhou C

    更新日期:2005-06-01 00:00:00

  • Estimating predictors for long- or short-term survivors.

    abstract::Suppose that the response variable in a well-executed clinical or observational study to evaluate a treatment is the time to a certain event, and a set of baseline covariates or predictors was collected for each study patient. Furthermore, suppose that a significant number of study patients had nontrivial, long-term a...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.0006-341x.2003.00116.x

    authors: Tian L,Wang W,Wei LJ

    更新日期:2003-12-01 00:00:00

  • A spatial Bayesian latent factor model for image-on-image regression.

    abstract::Image-on-image regression analysis, using images to predict images, is a challenging task, due to (1) the high dimensionality and (2) the complex spatial dependence structures in image predictors and image outcomes. In this work, we propose a novel image-on-image regression model, by extending a spatial Bayesian laten...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.13420

    authors: Guo C,Kang J,Johnson TD

    更新日期:2020-12-27 00:00:00

  • Some distribution properties of the sample species-diversity indices and their applications.

    abstract::In the area of ecological research the study of species diversity of a community or population seems to have been fully developed. However, the problem of how the distributions and expectations of the sample diversity indices are affected by the population diversity has received little attention. In this paper we show...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Tong YL

    更新日期:1983-12-01 00:00:00

  • An extension of the Cormack-Jolly-Seber model for continuous covariates with application to Microtus pennsylvanicus.

    abstract::Recent developments in the Cormack-Jolly-Seber (CJS) model for analyzing capture-recapture data have focused on allowing the capture and survival rates to vary between individuals. Several methods have been developed in which capture and survival are functions of auxiliary variables that may be discrete, constant over...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2005.00399.x

    authors: Bonner SJ,Schwarz CJ

    更新日期:2006-03-01 00:00:00

  • Case-control analysis with partial knowledge of exposure misclassification probabilities.

    abstract::Consider case control analysis with a dichotomous exposure variable that is subject to misclassification. If the classification probabilities are known, then methods are available to adjust odds-ratio estimates in light of the misclassification. We study the realistic scenario where reasonable guesses, but not exact v...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.0006-341x.2001.00598.x

    authors: Gustafson P,Le ND,Saskin R

    更新日期:2001-06-01 00:00:00

  • Bias in estimating association parameters for longitudinal binary responses with drop-outs.

    abstract::This paper considers the impact of bias in the estimation of the association parameters for longitudinal binary responses when there are drop-outs. A number of different estimating equation approaches are considered for the case where drop-out cannot be assumed to be a completely random process. In particular, standar...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.0006-341x.2001.00015.x

    authors: Fitzmaurice GM,Lipsitz SR,Molenberghs G,Ibrahim JG

    更新日期:2001-03-01 00:00:00

  • Methods for multivariate recurrent event data with measurement error and informative censoring.

    abstract::In multivariate recurrent event data regression, observation of recurrent events is usually terminated by other events that are associated with the recurrent event processes, resulting in informative censoring. Additionally, some covariates could be measured with errors. In some applications, an instrumental variable ...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.12857

    authors: Yu H,Cheng YJ,Wang CY

    更新日期:2018-09-01 00:00:00

  • Calculating sample size for studies with expected all-or-none nonadherence and selection bias.

    abstract:SUMMARY:We develop sample size formulas for studies aiming to test mean differences between a treatment and control group when all-or-none nonadherence (noncompliance) and selection bias are expected. Recent work by Fay, Halloran, and Follmann (2007, Biometrics 63, 465-474) addressed the increased variances within grou...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2008.01114.x

    authors: Shardell MD,El-Kamary SS

    更新日期:2009-06-01 00:00:00

  • Some statistical methodology for the analysis of HLA data.

    abstract::The estimation of gene frequencies, linkage disequilibrium and disease associations for the human leukocyte antigen (HLA) system is considered. Comprehensive models for HLA data are introduced and contrasted with simpler approaches to the analysis of such data. ...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Farewell VT,Dahlberg S

    更新日期:1984-06-01 00:00:00

  • Improved doubly robust estimation when data are monotonely coarsened, with application to longitudinal studies with dropout.

    abstract::A routine challenge is that of making inference on parameters in a statistical model of interest from longitudinal data subject to dropout, which are a special case of the more general setting of monotonely coarsened data. Considerable recent attention has focused on doubly robust (DR) estimators, which in this contex...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2010.01476.x

    authors: Tsiatis AA,Davidian M,Cao W

    更新日期:2011-06-01 00:00:00

  • Optimal designs when the variance is a function of the mean.

    abstract::We develop locally D-optimal designs for nonlinear models when the variance of the response is a function of its mean. Using the two-parameter Michaelis-Menten model as an example, we show that the optimal design depends on both the type of heteroscedasticity and the magnitude of the variation. In addition, our result...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.0006-341x.1999.00925.x

    authors: Dette H,Wong WK

    更新日期:1999-09-01 00:00:00

  • Bayesian approaches to joint cure-rate and longitudinal models with applications to cancer vaccine trials.

    abstract::Complex issues arise when investigating the association between longitudinal immunologic measures and time to an event, such as time to relapse, in cancer vaccine trials. Unlike many clinical trials, we may encounter patients who are cured and no longer susceptible to the time-to-event endpoint. If there are cured pat...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/1541-0420.00079

    authors: Brown ER,Ibrahim JG

    更新日期:2003-09-01 00:00:00

  • Generalized estimating equation model for binary outcomes with missing covariates.

    abstract::This paper presents an approach to handling missing covariates in the generalized estimating equation (GEE) model for binary outcomes when the probability of missingness depends on the observed outcomes and covariates. The proposed method is to replace the missing quantities in the estimating function with consistent ...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Xie F,Paik MC

    更新日期:1997-12-01 00:00:00

  • A Bayesian integrative approach for multi-platform genomic data: A kidney cancer case study.

    abstract::Integration of genomic data from multiple platforms has the capability to increase precision, accuracy, and statistical power in the identification of prognostic biomarkers. A fundamental problem faced in many multi-platform studies is unbalanced sample sizes due to the inability to obtain measurements from all the pl...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/biom.12587

    authors: Chekouo T,Stingo FC,Doecke JD,Do KA

    更新日期:2017-06-01 00:00:00

  • Combined maximum likelihood estimates for the equicorrelation coefficient.

    abstract::Combined maximum likelihood estimates for equicorrelation covariance matrices are considered. The case of a common equicorrelation rho and possibly different standard deviations sigma 1, ..., sigma k among k experimental groups is examined first, and the estimation of (rho, sigma 1, ..., sigma k) is discussed. Second,...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Viana MA

    更新日期:1994-09-01 00:00:00

  • Regression estimator in ranked set sampling.

    abstract::Ranked set sampling (RSS) utilizes inexpensive auxiliary information about the ranking of the units in a sample to provide a more precise estimator of the population mean of the variable of interest Y, which is either difficult or expensive to measure. However, the ranking may not be perfect in most situations. In thi...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:

    authors: Yu PL,Lam K

    更新日期:1997-09-01 00:00:00

  • Spatial cluster detection for weighted outcomes using cumulative geographic residuals.

    abstract::Spatial cluster detection is an important methodology for identifying regions with excessive numbers of adverse health events without making strong model assumptions on the underlying spatial dependence structure. Previous work has focused on point or individual-level outcome data and few advances have been made when ...

    journal_title:Biometrics

    pub_type: 杂志文章

    doi:10.1111/j.1541-0420.2009.01323.x

    authors: Cook AJ,Li Y,Arterburn D,Tiwari RC

    更新日期:2010-09-01 00:00:00