Pseudo-observations in survival analysis.

Abstract:

:We review recent work on the application of pseudo-observations in survival and event history analysis. This includes regression models for parameters like the survival function in a single point, the restricted mean survival time and transition or state occupation probabilities in multi-state models, e.g. the competing risks cumulative incidence function. Graphical and numerical methods for assessing goodness-of-fit for hazard regression models and for the Fine-Gray model in competing risks studies based on pseudo-observations are also reviewed. Sensitivity to covariate-dependent censoring is studied. The methods are illustrated using a data set from bone marrow transplantation.

journal_name

Stat Methods Med Res

authors

Andersen PK,Perme MP

doi

10.1177/0962280209105020

subject

Has Abstract

pub_date

2010-02-01 00:00:00

pages

71-99

issue

1

eissn

0962-2802

issn

1477-0334

pii

0962280209105020

journal_volume

19

pub_type

杂志文章,评审
  • A non-parametric model to address overdispersed count response in a longitudinal data setting with missingness.

    abstract::Count responses are becoming increasingly important in biostatistical analysis because of the development of new biomedical techniques such as next-generation sequencing and digital polymerase chain reaction; a commonly met problem in modeling them with the popular Poisson model is overdispersion. Although it has been...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280215583397

    authors: Zhang H,He H,Lu N,Zhu L,Zhang B,Zhang Z,Tang L

    更新日期:2017-06-01 00:00:00

  • Maximum likelihood estimation based on Newton-Raphson iteration for the bivariate random effects model in test accuracy meta-analysis.

    abstract::A bivariate generalised linear mixed model is often used for meta-analysis of test accuracy studies. The model is complex and requires five parameters to be estimated. As there is no closed form for the likelihood function for the model, maximum likelihood estimates for the parameters have to be obtained numerically. ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219853602

    authors: Willis BH,Baragilly M,Coomar D

    更新日期:2020-04-01 00:00:00

  • Estimating the personal cure rate of cancer patients using population-based grouped cancer survival data.

    abstract::Cancer patients are subject to multiple competing risks of death and may die from causes other than the cancer diagnosed. The probability of not dying from the cancer diagnosed, which is one of the patients' main concerns, is sometimes called the 'personal cure' rate. Two approaches of modelling competing-risk surviva...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280209347046

    authors: Binbing Yu,Tiwari RC,Feuer EJ

    更新日期:2011-06-01 00:00:00

  • Statistical modelling of measles and influenza outbreaks.

    abstract::This paper reviews the application of statistical models to outbreaks of two common respiratory viral diseases, measles and influenza. For each disease, we look first at its epidemiological characteristics and assess the extent to which these either aid or hinder modelling. We then turn to the models that have been de...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228029300200104

    authors: Cliff AD,Haggett P

    更新日期:1993-01-01 00:00:00

  • A stochastic estimation procedure for intermittently-observed semi-Markov multistate models with back transitions.

    abstract::Multistate models provide an important method for analyzing a wide range of life history processes including disease progression and patient recovery following medical intervention. Panel data consisting of the states occupied by an individual at a series of discrete time points are often used to estimate transition i...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217736342

    authors: Aralis H,Brookmeyer R

    更新日期:2019-03-01 00:00:00

  • Continuous(ly) missing outcome data in network meta-analysis: A one-stage pattern-mixture model approach.

    abstract::Appropriate handling of aggregate missing outcome data is necessary to minimise bias in the conclusions of systematic reviews. The two-stage pattern-mixture model has been already proposed to address aggregate missing continuous outcome data. While this approach is more proper compared with the exclusion of missing co...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220983544

    authors: Spineli LM,Kalyvas C,Papadimitropoulou K

    更新日期:2021-01-06 00:00:00

  • Bayesian sample size calculation for estimation of the difference between two binomial proportions.

    abstract::In this study, we discuss a decision theoretic or fully Bayesian approach to the sample size question in clinical trials with binary responses. Data are assumed to come from two binomial distributions. A Dirichlet distribution is assumed to describe prior knowledge of the two success probabilities p1 and p2. The param...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280211399562

    authors: Pezeshk H,Nematollahi N,Maroufy V,Marriott P,Gittins J

    更新日期:2013-12-01 00:00:00

  • Functional data analysis in longitudinal settings using smoothing splines.

    abstract::Data in many experiments arise as curves and therefore it is natural to use a curve as a basic unit in the analysis, which is termed functional data analysis (FDA). In longitudinal studies, recent developments in FDA have extended classical linear models and linear mixed effects models to functional linear models (als...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1191/0962280204sm352ra

    authors: Guo W

    更新日期:2004-02-01 00:00:00

  • Analysis of phase II methodologies for single-arm clinical trials with multiple endpoints in rare cancers: An example in Ewing's sarcoma.

    abstract::Trials run in either rare diseases, such as rare cancers, or rare sub-populations of common diseases are challenging in terms of identifying, recruiting and treating sufficient patients in a sensible period. Treatments for rare diseases are often designed for other disease areas and then later proposed as possible tre...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216662070

    authors: Dutton P,Love SB,Billingham L,Hassan AB

    更新日期:2018-05-01 00:00:00

  • Random-effects models for multivariate repeated measures.

    abstract::Mixed models are widely used for the analysis of one repeatedly measured outcome. If more than one outcome is present, a mixed model can be used for each one. These separate models can be tied together into a multivariate mixed model by specifying a joint distribution for their random effects. This strategy has been u...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280206075305

    authors: Fieuws S,Verbeke G,Molenberghs G

    更新日期:2007-10-01 00:00:00

  • Estimation of regression quantiles in complex surveys with data missing at random: An application to birthweight determinants.

    abstract::The estimation of population parameters using complex survey data requires careful statistical modelling to account for the design features. This is further complicated by unit and item nonresponse for which a number of methods have been developed in order to reduce estimation bias. In this paper, we address some issu...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280213484401

    authors: Geraci M

    更新日期:2016-08-01 00:00:00

  • Meta-analysis without study-specific variance information: Heterogeneity case.

    abstract::The random effects model in meta-analysis is a standard statistical tool often used to analyze the effect sizes of the quantity of interest if there is heterogeneity between studies. In the special case considered here, meta-analytic data contain only the sample means in two treatment arms and the sample sizes, but no...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217718867

    authors: Sangnawakij P,Böhning D,Niwitpong SA,Adams S,Stanton M,Holling H

    更新日期:2019-01-01 00:00:00

  • Latent mixture models for multivariate and longitudinal outcomes.

    abstract::Repeated measures and multivariate outcomes are an increasingly common feature of trials. Their joint analysis by means of random effects and latent variable models is appealing but patterns of heterogeneity in outcome profile may not conform to standard multivariate normal assumptions. In addition, there is much inte...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/0962280209105016

    authors: Pickles A,Croudace T

    更新日期:2010-06-01 00:00:00

  • Semiparametric integrative interaction analysis for non-small-cell lung cancer.

    abstract::In genomic analysis, it is significant though challenging to identify markers associated with cancer outcomes or phenotypes. Based on the biological mechanisms of cancers and the characteristics of datasets, we propose a novel integrative interaction approach under a semiparametric model, in which genetic and environm...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220909969

    authors: Li Y,Wang F,Li R,Sun Y

    更新日期:2020-10-01 00:00:00

  • Interpolation between spatial frameworks: an application of process convolution to estimating neighbourhood disease prevalence.

    abstract::Health data may be collected across one spatial framework (e.g. health provider agencies), but contrasts in health over another spatial framework (neighbourhoods) may be of policy interest. In the UK, population prevalence totals for chronic diseases are provided for populations served by general practitioner practice...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212447150

    authors: Congdon P

    更新日期:2014-04-01 00:00:00

  • Exact one-sided confidence limits for Cohen's kappa as a measurement of agreement.

    abstract::Cohen's kappa coefficient, κ, is a statistical measure of inter-rater agreement or inter-annotator agreement for qualitative items. In this paper, we focus on interval estimation of κ in the case of two raters and binary items. So far, only asymptotic and bootstrap intervals are available for κ due to its complexity. ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214552881

    authors: Shan G,Wang W

    更新日期:2017-04-01 00:00:00

  • Joint modelling for organ transplantation outcomes for patients with diabetes and the end-stage renal disease.

    abstract::This article is motivated by jointly modelling longitudinal and time-to-event clinical data of patients with diabetes and end-stage renal disease. All patients are on the waiting list for the pancreas transplant after kidney transplant, and some of them have a pancreas transplant before kidney transplant failure or de...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218786980

    authors: Dong JJ,Wang S,Wang L,Gill J,Cao J

    更新日期:2019-09-01 00:00:00

  • Stochastic models of sequence evolution including insertion-deletion events.

    abstract::Comparison of sequences that have descended from a common ancestor based on an explicit stochastic model of substitutions, insertions and deletions has risen to prominence in the last decade. Making statements about the positions of insertions-deletions (abbr. indels) is central in sequence and genome analysis and is ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280208099500

    authors: Miklós I,Novák A,Satija R,Lyngsø R,Hein J

    更新日期:2009-10-01 00:00:00

  • Linear time-dependent reference intervals where there is measurement error in the time variable-a parametric approach.

    abstract::This article re-examines parametric methods for the calculation of time specific reference intervals where there is measurement error present in the time covariate. Previous published work has commonly been based on the standard ordinary least squares approach, weighted where appropriate. In fact, this is an incorrect...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280211426617

    authors: Gillard J

    更新日期:2015-12-01 00:00:00

  • Practical issues arising in an exploratory analysis evaluating progression-free survival as a surrogate endpoint for overall survival in advanced colorectal cancer.

    abstract::This paper is based on a conference presentation in which several authors presented results from analyses of the same dataset concerning the evaluation of progression-free survival (PFS) as a surrogate endpoint for overall survival in advanced colorectal cancer clinical trials. In evaluating a potential surrogate endp...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280207081860

    authors: Hughes MD

    更新日期:2008-10-01 00:00:00

  • Bayesian latent structure modeling of walking behavior in a physical activity intervention.

    abstract::The analysis of walking behavior in a physical activity intervention is considered. A Bayesian latent structure modeling approach is proposed whereby the ability and willingness of participants is modeled via latent effects. The dropout process is jointly modeled via a linked survival model. Computational issues are a...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214529932

    authors: Lawson AB,Ellerbe C,Carroll R,Alia K,Coulon S,Wilson DK,VanHorn ML,George SM

    更新日期:2016-12-01 00:00:00

  • A comparison of imputation strategies in cluster randomized trials with missing binary outcomes.

    abstract::In cluster randomized trials, clusters of subjects are randomized rather than subjects themselves, and missing outcomes are a concern as in individual randomized trials. We assessed strategies for handling missing data when analysing cluster randomized trials with a binary outcome; strategies included complete case, a...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214530030

    authors: Caille A,Leyrat C,Giraudeau B

    更新日期:2016-12-01 00:00:00

  • Model selection in multivariate semiparametric regression.

    abstract::Variable selection in semiparametric mixed models for longitudinal data remains a challenge, especially in the presence of multiple correlated outcomes. In this paper, we propose a model selection procedure that simultaneously selects fixed and random effects using a maximum penalized likelihood method with the adapti...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217690769

    authors: Li Z,Liu H,Tu W

    更新日期:2018-10-01 00:00:00

  • Predicting brain activity using a Bayesian spatial model.

    abstract::Increasing the clinical applicability of functional neuroimaging technology is an emerging objective, e.g. for diagnostic and treatment purposes. We propose a novel Bayesian spatial hierarchical framework for predicting follow-up neural activity based on an individual's baseline functional neuroimaging data. Our appro...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212448972

    authors: Derado G,Bowman FD,Zhang L,Alzheimer's Disease Neuroimaging Initiative Investigators.

    更新日期:2013-08-01 00:00:00

  • Sample size for binary logistic prediction models: Beyond events per variable criteria.

    abstract::Binary logistic regression is one of the most frequently applied statistical approaches for developing clinical prediction models. Developers of such models often rely on an Events Per Variable criterion (EPV), notably EPV ≥10, to determine the minimal sample size required and the maximum number of candidate predictor...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218784726

    authors: van Smeden M,Moons KG,de Groot JA,Collins GS,Altman DG,Eijkemans MJ,Reitsma JB

    更新日期:2019-08-01 00:00:00

  • Promoting structural effects of covariates in the cure rate model with penalization.

    abstract::Cure rate models have been widely adopted for characterizing survival data that have long-term survivors. Under a mixture cure rate model where the population is a mixture of cured and susceptible subjects, a primary goal is to study covariate effects on the cure probability and survival function of the susceptible su...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217708684

    authors: Fan X,Liu M,Fang K,Huang Y,Ma S

    更新日期:2017-10-01 00:00:00

  • A generalization of functional clustering for discrete multivariate longitudinal data.

    abstract::This paper presents a new model-based generalized functional clustering method for discrete longitudinal data, such as multivariate binomial and Poisson distributed data. For this purpose, we propose a multivariate functional principal component analysis (MFPCA)-based clustering procedure for a latent multivariate Gau...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220921912

    authors: Lim Y,Cheung YK,Oh HS

    更新日期:2020-11-01 00:00:00

  • Bayesian nonparametric mixed-effects joint model for longitudinal-competing risks data analysis in presence of multiple data features.

    abstract::Recently, the joint analysis of longitudinal and survival data has been an active research area. Most joint models focus on survival data with only one type of failure. The research on joint modeling of longitudinal and competing risks survival data is sparse. Even so, many joint models for this type of data assume pa...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280215597939

    authors: Lu T

    更新日期:2017-10-01 00:00:00

  • An intuitive Bayesian spatial model for disease mapping that accounts for scaling.

    abstract::In recent years, disease mapping studies have become a routine application within geographical epidemiology and are typically analysed within a Bayesian hierarchical model formulation. A variety of model formulations for the latent level have been proposed but all come with inherent issues. In the classical BYM (Besag...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216660421

    authors: Riebler A,Sørbye SH,Simpson D,Rue H

    更新日期:2016-08-01 00:00:00

  • Prospective analysis of infectious disease surveillance data using syndromic information.

    abstract::In this paper, we describe a Bayesian hierarchical Poisson model for the prospective analysis of data for infectious diseases. The proposed model consists of two components. The first component describes the behavior of disease during nonepidemic periods and the second component represents the increase in disease coun...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214527385

    authors: Corberán-Vallet A,Lawson AB

    更新日期:2014-12-01 00:00:00