Abstract:
:Clustered data is not simply correlated data, but has its own unique aspects. In this paper, various methods for correlated receiver operating characteristic (ROC) curve data that have been extended specifically to clustered data are reviewed. For those methods that have not yet been extended, suggestions for their application to clustered ROC studies are provided. Various methods with respect to their ability to meet either of two objectives of the analysis of clustered ROC data are compared to consider a variety of ROC indices and their accessibility to researchers. The available statistical methods for clustered data vary in the range of indices that can be considered and in their accessibility to researchers. Parametric models permit all indices to be considered but, owing to computational complexity, are the least accessible of available methods. Nonparametric methods are much more accessible, but only permit estimation and inference about ROC curve area. The jackknife method is the most accessible and permits any index to be considered. Future development of methods for clustered ROC studies should consider the continuation ratio model, which will permit the application of widely available software for the analysis of mixed generalized linear models. Another area of development should be in the adoption of bootstrapping methods to clustered ROC data.
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
Beam CAdoi
10.1177/096228029800700402subject
Has Abstractpub_date
1998-12-01 00:00:00pages
324-36issue
4eissn
0962-2802issn
1477-0334journal_volume
7pub_type
杂志文章,评审abstract::The use of genetic variants as instrumental variables - an approach known as Mendelian randomization - is a popular epidemiological method for estimating the causal effect of an exposure (phenotype, biomarker, risk factor) on a disease or health-related outcome from observational data. Instrumental variables must sati...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219851817
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abstract::The mixed effects model for repeated measures has been widely used for the analysis of longitudinal clinical data collected at a number of fixed time points. We propose a robust extension of the mixed effects model for repeated measures for skewed and heavy-tailed data on basis of the multivariate skew-t distribution,...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219865579
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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
更新日期:2013-08-01 00:00:00
abstract::Estimating the long-term health impact of air pollution using an ecological spatio-temporal study design is a challenging task, due to the presence of residual spatio-temporal autocorrelation in the health counts after adjusting for the covariate effects. This autocorrelation is commonly modelled by a set of random ef...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214527384
更新日期:2014-12-01 00:00:00
abstract::Bayes or empirical Bayes methods to improve inferential accuracy for a population mean has been widely adopted in medical research. As the joint prior distribution of both the mean and variance parameters can be difficult to specify or estimate, most of these methods have relied on certain level of simplifications of ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218773537
更新日期:2019-06-01 00:00:00
abstract::When comparing two different kinds of group therapy or two individual treatments where patients within each arm are nested within care providers, clustering of observations may occur in both arms. The arms may differ in terms of (a) the intraclass correlation, (b) the outcome variance, (c) the cluster size, and (d) th...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214563100
更新日期:2015-10-01 00:00:00
abstract::This work presents a brief overview of Markov models in cancer screening evaluation and focuses on two specific models. A three-state model was first proposed to estimate jointly the sensitivity of the screening procedure and the average duration in the preclinical phase, i.e. the period when the cancer is asymptomati...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/0962280209359848
更新日期:2010-10-01 00:00:00
abstract::There is debate whether clinical trials with suboptimal power are justified and whether results from large studies are more reliable than the (combined) results of smaller trials. We quantified the error rates for evaluations based on single conventionally powered trials (80% or 90% power) versus evaluations based on ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212461098
更新日期:2016-04-01 00:00:00
abstract::Couples with diseases associated with the sexual chromosomes, as well as families in countries where the desire for a male is extreme, are interested in influencing the sex of the baby. We propose an original composite likelihood approach to analyse the relation between sex of the newborn and timing of the intercourse...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217702415
更新日期:2018-11-01 00:00:00
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
更新日期:2011-06-01 00:00:00
abstract::In many experiments and especially in translational and preclinical research, sample sizes are (very) small. In addition, data designs are often high dimensional, i.e. more dependent than independent replications of the trial are observed. The present paper discusses the applicability of max t-test-type statistics (mu...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280220970228
更新日期:2020-11-24 00:00:00
abstract::Propensity score methods are common for estimating a binary treatment effect when treatment assignment is not randomized. When exposure is measured on an ordinal scale (i.e. low-medium-high), however, propensity score inference requires extensions which have received limited attention. Estimands of possible interest w...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214560046
更新日期:2017-04-01 00:00:00
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
更新日期:2017-10-01 00:00:00
abstract::With the emergence of rich information on biomarkers after treatments, new types of prognostic tools are being developed: dynamic prognostic tools that can be updated at each new biomarker measurement. Such predictions are of interest in oncology where after an initial treatment, patients are monitored with repeated b...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214535763
更新日期:2016-12-01 00:00:00
abstract::In the field of diagnostic studies for tree or umbrella ordering, under which the marker measurement for one class is lower or higher than those for the rest unordered classes, there exist a few diagnostic measures such as the naive AUC ( NAUC), the umbrella volume ( UV), and the recently proposed TAUC, i.e. area unde...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218755810
更新日期:2019-05-01 00:00:00
abstract::Many non-experimental studies use propensity-score methods to estimate causal effects by balancing treatment and control groups on a set of observed baseline covariates. Full matching on the propensity score has emerged as a particularly effective and flexible method for utilizing all available data, and creating well...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280215601134
更新日期:2017-12-01 00:00:00
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journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216657376
更新日期:2018-04-01 00:00:00
abstract::The simple yet subtle concept of regression towards the mean is reviewed historically. Verbal, geometric, and mathematical expressions of the concept date to the discoverer of the concept, Francis Galton. That discovery and subsequent understanding (and misunderstanding) of the concept are surveyed. ...
journal_title:Statistical methods in medical research
pub_type: 传,历史文章,杂志文章,评审
doi:10.1177/096228029700600202
更新日期:1997-06-01 00:00:00
abstract::Semicompeting risks and interval censoring are frequent in medical studies, for instance when a disease may be diagnosed only at times of visit and disease onset is in competition with death. To evaluate the ability of markers to predict disease onset in this context, estimators of discrimination measures must account...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214531691
更新日期:2016-12-01 00:00:00
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journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216660421
更新日期:2016-08-01 00:00:00
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journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217690770
更新日期:2018-10-01 00:00:00
abstract::Mixed models estimated by maximum likelihood and marginal models estimated by generalized estimating equations are the standard methods for the analysis of longitudinal data. However, their use is highly debated when attrition may be due to death. While some authors consider that mixed model estimates are interpretabl...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217723675
更新日期:2019-02-01 00:00:00
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journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280213502403
更新日期:2016-10-01 00:00:00
abstract::Covariate-adaptive designs are widely used to balance covariates and maintain randomization in clinical trials. Adaptive designs for discrete covariates and their asymptotic properties have been well studied in the literature. However, important continuous covariates are often involved in clinical studies. Simply disc...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218770231
更新日期:2019-06-01 00:00:00
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
更新日期:2020-10-01 00:00:00
abstract::Purpose The prevalence estimates of binary variables in sample surveys are often subject to two systematic errors: measurement error and nonresponse bias. A multiple-bias analysis is essential to adjust for both biases. Methods In this paper, we linked the latent class log-linear and proxy pattern-mixture models to ad...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217690939
更新日期:2018-10-01 00:00:00
abstract::We often seek to estimate the impact of an exposure naturally occurring or randomly assigned at the cluster-level. For example, the literature on neighborhood determinants of health continues to grow. Likewise, community randomized trials are applied to learn about real-world implementation, sustainability, and popula...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218774936
更新日期:2019-06-01 00:00:00
abstract::Understanding the limitation of solely relying on statistical significance, researchers have proposed methods to draw biomedical conclusions based on clinical significance. The minimal clinically important significance is one of the most fundamental concepts to study clinical significance. Based on an anchor question ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219850191
更新日期:2020-03-01 00:00:00
abstract::The positivity assumption, or the experimental treatment assignment (ETA) assumption, is important for identifiability in causal inference. Even if the positivity assumption holds, practical violations of this assumption may jeopardize the finite sample performance of the causal estimator. One of the consequences of p...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218774817
更新日期:2019-06-01 00:00:00
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
更新日期:2004-02-01 00:00:00