Cluster analysis and related techniques in medical research.

Abstract:

:In this paper we review methods of cluster analysis in the context of classifying patients on the basis of clinical and/or laboratory type observations. Both hierarchical and non-hierarchical methods of clustering are considered, although the emphasis is on the latter type, with particular attention devoted to the mixture likelihood-based approach. For the purposes of dividing a given data set into g clusters, this approach fits a mixture model of g components, using the method of maximum likelihood. It thus provides a sound statistical basis for clustering. The important but difficult question of how many clusters are there in the data can be addressed within the framework of standard statistical theory, although theoretical and computational difficulties still remain. Two case studies, involving the cluster analysis of some haemophilia and diabetes data respectively, are reported to demonstrate the mixture likelihood-based approach to clustering.

journal_name

Stat Methods Med Res

authors

McLachlan GJ

doi

10.1177/096228029200100103

subject

Has Abstract

pub_date

1992-01-01 00:00:00

pages

27-48

issue

1

eissn

0962-2802

issn

1477-0334

journal_volume

1

pub_type

杂志文章,评审
  • Unbiasedness and efficiency of non-parametric and UMVUE estimators of the probabilistic index and related statistics.

    abstract::In reliability theory, diagnostic accuracy, and clinical trials, the quantity P ( X > Y ) + ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220966629

    authors: Verbeeck J,Deltuvaite-Thomas V,Berckmoes B,Burzykowski T,Aerts M,Thas O,Buyse M,Molenberghs G

    更新日期:2020-12-01 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

  • A monotone data augmentation algorithm for longitudinal data analysis via multivariate skew-t, skew-normal or t distributions.

    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

    authors: Tang Y

    更新日期:2020-06-01 00:00:00

  • Modelling breast cancer tumour growth for a stable disease population.

    abstract::Statistical models of breast cancer tumour progression have been used to further our knowledge of the natural history of breast cancer, to evaluate mammography screening in terms of mortality, to estimate overdiagnosis, and to estimate the impact of lead-time bias when comparing survival times between screen detected ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217734583

    authors: Isheden G,Humphreys K

    更新日期:2019-03-01 00:00:00

  • Evaluation of software for multiple imputation of semi-continuous data.

    abstract::It is now widely accepted that multiple imputation (MI) methods properly handle the uncertainty of missing data over single imputation methods. Several standard statistical software packages, such as SAS, R and STATA, have standard procedures or user-written programs to perform MI. The performance of these packages is...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280206074464

    authors: Yu LM,Burton A,Rivero-Arias O

    更新日期:2007-06-01 00:00:00

  • Analysis of clustered competing risks data using subdistribution hazard models with multivariate frailties.

    abstract::Competing risks data often exist within a center in multi-center randomized clinical trials where the treatment effects or baseline risks may vary among centers. In this paper, we propose a subdistribution hazard regression model with multivariate frailty to investigate heterogeneity in treatment effects among centers...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214526193

    authors: Ha ID,Christian NJ,Jeong JH,Park J,Lee Y

    更新日期:2016-12-01 00:00:00

  • Inferential tools in penalized logistic regression for small and sparse data: A comparative study.

    abstract::This paper focuses on inferential tools in the logistic regression model fitted by the Firth penalized likelihood. In this context, the Likelihood Ratio statistic is often reported to be the preferred choice as compared to the 'traditional' Wald statistic. In this work, we consider and discuss a wider range of test st...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216661213

    authors: Siino M,Fasola S,Muggeo VM

    更新日期:2018-05-01 00:00:00

  • Propensity scores: from naive enthusiasm to intuitive understanding.

    abstract::Estimation of the effect of a binary exposure on an outcome in the presence of confounding is often carried out via outcome regression modelling. An alternative approach is to use propensity score methodology. The propensity score is the conditional probability of receiving the exposure given the observed covariates a...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280210394483

    authors: Williamson E,Morley R,Lucas A,Carpenter J

    更新日期:2012-06-01 00:00:00

  • Reference-based pattern-mixture models for analysis of longitudinal binary data.

    abstract::Pattern-mixture model (PMM)-based controlled imputations have become a popular tool to assess the sensitivity of primary analysis inference to different post-dropout assumptions or to estimate treatment effectiveness. The methodology is well established for continuous responses but less well established for binary res...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220941880

    authors: Lu K

    更新日期:2020-12-01 00:00:00

  • Analysis of clustered data in receiver operating characteristic studies.

    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 ap...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228029800700402

    authors: Beam CA

    更新日期:1998-12-01 00:00:00

  • Projections of cancer mortality risks using spatio-temporal P-spline models.

    abstract::Cancer mortality risk estimates are essential for planning resource allocation and designing and evaluating cancer prevention and management strategies. However, mortality figures generally become available after a few years, making necessary to develop reliable procedures to provide current and near future mortality ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212446366

    authors: Ugarte MD,Goicoa T,Etxeberria J,Militino AF

    更新日期:2012-10-01 00:00:00

  • Adjustment for treatment changes in epilepsy trials: A comparison of causal methods for time-to-event outcomes.

    abstract:BACKGROUND:When trials are subject to departures from randomised treatment, simple statistical methods that aim to estimate treatment efficacy, such as per protocol or as treated analyses, typically introduce selection bias. More appropriate methods to adjust for departure from randomised treatment are rarely employed,...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217735560

    authors: Dodd S,Williamson P,White IR

    更新日期:2019-03-01 00:00:00

  • armDNA: A functional beta model for detecting age-related genomewide DNA methylation marks.

    abstract::DNA methylation has been shown to play an important role in many complex diseases. The rapid development of high-throughput DNA methylation scan technologies provides great opportunities for genomewide DNA methylation-disease association studies. As methylation is a dynamic process involving time, it is quite plausibl...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216683571

    authors: Wang C,Shen Q,Du L,Xu J,Zhang H

    更新日期:2018-09-01 00:00:00

  • Joint modeling of longitudinal zero-inflated count and time-to-event data: A Bayesian perspective.

    abstract::Longitudinal zero-inflated count data are encountered frequently in substance-use research when assessing the effects of covariates and risk factors on outcomes. Often, both the time to a terminal event such as death or dropout and repeated measure count responses are collected for each subject. In this setting, the l...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216659312

    authors: Zhu H,DeSantis SM,Luo S

    更新日期:2018-04-01 00:00:00

  • Correcting for dependent censoring in routine outcome monitoring data by applying the inverse probability censoring weighted estimator.

    abstract::Censored data make survival analysis more complicated because exact event times are not observed. Statistical methodology developed to account for censored observations assumes that patients' withdrawal from a study is independent of the event of interest. However, in practice, some covariates might be associated to b...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216628900

    authors: Willems S,Schat A,van Noorden MS,Fiocco M

    更新日期:2018-02-01 00:00:00

  • Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

    abstract::Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cl...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217708654

    authors: NeCamp T,Kilbourne A,Almirall D

    更新日期:2017-08-01 00:00:00

  • Inferring the direction of a causal link and estimating its effect via a Bayesian Mendelian randomization approach.

    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

    authors: Bucur IG,Claassen T,Heskes T

    更新日期:2020-04-01 00:00:00

  • An ad hoc method for dual adjusting for measurement errors and nonresponse bias for estimating prevalence in survey data: Application to Iranian mental health survey on any illicit drug use.

    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

    authors: Khalagi K,Mansournia MA,Motevalian SA,Nourijelyani K,Rahimi-Movaghar A,Bakhtiyari M

    更新日期:2018-10-01 00:00:00

  • Accurate quantification of uncertainty in epidemic parameter estimates and predictions using stochastic compartmental models.

    abstract::Stochastic transmission dynamic models are needed to quantify the uncertainty in estimates and predictions during outbreaks of infectious diseases. We previously developed a calibration method for stochastic epidemic compartmental models, called Multiple Shooting for Stochastic Systems (MSS), and demonstrated its comp...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218805780

    authors: Zimmer C,Leuba SI,Cohen T,Yaesoubi R

    更新日期:2019-12-01 00:00:00

  • Statistical methods in computational anatomy.

    abstract::This paper reviews recent developments by the Washington/Brown groups for the study of anatomical shape in the emerging new discipline of computational anatomy. Parametric representations of anatomical variation for computational anatomy are reviewed, restricted to the assumption of small deformations. The generation ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228029700600305

    authors: Miller M,Banerjee A,Christensen G,Joshi S,Khaneja N,Grenander U,Matejic L

    更新日期:1997-09-01 00:00:00

  • Efficient two-stage sequential arrays of proof of concept studies for pharmaceutical portfolios.

    abstract::Previous work has shown that individual randomized "proof-of-concept" (PoC) studies may be designed to maximize cost-effectiveness, subject to an overall PoC budget constraint. Maximizing cost-effectiveness has also been considered for arrays of simultaneously executed PoC studies. Defining Type III error as the oppor...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220958177

    authors: He L,Du L,Antonijevic Z,Posch M,Korostyshevskiy VR,Beckman RA

    更新日期:2020-09-21 00:00:00

  • Hybrid test for publication bias in meta-analysis.

    abstract::Publication bias frequently appears in meta-analyses when the included studies' results (e.g., p-values) influence the studies' publication processes. Some unfavorable studies may be suppressed from publication, so the meta-analytic results may be biased toward an artificially favorable direction. Many statistical tes...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220910172

    authors: Lin L

    更新日期:2020-10-01 00:00:00

  • Study design for epidemiologic studies with measurement error.

    abstract::Exposure measurement error in epidemiological studies is recognized as a feature that must be considered because of the potential bias that can result in estimates of the exposure-disease association. Most of the work to date has focused on methods of analysis that adjust for the resultant bias, but the implications o...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228029500400405

    authors: Holford TR,Stack C

    更新日期:1995-12-01 00:00:00

  • Forensic inference from genetic markers.

    abstract::This review provides an overview of forensic inference from genetic markers. Because the judge and jurors are charged with decision-making, the forensic expert's job is to provide a useful summary of the evidence to the court. Hence, this review focuses on the likelihood ratio as a means of summarizing the genetic dat...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228029300200304

    authors: Devlin B

    更新日期:1993-01-01 00:00:00

  • Measurement error correction using validation data: a review of methods and their applicability in case-control studies.

    abstract::Measurement error is a serious problem in the analysis of epidemiological data. In the past 20 years, a large number of methods for the correction of measurement error have been developed. While at the beginning mostly methods for cohort studies were considered, recently more attention has been paid to case-control st...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228020000900504

    authors: Thürigen D,Spiegelman D,Blettner M,Heuer C,Brenner H

    更新日期:2000-10-01 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

  • Estimation of sensitivity depending on sojourn time and time spent in preclinical state.

    abstract::The probability model for periodic screening was extended to provide statistical inference for sensitivity depending on sojourn time, in which the sensitivity was modeled as a function of time spent in the preclinical state and the sojourn time. The likelihood function with the proposed sensitivity model was then eval...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212465499

    authors: Kim S,Wu D

    更新日期:2016-04-01 00:00:00

  • Joint nested frailty models for clustered recurrent and terminal events: An application to colonoscopy screening visits and colorectal cancer risks in Lynch Syndrome families.

    abstract::Joint models for recurrent and terminal events have not been yet developed for clustered data. The goals of our study are to develop a statistical framework for modelling clustered recurrent and terminal events and to perform dynamic predictions of the terminal event in family studies. We propose a joint nested frailt...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219863076

    authors: Choi YH,Jacqmin-Gadda H,Król A,Parfrey P,Briollais L,Rondeau V

    更新日期:2020-05-01 00:00:00

  • Towards joint disease mapping.

    abstract::This article discusses and extends statistical models to jointly analyse the spatial variation of rates of several diseases with common risk factors. We start with a review of methods for separate analyses of diseases, then move to ecological regression approaches, where the rates from one of the diseases enter as sur...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1191/0962280205sm389oa

    authors: Held L,Natário I,Fenton SE,Rue H,Becker N

    更新日期:2005-02-01 00:00:00

  • Measurement error, time lag, unmeasured confounding: Considerations for longitudinal estimation of the effect of a mediator in randomised clinical trials.

    abstract::Clinical trials are expensive and time-consuming and so should also be used to study how treatments work, allowing for the evaluation of theoretical treatment models and refinement and improvement of treatments. These treatment processes can be studied using mediation analysis. Randomised treatment makes some of the a...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216666111

    authors: Goldsmith KA,Chalder T,White PD,Sharpe M,Pickles A

    更新日期:2018-06-01 00:00:00