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 used for joining multivariate longitudinal profiles or other types of multivariate repeated data. However, computational problems are likely to occur when the number of outcomes increases. A pairwise modeling approach, in which all possible bivariate mixed models are fitted and where inference follows from pseudo-likelihood arguments, has been proposed to circumvent the dimensional limitations in multivariate mixed models. An analysis on 22-variate longitudinal measurements of hearing thresholds illustrates the performance of the pairwise approach in the context of multivariate linear mixed models. For generalized linear mixed models, a data set containing repeated measurements of seven aspects of psycho-cognitive functioning will be analyzed.

journal_name

Stat Methods Med Res

authors

Fieuws S,Verbeke G,Molenberghs G

doi

10.1177/0962280206075305

subject

Has Abstract

pub_date

2007-10-01 00:00:00

pages

387-97

issue

5

eissn

0962-2802

issn

1477-0334

pii

0962280206075305

journal_volume

16

pub_type

杂志文章
  • 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

  • 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

  • Controlling false positive selections in high-dimensional regression and causal inference.

    abstract::Guarding against false positive selections is important in many applications. We discuss methods based on subsampling and sample splitting for controlling the expected number of false positives and assigning p-values. They are generic and especially useful for high-dimensional settings. We review encouraging results f...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280211428371

    authors: Bühlmann P,Rütimann P,Kalisch M

    更新日期:2013-10-01 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

  • Re-weighted inference about hepatitis C virus-infected communities when analysing diagnosed patients referred to liver clinics.

    abstract::To project national hepatitis C virus (HCV) burden, unbiased estimation of HCV progression to liver cirrhosis is required for the whole community of HCV-infected individuals. However, widely varying estimates of progression rates to cirrhosis have been produced. This disparity is partly associated with the statistical...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280208094688

    authors: Fu B,Tom BD,Bird SM

    更新日期:2009-06-01 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

  • Components of variance in a group-randomized trial analysed via a random-coefficients model: the Rapid Early Action for Coronary Treatment (REACT) trial.

    abstract::Rapid Early Action for Coronary Treatment (REACT) was a multisite trial testing a community intervention to reduce the delay between onset of symptoms of acute myocardial infarction (MI) and patients' arrival at a hospital emergency department. The study employed a group-randomized trial design, with ten communities r...

    journal_title:Statistical methods in medical research

    pub_type: 临床试验,杂志文章,随机对照试验

    doi:10.1177/096228020000900204

    authors: Murray DM,Feldman HA,McGovern PG

    更新日期:2000-04-01 00:00:00

  • The EM algorithm in medical imaging.

    abstract::This article outlines the statistical developments that have taken place in the use of the EM algorithm in emission and transmission tomography during the past decade or so. We discuss the statistical aspects of the modelling of the projection data for both the emission and transmission cases and define the relevant p...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/096228029700600105

    authors: Kay J

    更新日期:1997-03-01 00:00:00

  • A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data.

    abstract::For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280213509798

    authors: Tom BD,Su L,Farewell VT

    更新日期:2016-10-01 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

  • The impact of covariance misspecification in group-based trajectory models for longitudinal data with non-stationary covariance structure.

    abstract::One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to iden...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280215598806

    authors: Davies CE,Glonek GF,Giles LC

    更新日期:2017-08-01 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

  • 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

  • Letter to the editor: Fitting truncated normal distributions.

    abstract::I comment here on a recent paper in this journal, on the fitting of truncated normal distributions by the EM algorithm. I show that the fitting of such distributions by direct numerical maximization of likelihood (rather than EM) is straightforward, contrary to an assertion made by the authors of that paper. ...

    journal_title:Statistical methods in medical research

    pub_type: 评论,信件

    doi:10.1177/0962280217712089

    authors: MacDonald IL

    更新日期:2018-12-01 00:00:00

  • Semiparametric analysis of correlated and interval-censored event-history data.

    abstract::We propose a semiparametric multi-state frailty model to analyze clustered event-history data subject to interval censoring. The proposed model is motivated by an attempt to study the life course of dental caries at the tooth level, taking into account the multiplicity of caries states and the intra-oral clustering of...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218788383

    authors: Pak D,Li C,Todem D

    更新日期:2019-09-01 00:00:00

  • Bayesian modeling and prediction of accrual in multi-regional clinical trials.

    abstract::In multi-regional trials, the underlying overall and region-specific accrual rates often do not hold constant over time and different regions could have different start-up times, which combined with initial jump in accrual within each region often leads to a discontinuous overall accrual rate, and these issues associa...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214557581

    authors: Deng Y,Zhang X,Long Q

    更新日期:2017-04-01 00:00:00

  • Statistical methods for HIV dynamic studies in AIDS clinical trials.

    abstract::Studies of HIV dynamics in AIDS research are very important for understanding pathogenesis of HIV infection and for assessing the potency of antiviral therapies. Since the viral dynamic results from clinical data were first published by Ho et al. and Wei et al., the study of HIV-1 dynamics in vivo has drawn a great at...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1191/0962280205sm390oa

    authors: Wu H

    更新日期:2005-04-01 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

  • Maximum likelihood estimation of time to first event in the presence of data gaps and multiple events.

    abstract::We propose a novel likelihood method for analyzing time-to-event data when multiple events and multiple missing data intervals are possible prior to the first observed event for a given subject. This research is motivated by data obtained from a heart monitor used to track the recovery process of subjects experiencing...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212466089

    authors: Green CL,Brownie C,Boos DD,Lu JC,Krucoff MW

    更新日期:2016-04-01 00:00:00

  • Fitting mechanistic epidemic models to data: A comparison of simple Markov chain Monte Carlo approaches.

    abstract::Simple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical fra...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217747054

    authors: Li M,Dushoff J,Bolker BM

    更新日期:2018-07-01 00:00:00

  • Testing for association in case-control genome-wide association studies with shared controls.

    abstract::The statistical analysis of genome-wide association studies (GWASs) with multiple diseases and shared controls (SCs) is discussed. The usual method for analyzing data from these studies is to compare each individual disease with either the SCs or the pooled controls which include other diseases. We observed that apply...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212474061

    authors: Chen Z,Huang H,Ng HK

    更新日期:2016-04-01 00:00:00

  • A goodness-of-fit test for the random-effects distribution in mixed models.

    abstract::In this paper, we develop a simple diagnostic test for the random-effects distribution in mixed models. The test is based on the gradient function, a graphical tool proposed by Verbeke and Molenberghs to check the impact of assumptions about the random-effects distribution in mixed models on inferences. Inference is c...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214564721

    authors: Efendi A,Drikvandi R,Verbeke G,Molenberghs G

    更新日期:2017-04-01 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

  • Multi-state Markov models in cancer screening evaluation: a brief review and case study.

    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

    authors: Uhry Z,Hédelin G,Colonna M,Asselain B,Arveux P,Rogel A,Exbrayat C,Guldenfels C,Courtial I,Soler-Michel P,Molinié F,Eilstein D,Duffy SW

    更新日期:2010-10-01 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

  • Power and sample size for multivariate logistic modeling of unmatched case-control studies.

    abstract::Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217737157

    authors: Gail MH,Haneuse S

    更新日期:2019-03-01 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

  • Designs in partially controlled studies: messages from a review.

    abstract::The ability to evaluate effects of factors on outcomes is increasingly important for studies that control some but not all of the factors. Although important advances have been made in methods of analysis for such partially controlled studies, work on designs has been limited. To help understand why, we review the mai...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1191/0962280205sm405oa

    authors: Li F,Frangakis CE

    更新日期:2005-08-01 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

  • Advanced colorectal neoplasia risk stratification by penalized logistic regression.

    abstract::Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratif...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280213497432

    authors: Lin Y,Yu M,Wang S,Chappell R,Imperiale TF

    更新日期:2016-08-01 00:00:00