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 studied extensively for cross-sectional observations, addressing overdispersion for longitudinal data without parametric distributional assumptions remains challenging, especially with missing data. In this paper, we propose a method to detect overdispersion in repeated measures in a non-parametric manner by extending the Mann-Whitney-Wilcoxon rank sum test to longitudinal data. In addition, we also incorporate the inverse probability weighted method to address the data missingness. The proposed model is illustrated with both simulated and real study data.

journal_name

Stat Methods Med Res

authors

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

doi

10.1177/0962280215583397

subject

Has Abstract

pub_date

2017-06-01 00:00:00

pages

1461-1475

issue

3

eissn

0962-2802

issn

1477-0334

pii

0962280215583397

journal_volume

26

pub_type

杂志文章
  • Assessing the reliability of ordered categorical scales using kappa-type statistics.

    abstract::Methods for the analysis of reliability of ordered categorical scales are discussed, focussing on the limitation of the single summary-weighted kappa coefficients. A symmetric matrix of kappa-type coefficients is suggested as an alternative. The method is proposed as being suitable for ordinal scale where there is no ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1191/0962280205sm413oa

    authors: Roberts C,McNamee R

    更新日期:2005-10-01 00:00:00

  • The cross-validated AUC for MCP-logistic regression with high-dimensional data.

    abstract::We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selec...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280211428385

    authors: Jiang D,Huang J,Zhang Y

    更新日期:2013-10-01 00:00:00

  • Estimating marginal and incremental effects in the analysis of medical expenditure panel data using marginalized two-part random-effects generalized Gamma models: Evidence from China healthcare cost data.

    abstract::Conditional two-part random-effects models have been proposed for the analysis of healthcare cost panel data that contain both zero costs from the non-users of healthcare facilities and positive costs from the users. These models have been extended to accommodate more flexible data structures when using the generalize...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217690770

    authors: Zhang B,Liu W,Hu Y

    更新日期:2018-10-01 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

  • 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

  • Pattern discovery of health curves using an ordered probit model with Bayesian smoothing and functional principal component analysis.

    abstract::This article is motivated by the need for discovering patterns of patients' health based on their daily settings of care to aid the health policy-makers to improve the effectiveness of distributing funding for health services. The hidden process of one's health status is assumed to be a continuous smooth function, cal...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220951834

    authors: Wang S,Nie Y,Sutherland JM,Wang L

    更新日期:2020-09-25 00:00:00

  • Long-term frailty modeling using a non-proportional hazards model: Application with a melanoma dataset.

    abstract::The semiparametric Cox regression model is often fitted in the modeling of survival data. One of its main advantages is the ease of interpretation, as long as the hazards rates for two individuals do not vary over time. In practice the proportionality assumption of the hazards may not be true in some situations. In ad...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219883905

    authors: Calsavara VF,Milani EA,Bertolli E,Tomazella V

    更新日期:2020-08-01 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

  • 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

  • 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

  • Controlling for localised spatio-temporal autocorrelation in long-term air pollution and health studies.

    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

    authors: Lee D,Mitchell R

    更新日期:2014-12-01 00:00:00

  • A quick and accurate method for the estimation of covariate effects based on empirical Bayes estimates in mixed-effects modeling: Correction of bias due to shrinkage.

    abstract::Nonlinear mixed-effects modeling is a popular approach to describe the temporal trajectory of repeated measurements of clinical endpoints collected over time in clinical trials, to distinguish the within-subject and the between-subject variabilities, and to investigate clinically important risk factors (covariates) th...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218812595

    authors: Yuan M,Xu XS,Yang Y,Xu J,Huang X,Tao F,Zhao L,Zhang L,Pinheiro J

    更新日期:2019-12-01 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 robust imputation method for missing responses and covariates in sample selection models.

    abstract::Sample selection arises when the outcome of interest is partially observed in a study. Although sophisticated statistical methods in the parametric and non-parametric framework have been proposed to solve this problem, it is yet unclear how to deal with selectively missing covariate data using simple multiple imputati...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217715663

    authors: Ogundimu EO,Collins GS

    更新日期:2019-01-01 00:00:00

  • Correcting for non-participation bias in health surveys using record-linkage, synthetic observations and pattern mixture modelling.

    abstract::Surveys are key means of obtaining policy-relevant information not available from routine sources. Bias arising from non-participation is typically handled by applying weights derived from limited socio-demographic characteristics. This approach neither captures nor adjusts for differences in health and related behavi...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219854482

    authors: Gray L,Gorman E,White IR,Katikireddi SV,McCartney G,Rutherford L,Leyland AH

    更新日期:2020-04-01 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

  • Time-dependent efficacy of longitudinal biomarker for clinical endpoint.

    abstract::Joint modelling of longitudinal biomarker and event-time processes has gained its popularity in recent years as they yield more accurate and precise estimates. Considering this modelling framework, a new methodology for evaluating the time-dependent efficacy of a longitudinal biomarker for clinical endpoint is propose...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216673084

    authors: Kolamunnage-Dona R,Williamson PR

    更新日期:2018-06-01 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

  • Stratified and randomized play-the-winner rule.

    abstract::In this paper, a new allocation rule for treatment assignments in sequential clinical trials is proposed. The stratified and randomized play-the-winner rule (SRPWR) is an extension of the randomized play-the-winner rule to more than two treatments. It is applicable to cases where the probabilities of success of a trea...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280207081606

    authors: Liang Y,Carriere KC

    更新日期:2008-12-01 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

  • 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

  • Estimating the average treatment effects of nutritional label use using subclassification with regression adjustment.

    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

    authors: Lopez MJ,Gutman R

    更新日期:2017-04-01 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

  • 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

  • Estimating the effect of treatment on binary outcomes using full matching on the propensity score.

    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

    authors: Austin PC,Stuart EA

    更新日期:2017-12-01 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

  • A new diagnostic accuracy measure and cut-point selection criterion.

    abstract::Most diagnostic accuracy measures and criteria for selecting optimal cut-points are only applicable to diseases with binary or three stages. Currently, there exist two diagnostic measures for diseases with general k stages: the hypervolume under the manifold and the generalized Youden index. While hypervolume under th...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280215611631

    authors: Dong T,Attwood K,Hutson A,Liu S,Tian L

    更新日期:2017-12-01 00:00:00

  • Mixture modelling for cluster analysis.

    abstract::Cluster analysis via a finite mixture model approach is considered. With this approach to clustering, the data can be partitioned into a specified number of clusters g by first fitting a mixture model with g components. An outright clustering of the data is then obtained by assigning an observation to the component to...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1191/0962280204sm372ra

    authors: McLachlan GJ,Chang SU

    更新日期:2004-10-01 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

  • Relative efficiency of unequal cluster sizes for variance component estimation in cluster randomized and multicentre trials.

    abstract::Cluster randomized and multicentre trials evaluate the effect of a treatment on persons nested within clusters, for instance patients within clinics or pupils within schools. Although equal sample sizes per cluster are generally optimal for parameter estimation, they are rarely feasible. This paper addresses the relat...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280206079018

    authors: van Breukelen GJ,Candel MJ,Berger MP

    更新日期:2008-08-01 00:00:00