A multiphase non-linear mixed effects model: An application to spirometry after lung transplantation.

abstract：:Immunotherapy, gene therapy or adoptive cell therapies, such as the chimeric antigen receptor+ T-cell therapies, have demonstrated promising therapeutic effects in oncology patients. We consider statistical designs for dose-finding adoptive cell therapy trials, in which the monotonic dose-response relationship assumed...

journal_title：Statistical methods in medical research

authors： Lin X,Ji Y

更新日期：2020-12-16 00:00:00

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

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

更新日期：2019-12-01 00:00:00

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

authors： Cliff AD,Haggett P

更新日期：1993-01-01 00:00:00

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

authors： NeCamp T,Kilbourne A,Almirall D

更新日期：2017-08-01 00:00:00

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

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

更新日期：2007-06-01 00:00:00

abstract：:Monte Carlo evaluation of resampling-based tests is often conducted in statistical analysis. However, this procedure is generally computationally intensive. The pooling resampling-based method has been developed to reduce the computational burden but the validity of the method has not been studied before. In this arti...

journal_title：Statistical methods in medical research

authors： Fung WK,Yu K,Yang Y,Zhou JY

更新日期：2018-05-01 00:00:00

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

authors： Lu T

更新日期：2017-10-01 00:00:00

abstract：:Post-therapeutic surveillance is one important component of cancer care. However, there still is no evidence-based strategies to schedule patients' follow-up examinations. Our approach is based on the modeling of the probability of the onset of relapse at an early asymptotic or preclinical stage and its transition to ...

journal_title：Statistical methods in medical research

authors： Somda SM,Leconte E,Boher JM,Asselain B,Kramar A,Filleron T

更新日期：2016-12-01 00:00:00

abstract：:In many longitudinal studies, evaluating the effect of a binary or continuous predictor variable on the rate of change of the outcome, i.e. slope, is often of primary interest. Sample size determination of these studies, however, is complicated by the expectation that missing data will occur due to missed visits, earl...

journal_title：Statistical methods in medical research

authors： Wang C,Hall CB,Kim M

更新日期：2015-12-01 00:00:00

abstract：:Statistical methods for spatial health data to identify the significant covariates associated with the health outcomes are of critical importance. Most studies have developed variable selection approaches in which the covariates included appear within the spatial domain and their effects are fixed across space. Howeve...

journal_title：Statistical methods in medical research

authors： Choi J,Lawson AB

更新日期：2018-01-01 00:00:00

abstract：:Dependent censoring arises in biomedical studies when the survival outcome of interest is censored by competing risks. In survival data with microarray gene expressions, gene selection based on the univariate Cox regression analyses has been used extensively in medical research, which however, is only valid under the ...

journal_title：Statistical methods in medical research

authors： Emura T,Chen YH

更新日期：2016-12-01 00:00:00

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

authors： Li M,Dushoff J,Bolker BM

更新日期：2018-07-01 00:00:00

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

authors： Zhang B,Liu W,Hu Y

更新日期：2018-10-01 00:00:00

abstract：:This study proposes semiparametric models for analysis of hierarchical count data containing excess zeros and overdispersion simultaneously. The methods discussed in this paper handle nonlinear covariate effects through flexible semiparametric multilevel regression techniques. This is performed by providing a comprehe...

journal_title：Statistical methods in medical research

authors： Mahmoodi M,Moghimbeigi A,Mohammad K,Faradmal J

更新日期：2018-04-01 00:00:00

abstract：:Early phase trials of complex interventions currently focus on assessing the feasibility of a large randomised control trial and on conducting pilot work. Assessing the efficacy of the proposed intervention is generally discouraged, due to concerns of underpowered hypothesis testing. In contrast, early assessment of e...

journal_title：Statistical methods in medical research

authors： Wilson DT,Walwyn RE,Brown J,Farrin AJ,Brown SR

更新日期：2016-06-01 00:00:00

abstract：:We review the origins of backcalculation (or back projection) methods developed for the analysis of AIDS (acquired immunodeficiency syndrome) incidence data. These techniques have been used extensively for >15 years to deconvolute clinical case incidence, given knowledge of the incubation period distribution, to obtai...

journal_title：Statistical methods in medical research

authors： Donnelly CA,Ferguson NM,Ghani AC,Anderson RM

更新日期：2003-06-01 00:00:00

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

authors： Fieuws S,Verbeke G,Molenberghs G

更新日期：2007-10-01 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

authors： Austin PC,Stuart EA

更新日期：2017-12-01 00:00:00

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

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

更新日期：2005-02-01 00:00:00

abstract：:Tracking a subject's risk factors or health status over time is an important objective in long-term epidemiological studies with repeated measurements. An important issue of time-trend tracking is to define appropriate statistical indices to quantitatively measure the tracking abilities of the targeted risk factors or...

journal_title：Statistical methods in medical research

authors： Wu CO,Tian X,Tian L,Reis JP,Zhao L,Allen NB,Bae S,Liu K

更新日期：2020-02-01 00:00:00

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

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

更新日期：2017-04-01 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

authors： Feng Y,Tian L

更新日期：2019-05-01 00:00:00

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

authors： Lu K

更新日期：2020-12-01 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

authors： Ju C,Schwab J,van der Laan MJ

更新日期：2019-06-01 00:00:00

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

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

更新日期：2020-09-21 00:00:00

abstract：:The analysis of health care costs is complicated by the skewed and heteroscedastic nature of their distribution with possibly additional zero values. Statistical methods that do not adjust for these features can lead to incorrect conclusions. This paper reviews recent developments in statistical methods for the analys...

journal_title：Statistical methods in medical research

authors： Zhou XH

更新日期：2002-08-01 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

authors： IntHout J,Ioannidis JP,Borm GF

更新日期：2016-04-01 00:00:00

abstract：:The accuracy of a diagnostic test, which is often quantified by a pair of measures such as sensitivity and specificity, is critical for medical decision making. Separate studies of an investigational diagnostic test can be combined through meta-analysis; however, such an analysis can be threatened by publication bias....

journal_title：Statistical methods in medical research

authors： Piao J,Liu Y,Chen Y,Ning J

更新日期：2019-10-01 00:00:00

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

authors： Willis BH,Baragilly M,Coomar D

更新日期：2020-04-01 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

authors： Guo W

更新日期：2004-02-01 00:00:00