Bayesian nonparametric inference for the three-class Youden index and its associated optimal cutoff points.

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

authors： Holford TR,Stack C

更新日期：1995-12-01 00:00:00

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

authors： Bucur IG,Claassen T,Heskes T

更新日期：2020-04-01 00:00:00

abstract：:A growing body of evidence suggests that genetic factors have an important influence on the onset and course of smoking. Here we review some of the statistical methods that have been used to test for genetic influences on smoking behaviour, with a particular focus on studies of large national twin samples. We show how...

journal_title：Statistical methods in medical research

authors： Heath AC,Madden PA,Martin NG

更新日期：1998-06-01 00:00:00

abstract：:To evaluate the antiretroviral activity of antiretroviral agents and to compare the effects of two different antiretroviral agents, we propose a non-parametric mixed-effects model to investigate change of CD4+ counts. The proposed model and methods are applied to analyse the data from PACTG345 study. Population and in...

journal_title：Statistical methods in medical research

authors： Liang H

更新日期：2008-04-01 00:00:00

abstract：:Cancer survival trend analyses are essential to describe accurately the way medical practices impact patients' survival according to the year of diagnosis. To this end, survival models should be able to account simultaneously for non-linear and non-proportional effects and for complex interactions between continuous v...

journal_title：Statistical methods in medical research

authors： Remontet L,Uhry Z,Bossard N,Iwaz J,Belot A,Danieli C,Charvat H,Roche L,CENSUR Working Survival Group.

更新日期：2019-08-01 00:00:00

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

journal_title：Statistical methods in medical research

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

abstract：:In medical experiments with the objective of testing the equality of two means, data are often partially paired by design or because of missing data. The partially paired data represent a combination of paired and unpaired observations. In this article, we review and compare nine methods for analyzing partially paired...

journal_title：Statistical methods in medical research

authors： Guo B,Yuan Y

更新日期：2017-06-01 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：: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：: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

authors： Zhou Z,Zhao J,Bisson LJ

更新日期：2020-03-01 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：: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

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

更新日期：2016-08-01 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

abstract：:Pediatric cardiac surgery may lead to poor outcomes such as acute kidney injury (AKI) and prolonged hospital length of stay (LOS). Plasma and urine biomarkers may help with early identification and prediction of these adverse clinical outcomes. In a recent multi-center study, 311 children undergoing cardiac surgery we...

journal_title：Statistical methods in medical research

authors： Wang Z,Ma S,Zappitelli M,Parikh C,Wang CY,Devarajan P

更新日期：2016-12-01 00:00:00

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

authors： Tom BD,Su L,Farewell VT

更新日期：2016-10-01 00:00:00

abstract：:In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of t...

journal_title：Statistical methods in medical research

authors： Taguri M,Featherstone J,Cheng J

更新日期：2018-01-01 00:00:00

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

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

更新日期：2020-08-01 00:00:00

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

authors： Liang Y,Carriere KC

更新日期：2008-12-01 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 propose a flexible and computationally efficient penalized estimation method for a semi-parametric linear transformation model with current status data. To facilitate model fitting, the unknown monotone function is approximated by monotone B-splines, and a computationally efficient hybrid algorithm involving the Fi...

journal_title：Statistical methods in medical research

authors： Lu M,Liu Y,Li CS

更新日期：2020-01-01 00:00:00

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

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

更新日期：2016-12-01 00:00:00

abstract：:In the past two decades, it has become increasingly clear that genetic factors contribute to the aetiology of many common diseases including cancers, coronary disease, allergy and psychiatric disorders. While one goal of genetic epidemiological studies is to locate susceptibility genes for these complex diseases, it i...

journal_title：Statistical methods in medical research

authors： Liang KY,Beaty TH

更新日期：2000-12-01 00:00:00

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：: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：:One of the main advantages of Bayesian analyses of clinical trials is their ability to formally incorporate skepticism about large treatment effects through the use of informative priors. We conducted a simulation study to assess the performance of informative normal, Student- t, and beta distributions in estimating r...

journal_title：Statistical methods in medical research

authors： Pedroza C,Han W,Truong VTT,Green C,Tyson JE

更新日期：2018-01-01 00:00:00

abstract：:Many longitudinal studies observe time to occurrence of a clinical event such as death, while also collecting serial measurements of one or more biomarkers that are predictive of the event, or are surrogate outcomes of interest. Joint modeling can be used to examine the relationship between the biomarker and the event...

journal_title：Statistical methods in medical research

authors： Schluchter MD,Piccorelli AV

更新日期：2019-05-01 00:00:00

abstract：:The change-point model has drawn much attention over the past few decades. It can accommodate the jump process, which allows for changes of the effects before and after the change point. Intellectual disability is a long-term disability that impacts performance in cognitive aspects of life and usually has its onset pr...

journal_title：Statistical methods in medical research

authors： Cai B,Lawson AB,McDermott S,Aelion CM

更新日期：2016-04-01 00:00:00

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

authors： Tang Y

更新日期：2020-06-01 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

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

更新日期：2018-10-01 00:00:00

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

authors： Bühlmann P,Rütimann P,Kalisch M

更新日期：2013-10-01 00:00:00