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

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：:This paper presents a new model-based generalized functional clustering method for discrete longitudinal data, such as multivariate binomial and Poisson distributed data. For this purpose, we propose a multivariate functional principal component analysis (MFPCA)-based clustering procedure for a latent multivariate Gau...

journal_title：Statistical methods in medical research

authors： Lim Y,Cheung YK,Oh HS

更新日期：2020-11-01 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：:Improving the quality of care that patients receive is a major focus of clinical research, particularly in the setting of cardiovascular hospitalization. Quality improvement studies seek to estimate and visualize the degree of variability in dichotomous treatment patterns and outcomes across different providers, where...

journal_title：Statistical methods in medical research

authors： Thomas LE,Schulte PJ

更新日期：2019-04-01 00:00:00

abstract：:This article re-examines parametric methods for the calculation of time specific reference intervals where there is measurement error present in the time covariate. Previous published work has commonly been based on the standard ordinary least squares approach, weighted where appropriate. In fact, this is an incorrect...

journal_title：Statistical methods in medical research

authors： Gillard J

更新日期：2015-12-01 00:00:00

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

authors： Dodd S,Williamson P,White IR

更新日期：2019-03-01 00:00:00

abstract：:When estimating a survival time distribution, the loss of information due to right censoring results in a loss of efficiency in the estimator. In many circumstances, however, repeated measurements on a longitudinal process which is associated with survival time are made throughout the observation time, and these measu...

journal_title：Statistical methods in medical research

authors： Hogan JW,Laird NM

更新日期：1998-03-01 00:00:00

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 mix...

journal_title：Statistical methods in medical research

authors： McLachlan GJ

更新日期：1992-01-01 00:00:00

abstract：:The Cochran-Armitage (CA) test is commonly used in both epidemiology and genetics to test for linear trend in two-way tables with a binary outcome. There has been increasing interest in the power and size of the test and in determination of sample size, especially when there is potential misclassification in the 'expo...

journal_title：Statistical methods in medical research

authors： Buonaccorsi JP,Laake P,Veierød MB

更新日期：2014-06-01 00:00:00

abstract：:The maximal procedure is a restricted randomization method that maximizes the number of feasible allocation sequences under the constraints of the maximum tolerated imbalance and the allocation sequence length. It assigns an equal probability to all feasible sequences. However, its implementation is not easy due to th...

journal_title：Statistical methods in medical research

authors： Zhao W,Berger VW,Yu Z

更新日期：2018-07-01 00:00:00

abstract：:Covariate-adaptive designs are widely used to balance covariates and maintain randomization in clinical trials. Adaptive designs for discrete covariates and their asymptotic properties have been well studied in the literature. However, important continuous covariates are often involved in clinical studies. Simply disc...

journal_title：Statistical methods in medical research

authors： Li X,Zhou J,Hu F

更新日期：2019-06-01 00:00:00

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

authors： Zhu H,DeSantis SM,Luo S

更新日期：2018-04-01 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：: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 simple yet subtle concept of regression towards the mean is reviewed historically. Verbal, geometric, and mathematical expressions of the concept date to the discoverer of the concept, Francis Galton. That discovery and subsequent understanding (and misunderstanding) of the concept are surveyed. ...

journal_title：Statistical methods in medical research

authors： Stigler SM

更新日期：1997-06-01 00:00:00

abstract：:Binary logistic regression is one of the most frequently applied statistical approaches for developing clinical prediction models. Developers of such models often rely on an Events Per Variable criterion (EPV), notably EPV ≥10, to determine the minimal sample size required and the maximum number of candidate predictor...

journal_title：Statistical methods in medical research

authors： van Smeden M,Moons KG,de Groot JA,Collins GS,Altman DG,Eijkemans MJ,Reitsma JB

更新日期：2019-08-01 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：:Adherence to medication is often measured as a continuous outcome but analyzed as a dichotomous outcome due to lack of appropriate tools. In this paper, we illustrate the use of the temporal kernel canonical correlation analysis (tkCCA) as a method to analyze adherence measurements and symptom levels on a continuous s...

journal_title：Statistical methods in medical research

authors： John M,Lencz T,Ferbinteanu J,Gallego JA,Robinson DG

更新日期：2017-10-01 00:00:00

abstract：:Nonlinear mixed-effects modeling is one of the most popular tools for analyzing repeated measurement data, particularly for applications in the biomedical fields. Multiple integration and nonlinear optimization are the two major challenges for likelihood-based methods in nonlinear mixed-effects modeling. To solve thes...

journal_title：Statistical methods in medical research

authors： Yuan M,Zhu Z,Yang Y,Zhao M,Sasser K,Hamadeh H,Pinheiro J,Xu XS

更新日期：2020-08-24 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：: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

authors： Chen Z,Huang H,Ng HK

更新日期：2016-04-01 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：: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：: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：: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

authors： Roberts C,McNamee R

更新日期：2005-10-01 00:00:00

abstract：BACKGROUND:Dyspepsia diagnoses and treatment decisions are made in situations in which multiple factors must be taken into account. Evolving from neuro-biological insights, artificial neural networks (ANNs) can employ multiple factors in resolving medical prediction, classification, pattern recognition, and pattern com...

journal_title：Statistical methods in medical research

authors： García-Altés A,Santín D,Barenys M

更新日期：2007-08-01 00:00:00

abstract：:Many statistical studies report p-values for inferential purposes. In several scenarios, the stochastic aspect of p-values is neglected, which may contribute to drawing wrong conclusions in real data experiments. The stochastic nature of p-values makes their use to examine the performance of given testing procedures o...

journal_title：Statistical methods in medical research

authors： Vexler A,Yu J,Zhao Y,Hutson AD,Gurevich G

更新日期：2018-12-01 00:00:00

abstract：:Regression models are frequently used to model the functional relationship between an interesting outcome parameter and one or more potentially relevant explanatory variables. Objectives can be to set up as a prognostic model, for example, or an estimation model for a certain parameter of interest. Determining half-li...

journal_title：Statistical methods in medical research

authors： Mayer B,Keller F,Syrovets T,Wittau M

更新日期：2016-10-01 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：: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

authors： Jiang D,Huang J,Zhang Y

更新日期：2013-10-01 00:00:00