The application of methods to quantify attributable risk in medical practice.

abstract：:This paper reviews models for incomplete continuous and categorical longitudinal data. In terms of Rubin's classification of missing value processes we are specifically concerned with the problem of nonrandom missingness. A distinction is drawn between the classes of selection and pattern-mixture models and, using sev...

journal_title：Statistical methods in medical research

authors： Kenward MG,Molenberghs G

更新日期：1999-03-01 00:00:00

abstract：:Publication bias frequently appears in meta-analyses when the included studies' results (e.g., p-values) influence the studies' publication processes. Some unfavorable studies may be suppressed from publication, so the meta-analytic results may be biased toward an artificially favorable direction. Many statistical tes...

journal_title：Statistical methods in medical research

authors： Lin L

更新日期：2020-10-01 00:00:00

abstract：:The random effects model in meta-analysis is a standard statistical tool often used to analyze the effect sizes of the quantity of interest if there is heterogeneity between studies. In the special case considered here, meta-analytic data contain only the sample means in two treatment arms and the sample sizes, but no...

journal_title：Statistical methods in medical research

authors： Sangnawakij P,Böhning D,Niwitpong SA,Adams S,Stanton M,Holling H

更新日期：2019-01-01 00:00:00

abstract：:In recent years, disease mapping studies have become a routine application within geographical epidemiology and are typically analysed within a Bayesian hierarchical model formulation. A variety of model formulations for the latent level have been proposed but all come with inherent issues. In the classical BYM (Besag...

journal_title：Statistical methods in medical research

authors： Riebler A,Sørbye SH,Simpson D,Rue H

更新日期：2016-08-01 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：:Metagenomics enables the study of gene abundances in complex mixtures of microorganisms and has become a standard methodology for the analysis of the human microbiome. However, gene abundance data is inherently noisy and contains high levels of biological and technical variability as well as an excess of zeros due to ...

journal_title：Statistical methods in medical research

authors： Jonsson V,Österlund T,Nerman O,Kristiansson E

更新日期：2019-12-01 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：:We propose a hierarchical Bayesian methodology to model spatially or spatio-temporal clustered survival data with possibility of cure. A flexible continuous transformation class of survival curves indexed by a single parameter is used. This transformation model is a larger class of models containing two special cases ...

journal_title：Statistical methods in medical research

authors： Hurtado Rúa SM,Dey DK

更新日期：2016-02-01 00:00:00

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

authors： Murray DM,Feldman HA,McGovern PG

更新日期：2000-04-01 00:00:00

abstract：:Common limitations of clustering methods include the slow algorithm convergence, the instability of the pre-specification on a number of intrinsic parameters, and the lack of robustness to outliers. A recent clustering approach proposed a fast search algorithm of cluster centers based on their local densities. However...

journal_title：Statistical methods in medical research

authors： Wang XF,Xu Y

更新日期：2017-12-01 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：: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：: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

authors： Caille A,Leyrat C,Giraudeau B

更新日期：2016-12-01 00:00:00

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

authors： van Breukelen GJ,Candel MJ,Berger MP

更新日期：2008-08-01 00:00:00

abstract：:In recent years, there has been a prominent discussion in the literature about the potential for overestimation of the treatment effect when a clinical trial stops at an interim analysis due to the experimental treatment showing a benefit over the control. However, there has been much less attention paid to the conver...

journal_title：Statistical methods in medical research

authors： Marschner IC,Schou IM

更新日期：2019-10-01 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

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：: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：:Identification of cancer patient subgroups using high throughput genomic data is of critical importance to clinicians and scientists because it can offer opportunities for more personalized treatment and overlapping treatments of cancers. In spite of tremendous efforts, this problem still remains challenging because o...

journal_title：Statistical methods in medical research

authors： Wei W,Sun Z,da Silveira WA,Yu Z,Lawson A,Hardiman G,Kelemen LE,Chung D

更新日期：2019-07-01 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：: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

authors： Pak D,Li C,Todem D

更新日期：2019-09-01 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：:Increasing the clinical applicability of functional neuroimaging technology is an emerging objective, e.g. for diagnostic and treatment purposes. We propose a novel Bayesian spatial hierarchical framework for predicting follow-up neural activity based on an individual's baseline functional neuroimaging data. Our appro...

journal_title：Statistical methods in medical research

authors： Derado G,Bowman FD,Zhang L,Alzheimer's Disease Neuroimaging Initiative Investigators.

更新日期：2013-08-01 00:00:00

abstract：:Medical research commonly relies on the combination of 2 x 2 tables of counted data for making inferences about treatment effects or about the causes of disease. This article reviews point estimation and interval estimation for a common odds ratio. Traditional methods for providing these estimates face special challen...

journal_title：Statistical methods in medical research

authors： Emerson JD

更新日期：1994-01-01 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：:Multilevel models were originally developed to allow linear regression or ANOVA models to be applied to observations that are not mutually independent. This lack of independence commonly arises due to clustering of the units of observations into 'higher level units' such as patients in hospitals. In linear mixed model...

journal_title：Statistical methods in medical research

authors： Rabe-Hesketh S,Yang S,Pickles A

更新日期：2001-12-01 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：:We propose a fully parametric model for the analysis of competing risks data where the types of failure may not be independent. We show how the dependence between the cause-specific survival times can be modelled with a copula function. Features include: identifiability of the problem; accessible understanding of the ...

journal_title：Statistical methods in medical research

authors： Escarela G,Carrière JF

更新日期：2003-08-01 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：:Spatial resolution plays an important role in functional magnetic resonance imaging studies as the signal-to-noise ratio increases linearly with voxel volume. In scientific studies, where functional magnetic resonance imaging is widely used, the standard spatial resolution typically used is relatively low which ensure...

journal_title：Statistical methods in medical research

authors： Liu Z,Bartsch AJ,Berrocal VJ,Johnson TD

更新日期：2019-04-01 00:00:00