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    1033 results match your criteria Biometrical Journal [Journal]

    1 OF 21

    Joint model selection of marginal mean regression and correlation structure for longitudinal data with missing outcome and covariates.
    Biom J 2017 Sep 14. Epub 2017 Sep 14.
    Institute of Statistical Science, Academia Sinica, Taipei, Taiwan, 11529, R.O.C.
    This work develops a joint model selection criterion for simultaneously selecting the marginal mean regression and the correlation/covariance structure in longitudinal data analysis where both the outcome and the covariate variables may be subject to general intermittent patterns of missingness under the missing at random mechanism. The new proposal, termed "joint longitudinal information criterion" (JLIC), is based on the expected quadratic error for assessing model adequacy, and the second-order weighted generalized estimating equation (WGEE) estimation for mean and covariance models. Simulation results reveal that JLIC outperforms existing methods performing model selection for the mean regression and the correlation structure in a two stage and hence separate manner. Read More

    A sequential test for assessing observed agreement between raters.
    Biom J 2017 Sep 12. Epub 2017 Sep 12.
    Department of Information Systems, Statistics and Management Science, University of Alabama, AL, 35487, USA.
    Assessing the agreement between two or more raters is an important topic in medical practice. Existing techniques, which deal with categorical data, are based on contingency tables. This is often an obstacle in practice as we have to wait for a long time to collect the appropriate sample size of subjects to construct the contingency table. Read More

    Bayesian estimation of multivariate normal mixtures with covariate-dependent mixing weights, with an application in antimicrobial resistance monitoring.
    Biom J 2017 Sep 12. Epub 2017 Sep 12.
    Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, BE3590, Diepenbeek, Belgium.
    Bacteria with a reduced susceptibility against antimicrobials pose a major threat to public health. Therefore, large programs have been set up to collect minimum inhibition concentration (MIC) values. These values can be used to monitor the distribution of the nonsusceptible isolates in the general population. Read More

    A comparison of group prediction approaches in longitudinal discriminant analysis.
    Biom J 2017 Aug 21. Epub 2017 Aug 21.
    Department of Biostatistics, University of Liverpool, Liverpool, UK.
    Longitudinal discriminant analysis (LoDA) can be used to classify patients into prognostic groups based on their clinical history, which often involves longitudinal measurements of various clinically relevant markers. Patients' longitudinal data is first modelled using multivariate generalised linear mixed models, allowing markers of different types (e.g. Read More

    Bayesian joint modeling of bivariate longitudinal and competing risks data: An application to study patient-ventilator asynchronies in critical care patients.
    Biom J 2017 Aug 11. Epub 2017 Aug 11.
    Critical Care Center, Parc Taulí University Hospital, Institut d'Investigació i Innovació Parc Taulí (I3PT), Universitat Autònoma de Barcelona, Sabadell, Spain.
    Mechanical ventilation is a common procedure of life support in intensive care. Patient-ventilator asynchronies (PVAs) occur when the timing of the ventilator cycle is not simultaneous with the timing of the patient respiratory cycle. The association between severity markers and the events death or alive discharge has been acknowledged before, however, little is known about the addition of PVAs data to the analyses. Read More

    Flexible Bayesian additive joint models with an application to type 1 diabetes research.
    Biom J 2017 Aug 10. Epub 2017 Aug 10.
    Department of Statistics, Ludwig-Maximilians-Universität München, München, Germany.
    The joint modeling of longitudinal and time-to-event data is an important tool of growing popularity to gain insights into the association between a biomarker and an event process. We develop a general framework of flexible additive joint models that allows the specification of a variety of effects, such as smooth nonlinear, time-varying and random effects, in the longitudinal and survival parts of the models. Our extensions are motivated by the investigation of the relationship between fluctuating disease-specific markers, in this case autoantibodies, and the progression to the autoimmune disease type 1 diabetes. Read More

    Dynamic predictions with time-dependent covariates in survival analysis using joint modeling and landmarking.
    Biom J 2017 Aug 9. Epub 2017 Aug 9.
    Department of Biostatistics, Erasmus Medical Center, The Netherlands.
    A key question in clinical practice is accurate prediction of patient prognosis. To this end, nowadays, physicians have at their disposal a variety of tests and biomarkers to aid them in optimizing medical care. These tests are often performed on a regular basis in order to closely follow the progression of the disease. Read More

    Random walk designs for selecting pool sizes in group testing estimation with small samples.
    Biom J 2017 Aug 9. Epub 2017 Aug 9.
    Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, MD, 21250, USA.
    Group testing estimation, which utilizes pooled rather than individual units for testing, has been an ongoing area of research for over six decades. While it is often argued that such methods can yield large savings in terms of resources and/or time, these benefits depend very much on the initial choice of pool sizes. In fact, when poor group sizes are used, the results can be much worse than those obtained using standard techniques. Read More

    Addressing small sample size bias in multiple-biomarker trials: Inclusion of biomarker-negative patients and Firth correction.
    Biom J 2017 Aug 1. Epub 2017 Aug 1.
    Department of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
    In recent years, numerous approaches for biomarker-based clinical trials have been developed. One of these developments are multiple-biomarker trials, which aim to investigate multiple biomarkers simultaneously in independent subtrials. For low-prevalence biomarkers, small sample sizes within the subtrials have to be expected, as well as many biomarker-negative patients at the screening stage. Read More

    Prediction accuracy and variable selection for penalized cause-specific hazards models.
    Biom J 2017 Aug 1. Epub 2017 Aug 1.
    Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
    We consider modeling competing risks data in high dimensions using a penalized cause-specific hazards (CSHs) approach. CSHs have conceptual advantages that are useful for analyzing molecular data. First, working on hazards level can further understanding of the underlying biological mechanisms that drive transition hazards. Read More

    Decision-theoretic designs for a series of trials with correlated treatment effects using the Sarmanov multivariate beta-binomial distribution.
    Biom J 2017 Jul 26. Epub 2017 Jul 26.
    Statistics and Epidemiology, Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK.
    The motivation for the work in this article is the setting in which a number of treatments are available for evaluation in phase II clinical trials and where it may be infeasible to try them concurrently because the intended population is small. This paper introduces an extension of previous work on decision-theoretic designs for a series of phase II trials. The program encompasses a series of sequential phase II trials with interim decision making and a single two-arm phase III trial. Read More

    Characterizing cross-subject spatial interaction patterns in functional magnetic resonance imaging studies: A two-stage point-process model.
    Biom J 2017 Jul 12. Epub 2017 Jul 12.
    Department of Neurology and Department of Radiology, University of Washington, Seattle, WA, 98185, USA.
    We develop a two-stage spatial point process model that introduces new characterizations of activation patterns in multisubject functional Magnetic Resonance Imaging (fMRI) studies. Conventionally multisubject fMRI methods rely on combining information across subjects one voxel at a time in order to identify locations of peak activation in the brain. The two-stage model that we develop here addresses shortcomings of standard methods by explicitly modeling the spatial structure of functional signals and recognizing that corresponding cross-subject functional signals can be spatially misaligned. Read More

    A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests.
    Biom J 2017 Jul 10. Epub 2017 Jul 10.
    Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec H3A 1A2, Canada.
    Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Read More

    Multilevel covariance regression with correlated random effects in the mean and variance structure.
    Biom J 2017 Sep 10;59(5):1047-1066. Epub 2017 Jul 10.
    KU Leuven, I-BioStat, Kapucijnenvoer 35, B3000, Leuven, Belgium.
    Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. Read More

    A flexible multivariate random effects proportional odds model with application to adverse effects during radiation therapy.
    Biom J 2017 Jul 10. Epub 2017 Jul 10.
    Institute for Medical Biometry and Statistics, University of Freiburg, Stefan-Meier-Str. 26, 79104, Freiburg, Germany.
    Radiation therapy in patients with head and neck cancer has a toxic effect on mucosa, the soft tissue in and around the mouth. Hence mucositis is a serious common side effect and is a condition characterized by pain and inflammation of the surface of the mucosa. Although the mucosa recovers during breaks of and following the radiotherapy course, the recovery will depend on the type of tissue involved and on its location. Read More

    Mixture model with multiple allocations for clustering spatially correlated observations in the analysis of ChIP-Seq data.
    Biom J 2017 Jun 30. Epub 2017 Jun 30.
    Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Nijenborgh 9, 9747 AG Groningen, The Netherlands.
    Model-based clustering is a technique widely used to group a collection of units into mutually exclusive groups. There are, however, situations in which an observation could in principle belong to more than one cluster. In the context of next-generation sequencing (NGS) experiments, for example, the signal observed in the data might be produced by two (or more) different biological processes operating together and a gene could participate in both (or all) of them. Read More

    Studying the relationship between a woman's reproductive lifespan and age at menarche using a Bayesian multivariate structured additive distributional regression model.
    Biom J 2017 Jun 29. Epub 2017 Jun 29.
    Faculty of Medicine, University of Coimbra, Rua Larga, 3004-504, Coimbra, Portugal.
    Studies addressing breast cancer risk factors have been looking at trends relative to age at menarche and menopause. These studies point to a downward trend of age at menarche and an upward trend for age at menopause, meaning an increase of a woman's reproductive lifespan cycle. In addition to studying the effect of the year of birth on the expectation of age at menarche and a woman's reproductive lifespan, it is important to understand how a woman's cohort affects the correlation between these two variables. Read More

    Multivariate binary classification of imbalanced datasets-A case study based on high-dimensional multiplex autoimmune assay data.
    Biom J 2017 Sep 19;59(5):948-966. Epub 2017 Jun 19.
    Department of Mathematical Statistics with Applications in Biometrics, Faculty of Statistics, Technical University Dortmund, Vogelpothsweg 87, 44227, Dortmund, Germany.
    The classification of a population by a specific trait is a major task in medicine, for example when in a diagnostic setting groups of patients with specific diseases are identified, but also when in predictive medicine a group of patients is classified into specific disease severity classes that might profit from different treatments. When the sizes of those subgroups become small, for example in rare diseases, imbalances between the classes are more the rule than the exception and make statistical classification problematic when the error rate of the minority class is high. Many observations are classified as belonging to the majority class, while the error rate of the majority class is low. Read More

    Fast precision estimation in high-dimensional multivariate joint models.
    Biom J 2017 Jun 16. Epub 2017 Jun 16.
    I-BioStat, KU Leuven, Kapucijnenvoer 35 blok d - box 7001, BE3000 Leuven, Belgium.
    A fast way is proposed based on the multiple outputation idea (Hoffman et al., ; Follmann et al., ) to calculate the precision of parameter estimates for high-dimensional multivariate joint models using a pairwise approach (Fieuws and Verbeke, ; Fieuws et al. Read More

    Stratified exact tests for the weak causal null hypothesis in randomized trials with a binary outcome.
    Biom J 2017 Sep 12;59(5):986-997. Epub 2017 Jun 12.
    Clinical Research Center, Kinki University Hospital, 377-2 Ohno-higashi, Osakasayama, Osaka, Japan.
    Fisher's exact test is commonly used to compare two groups when the outcome is binary in randomized trials. In the context of causal inference, this test explores the sharp causal null hypothesis (i.e. Read More

    Penalized estimation in latent Markov models, with application to monitoring serum calcium levels in end-stage kidney insufficiency.
    Biom J 2017 Sep 8;59(5):1035-1046. Epub 2017 Jun 8.
    Department of Public Health and Infectious Diseases (Sapienza-University of Rome), Piazzale Aldo Moro, 5, 00185, Roma, Italy.
    We introduce a penalized likelihood form for latent Markov models. We motivate its use for biomedical applications where the sample size is in the order of the tens, or at most hundreds, and there are only few repeated measures. The resulting estimates never break down, while spurious solutions are often obtained by maximizing the likelihood itself. Read More

    Comparison of joint modeling and landmarking for dynamic prediction under an illness-death model.
    Biom J 2017 May 16. Epub 2017 May 16.
    Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.
    Dynamic prediction incorporates time-dependent marker information accrued during follow-up to improve personalized survival prediction probabilities. At any follow-up, or "landmark", time, the residual time distribution for an individual, conditional on their updated marker values, can be used to produce a dynamic prediction. To satisfy a consistency condition that links dynamic predictions at different time points, the residual time distribution must follow from a prediction function that models the joint distribution of the marker process and time to failure, such as a joint model. Read More

    A spatially balanced design with probability function proportional to the within sample distance.
    Biom J 2017 Sep 16;59(5):1067-1084. Epub 2017 May 16.
    Istat, Directorate for Methodology and Statistical Process Design, Via Cesare Balbo 16, Rome, IT-00184, Italy.
    The units observed in a biological, agricultural, and environmental survey are often randomly selected from a finite population whose main feature is to be geo-referenced thus its spatial distribution should be used as essential information in designing the sample. In particular our interest is focused on probability samples that are well spread over the population in every dimension which in recent literature are defined as spatially balanced samples. To approach the problem we used the within sample distance as the summary index of the spatial distribution of a random selection criterion. Read More

    A critical evaluation of the current "p-value controversy".
    Biom J 2017 Sep 15;59(5):854-872. Epub 2017 May 15.
    Department of Biostatistics, CIMH Mannheim, Mannheim Medical School of the University of Heidelberg, D-68159, Mannheim, J5, Germany.
    This article has been triggered by the initiative launched in March 2016 by the Board of Directors of the American Statistical Association (ASA) to counteract the current p-value focus of statistical research practices that allegedly "have contributed to a reproducibility crisis in science." It is pointed out that in the very wide field of statistics applied to medicine, many of the problems raised in the ASA statement are not as severe as in the areas the authors may have primarily in mind, although several of them are well-known experts in biostatistics and epidemiology. This is mainly due to the fact that a large proportion of medical research falls under the realm of a well developed body of regulatory rules banning the most frequently occurring misuses of p-values. Read More

    Comparing dependent kappa coefficients obtained on multilevel data.
    Biom J 2017 Sep 2;59(5):1016-1034. Epub 2017 May 2.
    Methodology and Statistics, CAPHRI, Maastricht University, P. Debyeplein 1, 6229, HA Maastricht, The Netherlands.
    Reliability and agreement are two notions of paramount importance in medical and behavioral sciences. They provide information about the quality of the measurements. When the scale is categorical, reliability and agreement can be quantified through different kappa coefficients. Read More

    Joint analysis of longitudinal and survival AIDS data with a spatial fraction of long-term survivors: A Bayesian approach.
    Biom J 2017 May 2. Epub 2017 May 2.
    Centro de Estatística e Aplicações da Universidade de Lisboa (CEAUL), Bloco C6 - Piso 4, Campo Grande, 1749-016, Lisboa, Portugal.
    A typical survival analysis with time-dependent covariates usually does not take into account the possible random fluctuations or the contamination by measurement errors of the variables. Ignoring these sources of randomness may cause bias in the estimates of the model parameters. One possible way for overcoming that limitation is to consider a longitudinal model for the time-varying covariates jointly with a survival model for the time to the event of interest, thereby taking advantage of the complementary information flowing between these two-model outcomes. Read More

    Contribution to the discussion of '"A critical evaluation of the current p-value controversy"'.
    Biom J 2017 Sep 27;59(5):892-894. Epub 2017 Apr 27.
    Methodology and Statistics, Luxembourg Institute of Health, 1445, Strassen, Luxembourg.
    I pick up a very few points of minor disagreement with Stefan Wellek's comprehensive review of P-values in this journal. I conclude that P-values have a limited function in statistical inference but can nevertheless have their uses. Read More

    An improved uniformly more powerful exact Fisher-Hayter pairwise comparisons procedure.
    Biom J 2017 Jul 24;59(4):767-775. Epub 2017 Apr 24.
    Department of Statistics, University of California, Riverside, CA, 92521, USA.
    Pairwise comparison is a very common multiple comparison problem. It is known that Fisher's LSD test does not control the familywise error rate (FWER) when there are more than three groups to be compared. Improved testing strategies include the Tukey-Kramer (TK) test that eliminates the F-test step and the two-step Fisher-Hayter (FH) test which requires a significant F-test. Read More

    Using predictions from a joint model for longitudinal and survival data to inform the optimal time of intervention in an abdominal aortic aneurysm screening programme.
    Biom J 2017 Apr 24. Epub 2017 Apr 24.
    Department of Public Health and Primary Care, Cardiovascular Epidemiology Unit, Worts Causeway, Cambridge CB1 8RN, UK.
    Joint models of longitudinal and survival data can be used to predict the risk of a future event occurring based on the evolution of an endogenous biomarker measured repeatedly over time. This has led naturally to the use of dynamic predictions that update each time a new longitudinal measurement is provided. In this paper, we show how such predictions can be utilised within a fuller decision modelling framework, in particular to allow planning of future interventions for patients under a 'watchful waiting' care pathway. Read More

    Clustering multiply imputed multivariate high-dimensional longitudinal profiles.
    Biom J 2017 Sep 24;59(5):998-1015. Epub 2017 Apr 24.
    I-BioStat, Universiteit Hasselt, Agoralaan, B-3590, Diepenbeek, Belgium.
    In this paper, we propose a method to cluster multivariate functional data with missing observations. Analysis of functional data often encompasses dimension reduction techniques such as principal component analysis (PCA). These techniques require complete data matrices. Read More

    Propensity scores based methods for estimating average treatment effect and average treatment effect among treated: A comparative study.
    Biom J 2017 Sep 24;59(5):967-985. Epub 2017 Apr 24.
    Department of Bioinformatics and Biostatisitcs, University of Louisville, Louisville, KY, USA.
    Propensity score based statistical methods, such as matching, regression, stratification, inverse probability weighting (IPW), and doubly robust (DR) estimating equations, have become popular in estimating average treatment effect (ATE) and average treatment effect among treated (ATT) in observational studies. Propensity score is the conditional probability receiving a treatment assignment with given covariates, and propensity score is usually estimated by logistic regression. However, a misspecification of the propensity score model may result in biased estimates for ATT and ATE. Read More

    An empirical Bayes approach to network recovery using external knowledge.
    Biom J 2017 Sep 10;59(5):932-947. Epub 2017 Apr 10.
    Department of Mathematics, Vrije Universiteit Amsterdam, De Boelelaan 1081, 1081, HV Amsterdam, The Netherlands.
    Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior knowledge on the network topology. In the case of gene interaction networks such knowledge may come for instance from pathway repositories like KEGG, or be inferred from data of a pilot study. The Bayesian framework provides a natural means of including such prior knowledge. Read More

    A unified framework for weighted parametric multiple test procedures.
    Biom J 2017 Sep 29;59(5):918-931. Epub 2017 Mar 29.
    Novartis Pharma AG, 4002, Basel, Switzerland.
    We describe a general framework for weighted parametric multiple test procedures based on the closure principle. We utilize general weighting strategies that can reflect complex study objectives and include many procedures in the literature as special cases. The proposed weighted parametric tests bridge the gap between rejection rules using either adjusted significance levels or adjusted p-values. Read More

    Multinomial additive hazard model to assess the disability burden using cross-sectional data.
    Biom J 2017 Sep 23;59(5):901-917. Epub 2017 Mar 23.
    Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Universiteit Hasselt, Diepenbeek, Belgium.
    Population aging is accompanied by the burden of chronic diseases and disability. Chronic diseases are among the main causes of disability, which is associated with poor quality of life and high health care costs in the elderly. The identification of which chronic diseases contribute most to the disability prevalence is important to reduce the burden. Read More

    Boosting joint models for longitudinal and time-to-event data.
    Biom J 2017 Mar 21. Epub 2017 Mar 21.
    Department of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Waldstraße 6, 91054, Erlangen, Germany.
    Joint models for longitudinal and time-to-event data have gained a lot of attention in the last few years as they are a helpful technique clinical studies where longitudinal outcomes are recorded alongside event times. Those two processes are often linked and the two outcomes should thus be modeled jointly in order to prevent the potential bias introduced by independent modeling. Commonly, joint models are estimated in likelihood-based expectation maximization or Bayesian approaches using frameworks where variable selection is problematic and that do not immediately work for high-dimensional data. Read More

    A generalized mixture model applied to diabetes incidence data.
    Biom J 2017 Jul 21;59(4):826-842. Epub 2017 Mar 21.
    Departamento de Estatística, Universidade Federal de Sao Carlos, Rod. Washington Luís, Km 235, SP 310 Sao Carlos, São Paulo, 13565-905, Brazil.
    We present a generalization of the usual (independent) mixture model to accommodate a Markovian first-order mixing distribution. We propose the data-driven reversible jump, a Markov chain Monte Carlo (MCMC) procedure, for estimating the a posteriori probability for each model in a model selection procedure and estimating the corresponding parameters. Simulated datasets show excellent performance of the proposed method in the convergence, model selection, and precision of parameters estimates. Read More

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