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Biometrical Journal. Biometrische Zeitschrift

Ao Zhang, Suyan Tian
Pathway-based feature selection algorithms, which utilize biological information contained in pathways to guide which features/genes should be selected, have evolved quickly and become widespread in the field of bioinformatics. Based on how the pathway information is incorporated, we classify pathway-based feature selection algorithms into three major categories-penalty, stepwise forward, and weighting. Compared to the first two categories, the weighting methods have been underutilized even though they are usually the simplest ones...
December 5, 2017: Biometrical Journal. Biometrische Zeitschrift
Marcelo A da Silva, Eduardo S B de Oliveira, Alina A von Davier, Jorge L Bazán
The deterministic inputs, noisy, "and" gate (DINA) model is a popular cognitive diagnosis model (CDM) in psychology and psychometrics used to identify test takers' profiles with respect to a set of latent attributes or skills. In this work, we propose an estimation method for the DINA model with the No-U-Turn Sampler (NUTS) algorithm, an extension to Hamiltonian Monte Carlo (HMC) method. We conduct a simulation study in order to evaluate the parameter recovery and efficiency of this new Markov chain Monte Carlo method and to compare it with two other Bayesian methods, the Metropolis Hastings and Gibbs sampling algorithms, and with a frequentist method, using the Expectation-Maximization (EM) algorithm...
December 1, 2017: Biometrical Journal. Biometrische Zeitschrift
Anne-Laure Boulesteix, Harald Binder, Michal Abrahamowicz, Willi Sauerbrei
No abstract text is available yet for this article.
November 29, 2017: Biometrical Journal. Biometrische Zeitschrift
Anna K Rieger, Ulrich R Mansmann
Colorectal cancer screening is well established. The identification of high risk populations is the key to implement effective risk-adjusted screening. Good statistical approaches for risk prediction do not exist. The family's colorectal cancer history is used for identification of high risk families and usually assessed by a questionnaire. This paper introduces a prediction algorithm to designate a family for colorectal cancer risk and discusses its statistical properties. The new algorithm uses Bayesian reasoning and a detailed family history illustrated by a pedigree and a Lexis diagram...
November 8, 2017: Biometrical Journal. Biometrische Zeitschrift
Yuanyuan Tang, Michelle Xia, Liangrui Sun, John A Spertus, Philip G Jones
The risk difference is an intelligible measure for comparing disease incidence in two exposure or treatment groups. Despite its convenience in interpretation, it is less prevalent in epidemiological and clinical areas where regression models are required in order to adjust for confounding. One major barrier to its popularity is that standard linear binomial or Poisson regression models can provide estimated probabilities out of the range of (0,1), resulting in possible convergence issues. For estimating adjusted risk differences, we propose a general framework covering various constraint approaches based on binomial and Poisson regression models...
November 7, 2017: Biometrical Journal. Biometrische Zeitschrift
Luca Grassano, Guido Pagana, Marco Daperno, Enrico Bibbona, Mauro Gasparini
In clinical research and in more general classification problems, a frequent concern is the reliability of a rating system. In the absence of a gold standard, agreement may be considered as an indication of reliability. When dealing with categorical data, the well-known kappa statistic is often used to measure agreement. The aim of this paper is to obtain a theoretical result about the asymptotic distribution of the kappa statistic with multiple items, multiple raters, multiple conditions, and multiple rating categories (more than two), based on recent work...
November 7, 2017: Biometrical Journal. Biometrische Zeitschrift
Kevin Kunzmann, Meinhard Kieser
Inference after two-stage single-arm designs with binary endpoint is challenging due to the nonunique ordering of the sampling space in multistage designs. We illustrate the problem of specifying test-compatible confidence intervals for designs with nonconstant second-stage sample size and present two approaches that guarantee confidence intervals consistent with the test decision. Firstly, we extend the well-known Clopper-Pearson approach of inverting a family of two-sided hypothesis tests from the group-sequential case to designs with fully adaptive sample size...
October 27, 2017: Biometrical Journal. Biometrische Zeitschrift
Stephen R Cole, Jessie K Edwards, Daniel Westreich, Catherine R Lesko, Bryan Lau, Michael J Mugavero, W Christopher Mathews, Joseph J Eron, Sander Greenland
Marginal structural models for time-fixed treatments fit using inverse-probability weighted estimating equations are increasingly popular. Nonetheless, the resulting effect estimates are subject to finite-sample bias when data are sparse, as is typical for large-sample procedures. Here we propose a semi-Bayes estimation approach which penalizes or shrinks the estimated model parameters to improve finite-sample performance. This approach uses simple symmetric data-augmentation priors. Limited simulation experiments indicate that the proposed approach reduces finite-sample bias and improves confidence-interval coverage when the true values lie within the central "hill" of the prior distribution...
October 27, 2017: Biometrical Journal. Biometrische Zeitschrift
Yan-Yong Zhao, Jin-Guan Lin, Xu-Guo Ye, Hong-Xia Wang, Xing-Fang Huang
Semiparametric smoothing methods are usually used to model longitudinal data, and the interest is to improve efficiency for regression coefficients. This paper is concerned with the estimation in semiparametric varying-coefficient models (SVCMs) for longitudinal data. By the orthogonal projection method, local linear technique, quasi-score estimation, and quasi-maximum likelihood estimation, we propose a two-stage orthogonality-based method to estimate parameter vector, coefficient function vector, and covariance function...
October 26, 2017: Biometrical Journal. Biometrische Zeitschrift
Robin Bruyndonckx, Niel Hens, Marc Aerts
Data in medical sciences often have a hierarchical structure with lower level units (e.g. children) nested in higher level units (e.g. departments). Several specific but frequently studied settings, mainly in longitudinal and family research, involve a large number of units that tend to be quite small, with units containing only one element referred to as singletons. Regardless of sparseness, hierarchical data should be analyzed with appropriate methodology such as, for example linear-mixed models. Using a simulation study, based on the structure of a data example on Ceftriaxone consumption in hospitalized children, we assess the impact of an increasing proportion of singletons (0-95%), in data with a low, medium, or high intracluster correlation, on the stability of linear-mixed models parameter estimates, confidence interval coverage and F test performance...
October 25, 2017: Biometrical Journal. Biometrische Zeitschrift
Cristian Spitoni, Violette Lammens, Hein Putter
In this paper, we consider the estimation of prediction errors for state occupation probabilities and transition probabilities for multistate time-to-event data. We study prediction errors based on the Brier score and on the Kullback-Leibler score and prove their properness. In the presence of right-censored data, two classes of estimators, based on inverse probability weighting and pseudo-values, respectively, are proposed, and consistency properties of the proposed estimators are investigated. The second part of the paper is devoted to the estimation of dynamic prediction errors for state occupation probabilities for multistate models, conditional on being alive, and for transition probabilities...
October 25, 2017: Biometrical Journal. Biometrische Zeitschrift
Han Zheng, Alan Kimber, Victoria A Goodwin, Ruth M Pickering
A common design for a falls prevention trial is to assess falling at baseline, randomize participants into an intervention or control group, and ask them to record the number of falls they experience during a follow-up period of time. This paper addresses how best to include the baseline count in the analysis of the follow-up count of falls in negative binomial (NB) regression. We examine the performance of various approaches in simulated datasets where both counts are generated from a mixed Poisson distribution with shared random subject effect...
October 25, 2017: Biometrical Journal. Biometrische Zeitschrift
Alessandro Magrini, Davide Luciani, Federico M Stefanini
In this paper, the development of a probabilistic network for the diagnosis of acute cardiopulmonary diseases is presented in detail. A panel of expert physicians collaborated to specify the qualitative part, which is a directed acyclic graph defining a factorization of the joint probability distribution of domain variables into univariate conditional distributions. The quantitative part, which is a set of parametric models defining these univariate conditional distributions, was estimated following the Bayesian paradigm...
October 13, 2017: Biometrical Journal. Biometrische Zeitschrift
Marta Bofill Roig, Guadalupe Gómez Melis
The choice of a primary endpoint is an important issue when designing a clinical trial. It is common to use composite endpoints as a primary endpoint because it increases the number of observed events, captures more information and is expected to increase the power. However, combining events that have no similar clinical importance and have different treatment effects makes the interpretation of the results cumbersome and might reduce the power of the corresponding tests. Gómez and Lagakos proposed the ARE (asymptotic relative efficiency) method to choose between a composite or one of its components as primary endpoint comparing the efficacy of a treatment based on the times to each of these endpoints...
October 12, 2017: Biometrical Journal. Biometrische Zeitschrift
Shahab Jolani
In health and medical sciences, multiple imputation (MI) is now becoming popular to obtain valid inferences in the presence of missing data. However, MI of clustered data such as multicenter studies and individual participant data meta-analysis requires advanced imputation routines that preserve the hierarchical structure of data. In clustered data, a specific challenge is the presence of systematically missing data, when a variable is completely missing in some clusters, and sporadically missing data, when it is partly missing in some clusters...
October 9, 2017: Biometrical Journal. Biometrische Zeitschrift
Pier Francesco Perri, María Del Mar Rueda García, Beatriz Cobo Rodríguez
For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity...
September 27, 2017: Biometrical Journal. Biometrische Zeitschrift
Ipek Guler, Christel Faes, Carmen Cadarso-Suárez, Laetitia Teixeira, Anabela Rodrigues, Denisa Mendonça
In many follow-up studies different types of outcomes are collected including longitudinal measurements and time-to-event outcomes. Commonly, it is of interest to study the association between them. Joint modeling approaches of a single longitudinal outcome and survival process have recently gained increasing attention from both frequentist and Bayesian perspective. However, in many studies several longitudinal biomarkers are of interest and instead of selecting one single biomarker, the relationships between all these outcomes and their association with survival needs to be investigated...
November 2017: Biometrical Journal. Biometrische Zeitschrift
Il Do Ha, Maengseok Noh, Youngjo Lee
In longitudinal studies, a subject may have different types of outcomes that could be correlated. For example, a response variable of interest would be measured repeatedly over time on the same subject and at the same time, an event time representing a single event or competing-risks event is also observed. In this paper, we propose a joint modeling framework that accounts for the inherent association between such multiple outcomes via frailties (unobserved random effects). Among outcomes, at least one outcome is an event time that has a type of a single event or competing-risks event...
November 2017: Biometrical Journal. Biometrische Zeitschrift
Carmen Cadarso Suárez, Nadja Klein, Thomas Kneib, Geert Molenberghs, Dimitris Rizopoulos
No abstract text is available yet for this article.
November 2017: Biometrical Journal. Biometrische Zeitschrift
Elisa Duarte, Bruno de Sousa, Carmen Cadarso-Suárez, Nadja Klein, Thomas Kneib, Vítor Rodrigues
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...
November 2017: Biometrical Journal. Biometrische Zeitschrift
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