A Bayesian scoring rule on clustered event data for familial risk assessment – An example from colorectal cancer screening
Abstract
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. The algorithm is able...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Anna K. Rieger, Ulrich R. Mansmann Tags: CASE STUDY Source Type: research
A general framework for constraint approaches to adjusted risk differences
Abstract
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 binomi...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Yuanyuan Tang, Michelle Xia, Liangrui Sun, John A. Spertus, Philip G. Jones Tags: RESEARCH PAPER Source Type: research
Test ‐compatible confidence intervals for adaptive two‐stage single‐arm designs with binary endpoint
Abstract
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. Test compatibility is achieved by ...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Kevin Kunzmann, Meinhard Kieser Tags: RESEARCH PAPER Source Type: research
Two ‐stage orthogonality based estimation for semiparametric varying‐coefficient models and its applications in analyzing AIDS data
Abstract
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. The developed procedures can be implemented separately and the resulting estimator...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Yan ‐Yong Zhao, Jin‐Guan Lin, Xu‐Guo Ye, Hong‐Xia Wang, Xing‐Fang Huang Tags: RESEARCH PAPER Source Type: research
A comparison of different ways of including baseline counts in negative binomial models for data from falls prevention trials
Abstract
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. Including the baseline count after log‐transformation as a reg...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Han Zheng, Alan Kimber, Victoria A. Goodwin, Ruth M. Pickering Tags: RESEARCH PAPER Source Type: research
A probabilistic network for the diagnosis of acute cardiopulmonary diseases
Abstract
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. In particular, we exploited an original reparameterization of Beta and categorical logistic r...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Alessandro Magrini, Davide Luciani, Federico M. Stefanini Tags: RESEARCH PAPER Source Type: research
Selection of composite binary endpoints in clinical trials
Abstract
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 en...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Marta Bofill Roig, Guadalupe G ómez Melis Tags: RESEARCH PAPER Source Type: research
Hierarchical imputation of systematically and sporadically missing data: An approximate Bayesian approach using chained equations
Abstract
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. Unfortunately, little is known about how to perform MI when both ty...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Shahab Jolani Tags: RESEARCH PAPER Source Type: research
COMPUTER AGE STATISTICAL INFERENCE B. Efron T. Hastie (2016). New York, NY: Cambridge University Press. 475 pages, ISBN 978 ‐1‐107‐14989‐2
(Source: Biometrical Journal)
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Harald Binder Tags: BOOK REVIEW Source Type: research
Multiple sensitive estimation and optimal sample size allocation in the item sum technique
This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sam...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Pier Francesco Perri, Mar ía del Mar Rueda García, Beatriz Cobo Rodríguez Tags: RESEARCH PAPER Source Type: research
Joint model selection of marginal mean regression and correlation structure for longitudinal data with missing outcome and covariates
Abstract
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 re...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Chung ‐Wei Shen, Yi‐Hau Chen Tags: RESEARCH PAPER Source Type: research
Bayesian estimation of multivariate normal mixtures with covariate ‐dependent mixing weights, with an application in antimicrobial resistance monitoring
Abstract
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. Data are collected within several countries and over a number of years. In addition, the sampled bacterial isolates were not tested for susceptibility against one antimicrobial, but rather against an entire range of substances. Interest is therefore in the analysis of the joint distribution of MIC data on tw...
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Stijn Jaspers, Arno št Komárek, Marc Aerts Tags: RESEARCH PAPER Source Type: research
Editorial for the discussion papers on the p ‐value controversy
(Source: Biometrical Journal)
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Authors: Marco Alf ò, Dankmar Böhning Tags: Short Communication Source Type: research
Contents: Biometrical Journal 5'17
(Source: Biometrical Journal)
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Tags: Contents Source Type: research
Masthead: Biometrical Journal 5'17
(Source: Biometrical Journal)
Source: Biometrical Journal - September 1, 2017 Category: Biotechnology Tags: Masthead Source Type: research
