Ying Yuan, Hoang Q. Nguyen, and Peter F. Thall. BAYESIAN DESIGNS FOR PHASE I –II CLINICAL TRIALS. Boca Raton, FL: Chapman and Hall/CRC Biostatistics Series. 310 pages, ISBN 9781498709552
(Source: Biometrical Journal)
Source: Biometrical Journal - November 1, 2017 Category: Biotechnology Authors: Silvia Calderazzo Tags: BOOK REVIEW Source Type: research
Variance component analysis to assess protein quantification in biomarker discovery. Application to MALDI ‐TOF mass spectrometry
Abstract
Controlling the technological variability on an analytical chain is critical for biomarker discovery. The sources of technological variability should be modeled, which calls for specific experimental design, signal processing, and statistical analysis. Furthermore, with unbalanced data, the various components of variability cannot be estimated with the sequential or adjusted sums of squares of usual software programs. We propose a novel approach to variance component analysis with application to the matrix‐assisted laser desorption/ionization time‐of‐flight (MALDI‐TOF) technology and use this approach for ...
Source: Biometrical Journal - November 1, 2017 Category: Biotechnology Authors: Catherine Mercier, Amna Klich, Caroline Truntzer, Vincent Picaud, Jean ‐François Giovannelli, Patrick Ducoroy, Pierre Grangeat, Delphine Maucort‐Boulch, Pascal Roy Tags: RESEARCH PAPER Source Type: research
Classification of early ‐stage non‐small cell lung cancer by weighing gene expression profiles with connectivity information
Abstract
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. In this article, we constructed three different genes’ connectivity inform...
Source: Biometrical Journal - November 1, 2017 Category: Biotechnology Authors: Ao Zhang, Suyan Tian Tags: RESEARCH PAPER Source Type: research
Estimating the DINA model parameters using the No ‐U‐Turn Sampler
Abstract
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 samp...
Source: Biometrical Journal - November 1, 2017 Category: Biotechnology Authors: Marcelo A. da Silva, Eduardo S. B. de Oliveira, Alina A. Davier, Jorge L. Baz án Tags: RESEARCH PAPER Source Type: research
On the necessity and design of studies comparing statistical methods
(Source: Biometrical Journal)
Source: Biometrical Journal - November 1, 2017 Category: Biotechnology Authors: Anne ‐Laure Boulesteix, Harald Binder, Michal Abrahamowicz, Willi Sauerbrei, Tags: LETTER TO THE EDITOR Source Type: research
Lyle D. Broemeling. BAYESIAN METHODS FOR REPEATED MEASURES. Boca Raton: Chapman & Hall/CRC Press, 568 pages, ISBN 978 ‐1‐4822‐4819‐7
(Source: Biometrical Journal)
Source: Biometrical Journal - November 1, 2017 Category: Biotechnology Authors: Peter Congdon Tags: BOOK REVIEW Source Type: research
Estimating multiple time ‐fixed treatment effects using a semi‐Bayes semiparametric marginal structural Cox proportional hazards regression model
Abstract
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 confidenc...
Source: Biometrical Journal - October 27, 2017 Category: Biotechnology Authors: Stephen R. Cole, Jessie K. Edwards, Daniel Westreich, Catherine R. Lesko, Bryan Lau, Michael J. Mugavero, W. Christopher Mathews, Joseph J. Eron, Sander Greenland, Tags: RESEARCH PAPER Source Type: research
Prediction errors for state occupation and transition probabilities in multi ‐state models
Abstract
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 pr...
Source: Biometrical Journal - October 25, 2017 Category: Biotechnology Authors: Cristian Spitoni, Violette Lammens, Hein Putter Tags: RESEARCH PAPER Source Type: research
Simulation ‐based evaluation of the linear‐mixed model in the presence of an increasing proportion of singletons
Abstract
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 child...
Source: Biometrical Journal - October 25, 2017 Category: Biotechnology Authors: Robin Bruyndonckx, Niel Hens, Marc Aerts Tags: RESEARCH PAPER Source Type: research
Selection of composite binary endpoints in clinical trials
Biometrical Journal,Volume 60, Issue 2, Page 246-261, March 2018. (Source: Biometrical Journal)
Source: Biometrical Journal - October 12, 2017 Category: Biotechnology Source Type: research
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Biometrical Journal,Volume 60, Issue 2, Page 246-261, March 2018. (Source: Biometrical Journal)
Source: Biometrical Journal - October 12, 2017 Category: Biotechnology Source Type: research
Hierarchical imputation of systematically and sporadically missing data: An approximate Bayesian approach using chained equations
Biometrical Journal,Volume 60, Issue 2, Page 333-351, March 2018. (Source: Biometrical Journal)
Source: Biometrical Journal - October 9, 2017 Category: Biotechnology Source Type: research
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Biometrical Journal,Volume 60, Issue 2, Page 333-351, March 2018. (Source: Biometrical Journal)
Source: Biometrical Journal - October 9, 2017 Category: Biotechnology Source Type: research
Testing R Code R. Cotton Boca Raton, FL: Chapman & Hall/CRC Press. 178 pages, ISBN 978 ‐1‐4987‐6365‐3
(Source: Biometrical Journal)
Source: Biometrical Journal - September 12, 2017 Category: Biotechnology Authors: Fabian Scheipl Tags: BOOK REVIEW Source Type: research
A sequential test for assessing observed agreement between raters
Abstract
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. In this paper, we introduce a nonparametric sequential test for assessing agreement, which can be applied as data accrues, does not require a contingency table, facilitating a rapid assessment of the agreement. The proposed test is based on the cumulative sum of the number of di...
Source: Biometrical Journal - September 12, 2017 Category: Biotechnology Authors: Sotiris Bersimis, Athanasios Sachlas, Subha Chakraborti Tags: RESEARCH PAPER Source Type: research
