Penalized estimation in latent Markov models, with application to monitoring serum calcium levels in end ‐stage kidney insufficiency
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. We discuss model choice based on the Takeuchi Information Criterion. Simulations and a real‐data application to monitoring serum Calcium levels in end‐stage kidney disease are used for illustration. (Source: Biometrical Journal)
Source: Biometrical Journal - May 1, 2017 Category: Biotechnology Authors: Alessio Farcomeni Tags: Research Paper Source Type: research
Contribution to the discussion of “A critical evaluation of the current ‘p‐value controversy’”
(Source: Biometrical Journal)
Source: Biometrical Journal - May 1, 2017 Category: Biotechnology Authors: Werner Brannath Tags: Short Communication Source Type: research
Power Analysis of Trials with Multilevel Data. M. Moerbeek and S. Teerenstra (2016). Boca Raton, FL: Chapman & Hall/CRC Press. 288 Pages, ISBN: 9781498729895.
(Source: Biometrical Journal)
Source: Biometrical Journal - May 1, 2017 Category: Biotechnology Authors: Brady T. West Tags: Book review Source Type: research
Comparison of joint modeling and landmarking for dynamic prediction under an illness ‐death model
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. To circumvent the assumptions...
Source: Biometrical Journal - May 1, 2017 Category: Biotechnology Authors: Krithika Suresh, Jeremy M.G. Taylor, Daniel E. Spratt, Stephanie Daignault, Alexander Tsodikov Tags: Research Paper Source Type: research
A critical evaluation of the current “p‐value controversy”
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 larg...
Source: Biometrical Journal - May 1, 2017 Category: Biotechnology Authors: Stefan Wellek Tags: Review Article Source Type: research
