A double-Cox model for non-proportional hazards survival analysis with frailty. [PDF]
Stat Med, 2023 The Cox regression, a semi‐parametric method of survival analysis, is extremely popular in biomedical applications. The proportional hazards assumption is a key requirement in the Cox model. To accommodate non‐proportional hazards, we propose to parameterize the shape parameter of the baseline hazard function using the additional, separate Cox ...
Begun A, Kulinskaya E, Ncube N.
europepmc +2 more sources
Encoding of low-quality DNA profiles as genotype probability matrices for improved profile comparisons, relatedness evaluation and database searches [PDF]
, 2016 Many DNA profiles recovered from crime scene samples are of a quality that does not allow them to be searched against, nor entered into, databases. We propose a method for the comparison of profiles arising from two DNA samples, one or both of which can ...
Balding, David J. +2 more
core +3 more sources
Inference of Temporally Varying Bayesian Networks [PDF]
, 2012 When analysing gene expression time series data an often overlooked but crucial aspect of the model is that the regulatory network structure may change over time.
Akam +10 more
core +3 more sources
Criteria for Bayesian model choice with application to variable selection [PDF]
, 2012 In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propose differing prior choices. We first formalize the most
Bayarri, M. J. +3 more
core +3 more sources
Gravitational-Wave Asteroseismology with Fundamental Modes from Compact Binary Inspirals [PDF]
, 2019 The first detection of gravitational waves (GWs) from the binary neutron star (NS) inspiral GW170817 has opened a unique channel for probing the fundamental properties of matter at supra-nuclear densities inaccessible elsewhere in the Universe.
Hinderer, Tanja +2 more
core +3 more sources
Approximate Bayesian Computation for a Class of Time Series Models [PDF]
, 2014 In the following article we consider approximate Bayesian computation (ABC) for certain classes of time series models. In particular, we focus upon scenarios where the likelihoods of the observations and parameter are intractable, by which we mean that ...
Jasra, Ajay
core +1 more source
Default Mode Network alterations in alexithymia: An EEG power spectra and connectivity study [PDF]
, 2016 Recent neuroimaging studies have shown that alexithymia is characterized by functional alterations in different brain areas [e.g., posterior cingulate cortex (PCC)], during emotional/social tasks.
Amoroso, Noemi +9 more
core +1 more source
Design-Based Ratio Estimators and Central Limit Theorems for Clustered, Blocked RCTs
, 2021 This article develops design-based ratio estimators for clustered, blocked randomized controlled trials (RCTs), with an application to a federally funded, school-based RCT testing the effects of behavioral health interventions.
Kautz, Tim +3 more
core +1 more source
Simulation-based model selection for dynamical systems in systems and population biology [PDF]
, 2010 Computer simulations have become an important tool across the biomedical sciences and beyond. For many important problems several different models or hypotheses exist and choosing which one best describes reality or observed data is not straightforward ...
Addy +41 more
core +3 more sources
Log-mean linear models for binary data [PDF]
, 2012 This paper introduces a novel class of models for binary data, which we call log-mean linear models. The characterizing feature of these models is that they are specified by linear constraints on the log-mean linear parameter, defined as a log-linear ...
A. Roverato +4 more
core +3 more sources