Results 41 to 50 of about 751 (132)

Simulation study on the impact of measurement errors in hierarchical Bayesian semi-parametric models

Computational and Mathematical Biophysics
This study examines the impact of measurement errors on parameter estimates within hierarchical Bayesian semiparametric (HBS) models, with a focus on the Lotka–Volterra predator–prey model as a case study.
Langat Amos Kipkorir, Mwalili Samuel Musili, Kazembe Lawrence Ndekeleni   +2 more
doaj   +1 more source

Optimal precision of coarse structural nested mean models to estimate the effect of initiating ART in early and acute HIV infection

Journal of Causal Inference
Time-dependent coarse structural nested mean models (coarse SNMMs) were developed to estimate treatment effects from longitudinal observational data. Coarse SNMMs estimate the combined effect of multiple treatment dosages and are thus useful to estimate ...
Lok Judith J.
doaj   +1 more source

Statistical, machine learning, and deep learning models for COVID-19 forecasting in Kenya

Computational and Mathematical Biophysics
This study aims to enhance coronavirus disease 2019 forecasting in Kenya by comparing the predictive performance of statistical, machine learning, and deep learning (DL) models for total cases, critical cases, severe cases, and total deaths, using data ...
Kiarie Joyce, Mwalili Samuel Musili, Mbogo Rachel, Mutinda John Kamwele, Langat Amos Kipkorir   +4 more
doaj   +1 more source

Sequential tests and estimates after overrunning based on $p$-value combination

, 2008
Often in sequential trials additional data become available after a stopping boundary has been reached. A method of incorporating such information from overrunning is developed, based on the ``adding weighted Zs'' method of combining $p$-values.
Ding, Keyue, Hall, W. J.
core   +1 more source

Markov modeling on dynamic state space for genetic disorders and infectious diseases with mutations: Probabilistic framework, parameter estimation, and applications

Computational and Mathematical Biophysics
The emergence and dynamic prevalence of genetic disorders and infectious diseases with mutations pose significant challenges for public health interventions.
Baranon Mouhamadou Djima, Weke Patrick Guge Oloo, Alladatin Judicaël, Ale Boni Maxime   +3 more
doaj   +1 more source

A Gibbs approach to Chargaff's second parity rule

, 2011
Chargaff's second parity rule (CSPR) asserts that the frequencies of short polynucleotide chains are the same as those of the complementary reversed chains.
A. Hart, Andrew Hart, B. Powdel, D. Mitchell, E. Chargaff, Felipe Olmos, G. Albrecht-Buehler, J. Lobry, N. Sueoka, R. Bowen, R. Forsdyke, R. Rudner, S. Zhang, S.-G. Kong, S.J. Bell, Servet Martínez, V. Prabhu, Z. Coelho   +17 more
core   +2 more sources

A causal framework for the self-controlled case series design

Journal of Causal Inference
Vaccine safety surveillance programs that monitor possible short-term rare adverse events following vaccination usually only have access to data on vaccinated individuals who experienced the event of interest.
Etiévant Lola, Gail Mitchell H., Follmann Dean   +2 more
doaj   +1 more source

Smoothing-inspired lack-of-fit tests based on ranks

, 2008
A rank-based test of the null hypothesis that a regressor has no effect on a response variable is proposed and analyzed. This test is identical in structure to the order selection test but with the raw data replaced by ranks. The test is nonparametric in
Hart, Jeffrey D.
core   +1 more source

Quantifying and estimating additive measures of interaction from case-control data

, 2017
In this paper we develop a general framework for quantifying how binary risk factors jointly influence a binary outcome. Our key result is an additive expansion of odds ratios as a sum of marginal effects and interaction terms of varying order.
Alfredsson, Lars, Hedström, Anna Karin, Hössjer, Ola, Kockum, Ingrid, Lekman, Magnus, Olsson, Tomas   +5 more
core   +1 more source

Bayesian hierarchical models for analysing the spatial distribution of bioclimatic indices [PDF]

, 2017
A methodological approach for modelling the spatial distribution of bioclimatic indices is proposed in this paper. The value of the bioclimatic index is modelled with a hierarchical Bayesian model that incorporates both structured and unstructured random
Barber, Antoni, Barber, Xavier, Conesa Ortega, David, Lopez-Quílez, Antonio, Mayoral, Asuncion, Morales, Javier   +5 more
core