Results 21 to 30 of about 12,232,356 (294)

Bayesian variable selection in linear quantile mixed models for longitudinal data with application to macular degeneration.

PLoS ONE, 2020
This paper presents a Bayesian analysis of linear mixed models for quantile regression based on a Cholesky decomposition for the covariance matrix of random effects.
Yonggang Ji, Haifang Shi
doaj   +1 more source

A family of partial-linear single-index models for analyzing complex environmental exposures with continuous, categorical, time-to-event, and longitudinal health outcomes

Environmental Health, 2020
Background Statistical methods to study the joint effects of environmental factors are of great importance to understand the impact of correlated exposures that may act synergistically or antagonistically on health outcomes.
Yuyan Wang, Yinxiang Wu, Melanie H. Jacobson, Myeonggyun Lee, Peng Jin, Leonardo Trasande, Mengling Liu   +6 more
doaj   +1 more source

An Empirical Comparison of Meta- and Mega-Analysis With Data From the ENIGMA Obsessive-Compulsive Disorder Working Group

Frontiers in Neuroinformatics, 2019
Objective: Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses.
Premika S. W. Boedhoe, Premika S. W. Boedhoe, Martijn W. Heymans, Lianne Schmaal, Lianne Schmaal, Yoshinari Abe, Pino Alonso, Pino Alonso, Pino Alonso, Stephanie H. Ameis, Stephanie H. Ameis, Alan Anticevic, Paul D. Arnold, Paul D. Arnold, Marcelo C. Batistuzzo, Francesco Benedetti, Jan C. Beucke, Irene Bollettini, Anushree Bose, Silvia Brem, Anna Calvo, Rosa Calvo, Rosa Calvo, Yuqi Cheng, Kang Ik K. Cho, Valentina Ciullo, Valentina Ciullo, Sara Dallaspezia, Damiaan Denys, Damiaan Denys, Jamie D. Feusner, Kate D. Fitzgerald, Jean-Paul Fouche, Egill A. Fridgeirsson, Patricia Gruner, Gregory L. Hanna, Derrek P. Hibar, Marcelo Q. Hoexter, Hao Hu, Chaim Huyser, Chaim Huyser, Neda Jahanshad, Anthony James, Norbert Kathmann, Christian Kaufmann, Kathrin Koch, Kathrin Koch, Jun Soo Kwon, Jun Soo Kwon, Luisa Lazaro, Luisa Lazaro, Luisa Lazaro, Luisa Lazaro, Christine Lochner, Rachel Marsh, Rachel Marsh, Ignacio Martínez-Zalacaín, David Mataix-Cols, José M. Menchón, José M. Menchón, José M. Menchón, Luciano Minuzzi, Astrid Morer, Astrid Morer, Astrid Morer, Takashi Nakamae, Tomohiro Nakao, Janardhanan C. Narayanaswamy, Seiji Nishida, Erika L. Nurmi, Joseph O'Neill, John Piacentini, Fabrizio Piras, Federica Piras, Y. C. Janardhan Reddy, Tim J. Reess, Tim J. Reess, Yuki Sakai, Yuki Sakai, Joao R. Sato, H. Blair Simpson, H. Blair Simpson, Noam Soreni, Carles Soriano-Mas, Carles Soriano-Mas, Carles Soriano-Mas, Gianfranco Spalletta, Gianfranco Spalletta, Michael C. Stevens, Michael C. Stevens, Philip R. Szeszko, Philip R. Szeszko, David F. Tolin, David F. Tolin, Guido A. van Wingen, Ganesan Venkatasubramanian, Susanne Walitza, Zhen Wang, Zhen Wang, Je-Yeon Yun, Je-Yeon Yun, ENIGMA-OCD Working-Group, Paul M. Thompson, Dan J. Stein, Odile A. van den Heuvel, Odile A. van den Heuvel, Jos W. R. Twisk   +106 more
doaj   +1 more source

Optimal Antibody Purification Strategies Using Data-Driven Models

Engineering, 2019
This work addresses the multiscale optimization of the purification processes of antibody fragments. Chromatography decisions in the manufacturing processes are optimized, including the number of chromatography columns and their sizes, the number of ...
Songsong Liu, Lazaros G. Papageorgiou
doaj   +1 more source

Comparison of regression-based and machine learning techniques to explain alpha diversity of fish communities in streams of central and eastern India

Ecological Indicators, 2021
Over the past several decades, ecologists have been striving to develop models that accurately describe species-habitat relationships across ecological communities.
Rubina Mondal, Anuradha Bhat
doaj   +1 more source

Prior elicitation and variable selection for bayesian quantile regression [PDF]

, 2013
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Bayesian subset selection suffers from three important difficulties: assigning priors over model space, assigning priors to all components of the regression
Al-Hamzawi, Rahim Jabbar Thaher
core   +7 more sources

Additive quantile mixed effects modelling with application to longitudinal CD4 count data

Scientific Reports, 2021
Quantile regression offers an invaluable tool to discern effects that would be missed by other conventional regression models, which are solely based on modeling conditional mean.
Ashenafi A. Yirga, Sileshi F. Melesse, Henry G. Mwambi, Dawit G. Ayele   +3 more
doaj   +1 more source

APPLICATION OF PENALIZED SPLINE-SPATIAL AUTOREGRESSIVE MODEL TO HIV CASE DATA IN INDONESIA

Barekeng, 2023
Spatial regression analysis is a statistical method used to perform modeling by considering spatial effects. Spatial models generally use a parametric approach by assuming a linear relationship between explanatory and response variables.
Nindi Pigitha, Anik Djuraidah, Aji Hamim Wigena   +2 more
doaj   +1 more source

Finite Mixtures of Generalized Linear Regression Models [PDF]

, 2007
Generalized linear models have become a standard technique in the statistical modelling toolbox for investigating relationships between variables.
Bettina Grün, Leisch, Friedrich, Friedrich Leisch, Grün, Bettina   +3 more
core   +1 more source

Quantile regression in linear mixed models: a stochastic approximation EM approach [PDF]

Statistics and Its Interface, 2017
This paper develops a likelihood-based approach to analyze quantile regression (QR) models for continuous longitudinal data via the asymmetric Laplace distribution (ALD). Compared to the conventional mean regression approach, QR can characterize the entire conditional distribution of the outcome variable and is more robust to the presence of outliers ...
Christian E, Galarza, Victor H, Lachos, Dipankar, Bandyopadhyay   +2 more
openaire   +2 more sources