Search results for "Random effect"
showing 10 items of 57 documents
Change-point estimation in piecewise constant regression models and extensions
2015
Mortality associated with cardiovascular disease in patients with COVID-19
2020
Introducción y objetivos: Las enfermedades cardiovasculares (ECV) se han identificado como un factor de riesgo de mal pronóstico en pacientes con infección por COVID-19. Métodos: Se realizó un metanálisis de estudios actualmente disponibles con la prevalencia de ECV en supervivientes frente a no supervivientes en pacientes con infección por COVID-19 hasta el 16 de julio de 2020. Los análisis se realizaron mediante un modelo de efectos aleatorios y sensibilidad. Se realizaron análisis para identificar posibles fuentes de heterogeneidad o evaluar los efectos de los estudios pequeños. Resultados: Se incluyó a 307.596 pacientes de 16 estudios, de los que 46.321 (15,1%) tenían ECV. La tasa de mo…
Orthotopic Liver Transplantation: T-Tube or Not T-Tube? Systematic Review and Meta-Analysis of Results
2009
Background The purpose of this study was to compare outcomes after duct-to-duct anastomoses with or without biliary T-tube in orthotopic liver transplantation. Methods We pooled the outcomes of 1027 patients undergoing choledocho-choledochostomy with or without T-tube in 9 of 46 screened trials by means of fixed or random effects models. Results The "without T-tube" and "with T-tube" groups had equivalent outcomes for: anastomotic bile leaks or fistulas, choledocho-jejunostomy revisions, dilatation and stenting, hepatic artery thromboses, retransplantation, and mortality due to biliary complications. The "without T-tube" group had better outcomes when considering "fewer episodes of cholangi…
Bayesian joint models for longitudinal and survival data
2020
This paper takes a quick look at Bayesian joint models (BJM) for longitudinal and survival data. A general formulation for BJM is examined in terms of the sampling distribution of the longitudinal and survival processes, the conditional distribution of the random effects and the prior distribution. Next a basic BJM defined in terms of a mixed linear model and a Cox survival regression models is discussed and some extensions and other Bayesian topics are briefly outlined.
COVID-19 y tabaquismo: revisión sistemática y metaanálisis de la evidencia
2021
RESUMEN Objetivo: el objetivo del estudio ha sido responder a las siguientes preguntas: ¿Se asocia el consumo de tabaco en pacientes con Covid-19 con una progresión negativa y desenlace adverso de la enfermedad? y, ¿se asocia el consumo de tabaco, actual y pasado, a una mayor posibilidad de desarrollar COVID-19? Material y Métodos: Se realizó una revisión sistemática (RS) y metaanálisis (MA) de trabajos publicados previamente. La estrategia de búsqueda incluyó todos los descriptores conocidos sobre Covid-19 y tabaco y se realizó en diferentes bases de datos. Se utilizaron modelos estadísticos adecuados para abordar el tamaño del efecto en un metaanálisis: modelo de efectos aleatorios y de e…
Heart rate variability and self-control—A meta-analysis
2015
Heart rate variability (HRV) has been suggested as a biological correlate of self-control. Whereas many studies found a relationship between HRV at rest and self-control, effect sizes vary substantially across studies in magnitude and direction. This meta-analysis evaluated the association between HRV at rest and self-control in laboratory tasks, with a particular focus on the identification of moderating factors (task characteristics, methodological aspects of HRV assessment, demographics). Overall, 24 articles with 26 studies and 132 effects (n=2317, mean age=22.44, range 18.4-57.8) were integrated (random effects model with robust variance estimation). We found a positive average effect …
A Bayesian Multilevel Random-Effects Model for Estimating Noise in Image Sensors
2020
Sensor noise sources cause differences in the signal recorded across pixels in a single image and across multiple images. This paper presents a Bayesian approach to decomposing and characterizing the sensor noise sources involved in imaging with digital cameras. A Bayesian probabilistic model based on the (theoretical) model for noise sources in image sensing is fitted to a set of a time-series of images with different reflectance and wavelengths under controlled lighting conditions. The image sensing model is a complex model, with several interacting components dependent on reflectance and wavelength. The properties of the Bayesian approach of defining conditional dependencies among parame…
On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
2019
Entities such as individuals, teams, or organizations can vary systematically from one another. Researchers typically model such data using multilevel models, assuming that the random effects are uncorrelated with the regressors. Violating this testable assumption, which is often ignored, creates an endogeneity problem thus preventing causal interpretations. Focusing on two-level models, we explain how researchers can avoid this problem by including cluster means of the Level 1 explanatory variables as controls; we explain this point conceptually and with a large-scale simulation. We further show why the common practice of centering the predictor variables is mostly unnecessary. Moreover, …
La sopravvivenza immediata delle start-up italiane del settore manifatturiero sanitario: un'analisi multilevel
2017
The immediate survival of the Italian start-up businesses in healthcare industry: a multilevel analysis Objectives: The purpose of this contribution is to provide novel evidence about the main determinants of the short-run survival of pharmaceutical and medical device manufacturing start-up firms in Italy. In order to assess both the firm-specific determinants and the observed and unobserved regional and contextual characteristics, we model the three-year firm survival probability by means of a multilevel logistic framework. Methods and Results: The empirical analysis focuses on an internationally comparable database of the population of firms built up and managed by the Italian National In…
Exploring Neighborhood Influences on Small-Area Variations in Intimate Partner Violence Risk: A Bayesian Random-Effects Modeling Approach
2014
This paper uses spatial data of cases of intimate partner violence against women (IPVAW) to examine neighborhood-level influences on small-area variations in IPVAW risk in a police district of the city of Valencia (Spain). To analyze area variations in IPVAW risk and its association with neighborhood-level explanatory variables we use a Bayesian spatial random-effects modeling approach, as well as disease mapping methods to represent risk probabilities in each area. Analyses show that IPVAW cases are more likely in areas of high immigrant concentration, high public disorder and crime, and high physical disorder. Results also show a spatial component indicating remaining variability attribut…