Search results for "Random effects"
showing 10 items of 55 documents
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…
Bayesian hierarchical nonlinear modelling of intra-abdominal volume during pneumoperitoneum for laparoscopic surgery
2021
Laparoscopy is an operation carried out in the abdomen or pelvis through small incisions with external visual control by a camera. This technique needs the abdomen to be insufflated with carbon dioxide to obtain a working space for surgical instruments' manipulation. Identifying the critical point at which insufflation should be limited is crucial to maximizing surgical working space and minimizing injurious effects. Bayesian nonlinear growth mixed-effects models are applied to data coming from a repeated measures design. This study allows to assess the relationship between the insufflation pressure and the intra--abdominal volume.
Aspirin use and breast cancer risk: a meta-analysis and meta-regression of observational studies from 2001 to 2005
2007
Purpose To examine the recent epidemiological studies on aspirin use and breast cancer risk published from 2001 to 2005 within a meta-analysis, to investigate reasons for heterogeneity between the individual studies and to analyse a dose-response-relationship considering frequency and duration of use. Methods We systematically searched for cohort-studies and case-control-studies from 2001–2005, which evaluated the association between aspirin and breast cancer risk. We calculated a pooled estimate for the relative risk (RR) and investigated reasons for heterogeneity between the individual studies and analysed a dose-response-relationship using random effects mixed models. Results We identifi…
Meta-analysis of the relationship between teachers’ self-efficacy and attitudes toward inclusive education
2022
Abstract This meta-study aims to examine the size of the relationship between teachers' self-efficacy and attitudes toward inclusive education of K-12 students with special educational needs and to identify potential moderators (publication, sample, and research procedure characteristics). We synthesized the research conducted from 1994 to 2018, and 41 studies were included. Bare-bones meta-analysis with random effect model revealed a sample size weighted correlation coefficient between teachers’ self-efficacy and attitudes as r ¯ = 0.35 (CI = 0.31-0.39). The between-study variations were not associated with hypothesized publication and sample characteristics. However, the self-efficacy me…
Bayesian analysis and design for comparison of effect-sizes
2002
Comparison of effect-sizes, or more generally, of non-centrality parameters of non-central t distributions, is a common problem, especially in meta-analysis. The usual simplifying assumptions of either identical or non-related effect-sizes are often too restrictive to be appropriate. In this paper, the effect-sizes are modeled as random effects with t distributions. Bayesian hierarchical models are used both to design and analyze experiments. The main goal is to compare effect-sizes. Sample sizes are chosen so as to make accurate inferences about the difference of effect-sizes and also to convincingly solve the testing of equality of effect-sizes if such is the goal.
A model-based approach to Spotify data analysis: a Beta GLMM
2020
Digital music distribution is increasingly powered by automated mechanisms that continuously capture, sort and analyze large amounts of Web-based data. This paper deals with the management of songs audio features from a statistical point of view. In particular, it explores the data catching mechanisms enabled by Spotify Web API and suggests statistical tools for the analysis of these data. Special attention is devoted to songs popularity and a Beta model, including random effects, is proposed in order to give the first answer to questions like: which are the determinants of popularity? The identification of a model able to describe this relationship, the determination within the set of char…
Bayesian joint ordinal and survival modeling for breast cancer risk assessment
2016
We propose a joint model to analyze the structure and intensity of the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model. Time-to-event is modeled through a left-truncated proportionalhazards model, which incorporates information of the longitudinal marker as well as baseline covariates. Both longitudinal and survival processes are connected by means of a common vector of random effects. General inferences are discussed under the Bayesian approach and include the posterior distribution of the probabilities associated to each longitudinal category and the …
Subject-specific odds ratios in binomial GLMMs with continuous response
2007
In a regression context, the dichotomization of a continuous outcome variable is often motivated by the need to express results in terms of the odds ratio, as a measure of association between the response and one or more risk factors. Starting from the recent work of Moser and Coombs (Odds ratios for a continuous outcome variable without dichotomizing, Statistics in Medicine, 2004, 23, 1843-1860), in this article we explore in a mixed model framework the possibility of obtaining odds ratio estimates from a regression linear model without the need of dichotomizing the response variable. It is shown that the odds ratio estimators derived from a linear mixed model outperform those from a binom…
Segmented mixed models with random changepoints: a maximum likelihood approach with application to treatment for depression study
2014
We present a simple and effective iterative procedure to estimate segmented mixed models in a likelihood based framework. Random effects and covariates are allowed for each model parameter, including the changepoint. The method is practical and avoids the computational burdens related to estimation of nonlinear mixed effects models. A conventional linear mixed model with proper covariates that account for the changepoints is the key to our estimating algorithm. We illustrate the method via simulations and using data from a randomized clinical trial focused on change in depressive symptoms over time which characteristically show two separate phases of change.
Varying-time random effects models for longitudinal data: unmixing and temporal interpolation of remote-sensing data
2008
Remote sensing is a helpful tool for crop monitoring or vegetation-growth estimation at a country or regional scale. However, satellite images generally have to cope with a compromise between the time frequency of observations and their resolution (i.e. pixel size). When concerned with high temporal resolution, we have to work with information on the basis of kilometric pixels, named mixed pixels, that represent aggregated responses of multiple land cover. Disaggreggation or unmixing is then necessary to downscale from the square kilometer to the local dynamic of each theme (crop, wood, meadows, etc.). Assuming the land use is known, that is to say the proportion of each theme within each m…