The value of a statistical life: A meta-analysis with a mixed effects regression model

2009 ◽  
Vol 28 (2) ◽  
pp. 444-464 ◽  
Author(s):  
François Bellavance ◽  
Georges Dionne ◽  
Martin Lebeau
2021 ◽  
pp. 1-24
Author(s):  
Tatiana Gamboa-Gamboa ◽  
Romain Fantin ◽  
Jeancarlo Cordoba ◽  
Ivannia Caravaca ◽  
Ingrid Gómez-Duarte

Abstract Objective: This article analyzes the relationship between socioeconomic status and the prevalence of overweight and obesity in the primary school population in Costa Rica. Design: A National School Weight/Height Census was disseminated across Costa Rica in 2016. The percentage of children who were overweight or obese was calculated by sex, age, and socioeconomic indicators (type of institution: private, public, mix; type of geographic location: rural, urban; and the level of development of the district of residence: quartiles). A mixed effects multinomial logistic regression model and mixed effects logistic regression model were used to analyze the association between the prevalence of being overweight or obese and district socioeconomic status. Setting: The survey was carried out in public and private primary schools across Costa Rica in 2016. Participants: 347,366 students from 6 to 12 years old, enrolled in public and private primary schools. Results: The prevalence of overweight and obesity among children was 34.0%. Children in private schools were more likely to be overweight or obese than students in public schools (OR=1.10 [1.07, 1.13]). Additionally, children were less likely to be overweight or obese if attending a school in a district of the lowest socioeconomic quartile compared to the highest socioeconomic quartile (OR=0.79 [0.75, 0.83]), and in a rural area compared to the urban area (OR=0.92 [0.87, 0.97]). Conclusions: Childhood obesity in Costa Rica continues to be a public health problem. Prevalence of overweight and obesity in children was associated with indicators of higher socioeconomic status.


2018 ◽  
Vol 43 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Noel A. Card

Longitudinal data are common and essential to understanding human development. This paper introduces an approach to synthesizing longitudinal research findings called lag as moderator meta-analysis (LAMMA). This approach capitalizes on between-study variability in time lags studied in order to identify the impact of lag on estimates of stability and longitudinal prediction. The paper introduces linear, nonlinear, and mixed-effects approaches to LAMMA, and presents an illustrative example (with syntax and annotated output available as online Supplementary Materials). Several extensions of the basic LAMMA are considered, including artifact correction, multiple effect sizes from studies, and incorporating age as a predictor. It is hoped that LAMMA provides a framework for synthesizing longitudinal data to promote greater accumulation of knowledge in developmental science.


2019 ◽  
Vol 88 (2) ◽  
pp. 288-310 ◽  
Author(s):  
María Rubio-Aparicio ◽  
José Antonio López-López ◽  
Wolfgang Viechtbauer ◽  
Fulgencio Marín-Martínez ◽  
Juan Botella ◽  
...  
Keyword(s):  

2013 ◽  
Vol 86 ◽  
pp. 134-140 ◽  
Author(s):  
Jeremy Burdon ◽  
Patrick Connolly ◽  
Nihal de Silva ◽  
Nagin Lallu ◽  
Jonathan Dixon ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document