scholarly journals Bayesian modelling for spatially misaligned health areal data: A multiple membership approach

2021 ◽  
Author(s):  
Marco Gramatica ◽  
Peter Congdon ◽  
Silvia Liverani
Keyword(s):  
Bayesian Modelling ◽  
Areal Data ◽  
Multiple Membership

Between-Year and Within-Year School Mobility: Different Effects by Race/Ethnicity

2021 ◽  
pp. 001312452110045
Author(s):  
Jie Min
Keyword(s):  
Academic Achievement ◽  
Asian American ◽  
School Mobility ◽  
Student Groups ◽  
Asian American Students ◽  
Math Scores ◽  
American Students ◽  
Reading And Math ◽  
Multiple Membership ◽  
Racial Ethnic

The current study investigated the effects of school mobility on the academic achievement of different racial/ethnic groups in four cohorts of students from a very large urban school district. In this study, I compared within-year and between-year mobility and, most importantly, account for all the schools students attended over the study period. Using a multiple membership model (MMM), the findings confirmed that, for all student groups, academic achievement was affected more by within-year school mobility than between-year school mobility. Black students had the highest mobility rates, both for between- and within-year mobility. Although Asian-American students achieved higher reading and math scores on average, they were more negatively impacted by within-year school mobility compared to other groups. The current study was able to pinpoint the students most at risk for negative outcomes following within-year mobility. The findings are discussed in the context of policy recommendations that can be adopted by school districts.

scholarly journals Teacher Effects on Chilean Children’s Achievement Growth: A Cross-Classified Multiple Membership Accelerated Growth Curve Model

2018 ◽  
Vol 40 (3) ◽  
pp. 473-501 ◽  
Author(s):  
Lorena Ortega ◽  
Lars-Erik Malmberg ◽  
Pam Sammons
Keyword(s):  
Student Achievement ◽  
Growth Curve ◽  
Growth Models ◽  
Teacher Effects ◽  
Combined Use ◽  
Achievement Growth ◽  
Children's Achievement ◽  
Accelerated Growth ◽  
Multiple Membership ◽  
Achievement Trajectories

We investigated teacher effects (magnitude, predictors, and cumulativeness) on primary students’ achievement trajectories in Chile, using multilevel cross-classified (accelerated) growth models (four overlapping cohorts, spanning Grades 3 to 8; n = 19,704 students, and 851 language and 812 mathematics teachers, in 156 schools). It was found that teacher effects on achievement growth are large, exceeding school effects. Also, the contribution of teachers to student achievement growth was found to accumulate over time. The study advances the field by exploring teacher effects in the context of an emerging economy, contributing further evidence on the properties of teacher effects on student achievement growth and demonstrating the combined use of accelerated longitudinal designs, growth curve approaches, and cross-classified and multiple membership models.

scholarly journals Spatial models for point and areal data using Markov random fields on a fine grid

2013 ◽  
Vol 7 (0) ◽  
pp. 946-972 ◽  
Author(s):  
Christopher J. Paciorek
Keyword(s):  
Random Fields ◽  
Markov Random Fields ◽  
Spatial Models ◽  
Fine Grid ◽  
Areal Data ◽  
Markov Random

scholarly journals An application of the generalized Poisson difference distribution to the Bayesian modelling of football scores

2016 ◽  
Vol 70 (3) ◽  
pp. 260-273 ◽  
Author(s):  
Golnaz Shahtahmassebi ◽  
Rana Moyeed
Keyword(s):  
Bayesian Modelling ◽  
Generalized Poisson

Catheter ablation outscores all other treatment modalities in reducing all-cause mortality and heart failure related morbidity in patients of persistent atrial fibrillation with systolic heart failure

EP Europace ◽  
2021 ◽  
Vol 23 (Supplement_3) ◽  
Author(s):  
D Khanra ◽  
A Mukherjee ◽  
S Deshpande ◽  
D Padmanabhan ◽  
S Mohan ◽  
...  
Keyword(s):  
Heart Failure ◽  
Catheter Ablation ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Systolic Heart Failure ◽  
Individual Treatment ◽  
Published Data ◽  
Bayesian Modelling ◽  
All Cause Mortality ◽  
Pair Wise Comparison

Abstract Funding Acknowledgements Type of funding sources: None. Background Catheter ablation in the setting of persistent AF (PeAF) with heart failure (HF) is challenging and often has poor outcome. However, guideline and studies indicate ablation strategy in this group to reduce mortality and HF-related hospitalization. Purpose We have conducted a network meta-analysis (NMA) of all-cause mortality and improvement of HF-related QOL in patients of PeAF with systolic heart failure comparing  rate controlling drugs (RCDs), anti-arrhythmic drugs (AAD), catheter ablation (CA) of PeAF and AV nodal ablation with univentricular or biventricular pacing (AVNA). Method Bayesian network meta-analysis of randomized controlled studies comparing mortality and QOL among individual treatment arms (e.g. RCDs, AADs, CA and AVNA) and pair-wise network meta-analysis comparing CA and other treatment arms (RCD, AAD and AVNA) were performed using MetInsight V3.  Markov chain Monte Carlo (MCMC) modeling was used to estimate the relative ranking probability of each treatment group. Results Published data of 14 studies including 3698 patients were included in the NMA with a median follow-up of two years (1A, 2A). The Bayesian modelling with MCMC analysis for pair-wise comparison clearly demonstrated that, AAD [OR (95% CrI): 2.10 (0.43-9.0)], AVNA [OR (95% CrI): 1.32 (0.14-11.7)] and RCDs [OR (95% CrI): 2.76 (0.5-14.1)] have higher all-cause mortality than CA but not within the radar of statistical significance (1B). The Bayesian modelling with MCMC analysis for pair-wise comparison clearly demonstrated that, AADs [MD (95% CrI): 8.02 (-8.32-27.8)], AVNA [MD (95% CrI): 17.0 (-1.9-33.1)] and RCDs [MD (95% CrI): 13.0 (0.1-24.5)] have lesser improvement in QOL than CA but not within the radar of statistical significance (2B). Based on the Bayesian model, CA results in lower all-cause mortality and highest improvement of QOL in the patients of AF with HF (3A, 3B). Conclusion This shapes way for future treatment guidelines in patients with PeAF with HF group and points towards CA to be undertaken before medical therapy fails. This also paves way for further research to confirm the longevity of the beneficial effects and to find the specific subsets of AF with HF patients that would be benefited most from CA. Abstract Figure

scholarly journals Bayesian Modelling, Monte Carlo Sampling and Capital Allocation of Insurance Risks

Risks ◽  
2017 ◽  
Vol 5 (4) ◽  
pp. 53 ◽  
Author(s):  
Gareth Peters ◽  
Rodrigo Targino ◽  
Mario Wüthrich
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Sampling ◽  
Capital Allocation ◽  
Bayesian Modelling

scholarly journals Robust seasonal adjustment by Bayesian modelling

1996 ◽  
Vol 15 (5) ◽  
pp. 355-367 ◽  
Author(s):  
Martin R. Young
Keyword(s):  
Seasonal Adjustment ◽  
Bayesian Modelling
Sign in / Sign up

Export Citation Format

Share Document