A spatial mixed-effects regression model for electoral data

2020 ◽  
Author(s):  
Agnese Maria Di Brisco ◽  
Sonia Migliorati
Keyword(s):  
Regression Model ◽  
Mixed Effects ◽  
Electoral Data

Relationship between childhood obesity and socioeconomic status among primary school children in Costa Rica

2021 ◽  
pp. 1-24
Author(s):  
Tatiana Gamboa-Gamboa ◽  
Romain Fantin ◽  
Jeancarlo Cordoba ◽  
Ivannia Caravaca ◽  
Ingrid Gómez-Duarte
Keyword(s):  
Socioeconomic Status ◽  
Logistic Regression ◽  
Childhood Obesity ◽  
Costa Rica ◽  
Regression Model ◽  
Primary Schools ◽  
Logistic Regression Model ◽  
Mixed Effects ◽  
Overweight And Obesity ◽  
Public And Private

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.

P2778Geographic variability in the decline of the incidence of fatal and non-fatal stroke: a statewide study

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
J B Kostis ◽  
J Cabrera ◽  
S Zinonos ◽  
W J Kostis
Keyword(s):  
Risk Factors ◽  
Regression Model ◽  
Violent Crime ◽  
Low Income ◽  
Single Parent ◽  
Mixed Effects ◽  
Robert Wood Johnson Foundation ◽  
Stroke Incidence ◽  
Fatal Stroke ◽  
Physically Inactive

Abstract Background/Introduction There is scant information on the geographic variability in the rate of stroke incidence as it relates to the demographics, comorbidities, risk factors, and insurance type. Purpose/Methods County-level data on four modifiable groups of health factors including healthy behaviors, clinical care, physical environment, and socioeconomic conditions were obtained from the Robert Wood Johnson Foundation. The percentage of persons 65 years or older, smokers, physically inactive, obese, diabetics, heavy drinkers, college graduates, low income, unemployed, uninsured heads of single parent households, and residence in areas of violent crime was used in predicting fatal or non-fatal stroke. The counties were lumped into 5 categories based on similarities of the above characteristics. The incidence of fatal and non-fatal stroke was compared among the 5 county clusters using a mixed-effects regression model. Results The incidence of fatal and non-fatal stroke was significantly lower (p<0.0001) in cluster 3, where residents had higher income, were better educated, and were less likely to be unemployed, to live in single parent households, to have diabetes, to be obese, to smoke, to be physically inactive, or to live in communities with violent crime. The percentage of persons older than 65, violent crime rate, and obesity were identified as significant predictors of stroke using a mixed-effects regression model. Conclusions This study indicates that the incidence of stroke is higher in areas with older population, higher rate of obesity, and in regions with more violent crime. In order to improve health outcomes, preventive measures for stroke should address environmental factors in addition to the known cardiovascular risk factors. Acknowledgement/Funding Robert Wood Johnson Foundation

A mixed-effects regression model for three-level ordinal response data

2005 ◽  
Vol 24 (21) ◽  
pp. 3331-3345 ◽  
Author(s):  
Rema Raman ◽  
Donald Hedeker
Keyword(s):  
Regression Model ◽  
Mixed Effects ◽  
Response Data ◽  
Ordinal Response

scholarly journals Quantifying the Robustness of the English Sibilant Fricative Contrast in Children

2015 ◽  
Vol 58 (3) ◽  
pp. 622-637 ◽  
Author(s):  
Jeffrey J. Holliday ◽  
Patrick F. Reidy ◽  
Mary E. Beckman ◽  
Jan Edwards
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Mixed Effects ◽  
Vocabulary Size ◽  
Phonological Contrast ◽  
Different Types ◽  
Centroid Frequency ◽  
The Relationship ◽  
Children's Speech

Purpose Four measures of children's developing robustness of phonological contrast were compared to see how they correlated with age, vocabulary size, and adult listeners' correctness ratings. Method Word-initial sibilant fricative productions from eighty-one 2- to 5-year-old children and 20 adults were phonetically transcribed and acoustically analyzed. Four measures of robustness of contrast were calculated for each speaker on the basis of the centroid frequency measured from each fricative token. Productions that were transcribed as correct from different children were then used as stimuli in a perception experiment in which adult listeners rated the goodness of each production. Results Results showed that the degree of category overlap, quantified as the percentage of a child's productions whose category could be correctly predicted from the output of a mixed-effects logistic regression model, was the measure that correlated best with listeners' goodness judgments. Conclusions Even when children's productions have been transcribed as correct, adult listeners are sensitive to within-category variation quantified by the child's degree of category overlap. Further research is needed to explore the relationship between the age of a child and adults' sensitivity to different types of within-category variation in children's speech.

scholarly journals TWO-SIGMA: a novel TWO-component SInGle cell Model-based Association method for single-cell RNA-seq data

2019 ◽  
Author(s):  
Eric Van Buren ◽  
Ming Hu ◽  
Chen Weng ◽  
Fulai Jin ◽  
Yan Li ◽  
...  
Keyword(s):  
Regression Model ◽  
Single Cell ◽  
Cell Model ◽  
Random Effect ◽  
Mixed Effects ◽  
Rna Seq ◽  
Single Cell Model ◽  
Two Component ◽  
Association Method ◽  
Component Models

AbstractIn this paper, we develop TWO-SIGMA, a TWO-component SInGle cell Model-based Association method for differential expression (DE) analyses in single-cell RNA-seq (scRNA-seq) data. The first component models the probability of “drop-out” with a mixed-effects logistic regression model and the second component models the (conditional) mean expression with a mixed-effects negative binomial regression model. TWO-SIGMA is extremely flexible in that it: (i) does not require a log-transformation of the outcome, (ii) allows for overdispersed and zero-inflated counts, (iii) accommodates a correlation structure between cells from the same biological sample via random effect terms, (iv) can analyze unbalanced designs (in which the number of cells does not need to be identical for all samples), (v) can control for additional sample-level and cell-level covariates including batch effects, (vi) provides interpretable effect size estimates, and (vii) enables general tests of DE beyond two-group comparisons. To our knowledge, TWO-SIGMA is the only method for analyzing scRNA-seq data that can simultaneously accomplish each of these features. Simulations studies show that TWO-SIGMA outperforms alternative regression-based approaches in both type-I error control and power enhancement when the data contains even moderate within-sample correlation. A real data analysis using pancreas islet single-cells exhibits the flexibility of TWO-SIGMA and demonstrates that incorrectly failing to include random effect terms can have dramatic impacts on scientific conclusions. TWO-SIGMA is implemented in the R package twosigma available at https://github.com/edvanburen/twosigma.

scholarly journals Impact of Transcatheter Aortic Valve Replacement on Hospitalization Rates: Insights From Nationwide Readmission Database

2021 ◽  
Author(s):  
Ahmed Elkaryoni ◽  
Adnan K. Chhatriwalla ◽  
Kevin F. Kennedy ◽  
John T. Saxon ◽  
John J. Lopez ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Aortic Valve ◽  
Aortic Valve Replacement ◽  
Regression Model ◽  
Transcatheter Aortic Valve Replacement ◽  
Logistic Regression Model ◽  
Mixed Effects ◽  
Transcatheter Aortic Valve ◽  
Hospitalization Rates ◽  
Before And After

Background Hospitalization rates after transcatheter aortic valve replacement (TAVR) remain high, given the age and comorbidities of patients undergoing TAVR. To better understand the impact of TAVR on hospitalization, we sought to compare hospitalization rates before and after TAVR and to examine if underlying patient comorbidities are associated with a differential effect of TAVR on hospitalizations. Methods and Results We used the Nationwide Readmissions Database to identify patients who underwent TAVR. As Nationwide Readmissions Database data do not cross over calendar years, we limited our index admission to hospitalizations during April to September of each calendar year to allow 90 days of observation before and after TAVRs. We calculated the daily risk of all‐cause hospitalization and used a mixed‐effects logistic regression model to explore interactions between patient characteristics, TAVR, and hospitalization risk. Among 39 249 patients who underwent TAVR in 2014 to 2017 (median age, 82 years [interquartile range, 76–87 years]; 45.7% women), 32.0% had at least one hospitalization in the 90 days before TAVR compared with 23.2% in the 90 days post‐TAVR (relative reduction, 27.5%; P <0.001). In the mixed‐effects logistic regression model, TAVR was associated with decreased all‐cause hospitalization rate after TAVR in all comorbidity subgroups. However, younger patients and those with heart failure and reduced ejection fraction appeared to have more robust reduction in hospitalizations. Conclusions Although patients who are treated with TAVR have high rates of rehospitalization, TAVR is associated with an overall reduction in all‐cause hospitalizations regardless of underlying patient comorbidities.

scholarly journals On a Skew t–discrete Gamma Alternative to the Normal-Poisson Model for Clustered Count Outcomes

2021 ◽  
Author(s):  
Chénangnon Frédéric Tovissodé ◽  
Romain Lucas Glèlè Kakaï
Keyword(s):  
Regression Model ◽  
Random Effects ◽  
Conditional Distribution ◽  
Negative Binomial ◽  
Poisson Model ◽  
Mixed Effects ◽  
Sibling Negotiation ◽  
Count Distribution ◽  
Heavy Tailed ◽  
Distribution Assumption

The normal and Poisson distribution assumptions in the normal-Poisson mixed effects regression model are often too restrictive for many real count data. Several works have independently relaxed the Poisson conditional distribution assumption for counts or the normal distribution assumption for random effects. This work couples some recent advances in these two regards to develop a skew t&ndash;discrete gamma regression model in which the count outcomes have full dispersion flexibility and random effets can be skewed and heavy tailed. Inference in the model is achieved by maximum likelihood using pseudo-adaptive Gaussian quadature. The use of the proposal is demonstrated on a popular owl sibling negotiation data. It appears that, for this example, the proposed approach outperforms models based on normal random effects and the Poisson or negative binomial count distribution.

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
Keyword(s):  
Regression Model ◽  
Meta Analysis ◽  
Mixed Effects ◽  
Statistical Life
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