Assessing variance components in multilevel linear models using approximate Bayes factors: a case-study of ethnic disparities in birth weight

AbstractInsulin resistance and obesity are underlying causes of type 2 diabetes and therefore much interest is focused on the potential genes involved. A series of anthropometric and metabolic characteristic were measured in 240 MZ and 112 DZ twin pairs recruited from the East Flanders Prospective Twin Survey. Microsatellite markers located close to ABCC8, ADIPOQ, GCK, IGF1, IGFBP1, INSR, LEP, LEPR, PPARγ and the RETN gene were genotyped. Univariate single point variance components linkage analyses were performed using two methods: (1) the standard method, only comprising the phenotypic and genotypic data of the DZ twin pairs and (2) the extended method, also incorporating the phenotypic data of the MZ twin pairs. Suggestive linkages (LOD > 1) were observed between the ABCC8 marker and waist-to-hip ratio and HDL-cholesterol levels. Both markers flanking ADIPOQ showed suggestive linkage with triglycerides levels, the upstream marker also with body mass and HDL-cholesterol levels. The IGFBP1 marker showed suggestive linkage with fat mass, fasting insulin and leptin levels and the LEP marker showed suggestive linkage with birth weight. This study suggests that DNA variants in ABCC8, ADIPOQ, IGFBP1 and LEP gene region may predispose to type 2 diabetes. In addition, the two methods used to perform linkage analyses yielded similar results. This was however not the case for birth weight where chorionicity seems to be an important confounder.

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Evaluation of Coronavirus Anxiety in Pregnant Women on Apgar Score and Birth Weight After One Year of Coronavirus Outbreak (Case Study: Zabol, Iran)

Journal of Obstetrics Gynecology and Cancer Research ◽

10.30699/jogcr.7.2.89 ◽

2022 ◽

Vol 7 (2) ◽

pp. 89-98

Author(s):

Fatemeh Mirzaie ◽

Khadije Rezaie Keikhaie ◽

Mahin Badakhsh ◽

Bahareh Khajehpourbahareh ◽

Samira Ghofrani ◽

...

Keyword(s):

Birth Weight ◽

Pregnant Women ◽

Apgar Score ◽

One Year ◽

Outbreak Case

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Clinical Factors Influencing the Efficacy of Systemic Moxifloxacin in the Therapy of Patients With Generalized Aggressive Periodontitis: A Multilevel Analysis From a Clinical Trial

Global Journal of Health Science ◽

10.5539/gjhs.v8n3p80 ◽

2015 ◽

Vol 8 (3) ◽

pp. 80 ◽

Cited By ~ 4

Author(s):

Carlos M. Ardila ◽

Isabel C. Guzmán

Keyword(s):

Clinical Trial ◽

Multilevel Analysis ◽

Linear Models ◽

Clinical Results ◽

Aggressive Periodontitis ◽

Continuous Variables ◽

Clinical Factors ◽

Probing Depth ◽

Clinical Benefits ◽

Multilevel Linear Models

BACKGROUND: It has been reported that clinical results of mechanical periodontal treatment could differ between subjects and among different sites of the tooth in the patient. The objective of this multilevel analysis is to investigate clinical factors at subject and sites of the tooth that influence variations in clinical attachment (CAL) increase and probing depth (PD) diminution of adjunctive moxifloxacin (MOX) at six months post-treatment in generalized aggressive periodontitis. METHODS: This clinical trial included 40 patients randomly distributed to two therapy protocols: scaling and root planing alone or combined with MOX. Multilevel linear models for continuous variables were formulated to evaluate the clinical impact of the hierarchical configuration of periodontal data. RESULTS: Six months following therapy, the divergences between both protocols were statistically significant in PD diminution and CAL increase, favouring the MOX therapy (p<0.001). Besides, the multilevel analysis revealed that adjunctive MOX at the subject level, non-molar and the interaction non-molar x MOX at the tooth level, interproximal sites and the interaction interproximal sites x MOX at the site level, were statistically significant factors in determining CAL increase and PD diminution. CONCLUSIONS: The main cause of variability in CAL gain and PD reduction following adjunctive MOX was attributable to the tooth level. Adjunctive MOX and their interactions with non-molar and interproximal sites showed higher clinical benefits at the tooth and site levels which could be essential for PD reduction and CAL gain in generalized aggressive periodontitis subjects.

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Model predictive control of a CSTR: A hybrid modeling approach

Chemical Papers ◽

10.2478/s11696-010-0008-8 ◽

2010 ◽

Vol 64 (3) ◽

Cited By ~ 8

Author(s):

Michal Kvasnica ◽

Martin Herceg ◽

Ľuboš Čirka ◽

Miroslav Fikar

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Linear Models ◽

Nonlinear Behavior ◽

Continuous Stirred Tank Reactor ◽

Modeling Framework ◽

Future Evolution ◽

Continuous Stirred Tank ◽

Traditional Approaches

AbstractThis paper presents a case study of model predictive control (MPC) applied to a continuous stirred tank reactor (CSTR). It is proposed to approximate nonlinear behavior of a plant by several local linear models, enabling a piecewise affine (PWA) description of the model used to predict and optimize future evolution of the reactor behavior. Main advantage of the PWA model over traditional approaches based on single linearization is a significant increase of model accuracy which leads to a better control quality. It is also illustrated that, by adopting the PWA modeling framework, MPC strategy can be implemented using significantly less computational power compared to nonlinear MPC setups.

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Estimating Bayes factors from minimal summary statistics in repeated measures analysis of variance designs

Advances in Methodology and Statistics ◽

10.51936/abic6583 ◽

2020 ◽

Vol 17 (1) ◽

Author(s):

Thomas Faulkenberry

Keyword(s):

Analysis Of Variance ◽

Repeated Measures ◽

Bayes Factor ◽

Linear Models ◽

Repeated Measurements ◽

Bayes Factors ◽

Complex Method ◽

Summary Statistics ◽

Minimal Set ◽

Repeated Measures Analysis

In this paper, I develop a formula for estimating Bayes factors directly from minimal summary statistics produced in repeated measures analysis of variance designs. The formula, which requires knowing only the F-statistic, the number of subjects, and the number of repeated measurements per subject, is based on the BIC approximation of the Bayes factor, a common default method for Bayesian computation with linear models. In addition to providing computational examples, I report a simulation study in which I demonstrate that the formula compares favorably to a recently developed, more complex method that accounts for correlation between repeated measurements. The minimal BIC method provides a simple way for researchers to estimate Bayes factors from a minimal set of summary statistics, giving users a powerful index for estimating the evidential value of not only their own data, but also the data reported in published studies.

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Evaluación fenotípica y genética para características de crecimiento en la raza criolla colombiana Costeño con Cuernos

Ciencia y Tecnología Agropecuaria ◽

10.21930/rcta.vol7_num2_art:65 ◽

2007 ◽

Vol 7 (2) ◽

pp. 12 ◽

Cited By ~ 3

Author(s):

Rodrigo Alfredo Martínez ◽

Juan Esteban Pérez ◽

Teófilo Herazo

Keyword(s):

Birth Weight ◽

Variance Components ◽

Fixed Effects ◽

Genetic Parameters ◽

Growth Traits ◽

Phenotypic Correlation ◽

Phenotypic Variance ◽

Direct Effects ◽

Weaning Weight ◽

Number Of Births

Se establecieron componentes de varianza, así como parámetros fenotípicos y genéticos, respecto de las variables ‘peso al nacimiento’, ‘peso al destete’ (ajustado a los 270 días) y ‘peso a los 480 días’ en un hato del ganado criollo colombiano Costeño con Cuernos. Se analizaron 2.281 registros de pesos al nacer, 1.722 de pesos al destete y 1.086 de pesos ajustados a los 480 días utilizando la metodología de máxima verosimilitud restringida (DFREML). También se ajustó un modelo animal que incluyó efectos genéticos directos, maternos y de ambiente permanente, asumiendo como efectos fijos el año de nacimiento, el sexo del ternero y el número de partos de la madre; finalmente, se estimaron los parámetros genéticos ‘heredabilidad’, ‘repetibilildad’ y se establecieron correlaciones genéticas y fenotípicas. Se reportan bajas estimaciones de heredabilidad de los efectos directos, que varían entre 0,17 ± 0,001 y 0,21 ± 0,074 para los pesos al nacer y al destete, respectivamente; así mismo, fue baja la heredabilidad de los efectos genéticos maternos con relación al peso al nacimiento, aunque estos estimados aumentaron respecto de los pesos al nacer y al destete. Las correlaciones entre efectos directos y maternos fueron negativas, pero el mayor valor se encontró para el peso al nacimiento (-0,89). La contribución del ambiente permanente como proporción de la varianza fenotípica total fue baja y disminuyó a medida que aumentó la edad del animal. Genetic and phenotypic evaluation to characterize growth traits of the native Colombian breed Costeño con CuernosFor a herd of native Colombian breed of cattle -Costeño con Cuernos (CCC)- estimates of variance components for phenotypic and genetic parameters were obtained for birth weight, weight at weaning (adjusted to 270 days) and weight at 480 days. Using the restricted maximum likelihood (REMI) methodology, 2281 birth weight records (PN), 1722 weaning weight records and 1086 weight records adjusted to 480 days were analyze by fitting a model which included direct and maternal genetics effects as well as permanent environmental effects, assuming that fixed effects were year of birth weight, calf gender and the mother number of births. The genetic parameters for heritability, repeatability, genetic and phenotypic correlation were estimated and genotypic and phenotypic correlation was established. Heritability estimates for direct effects are low and range from 0.17 ± 0.001 and 0.21 ± 0.074 for birth and weaning weight respectively; while estimates for maternal genetics effects were also low for PN, they were higher for weaning weight and weight at 480 days. There was a negative correlation between direct and maternal effects, and the higher value was for PN (-0.89). The contribution of the variable permanent environment measured as the contribution of the phenotypic variance was low and diminished as animal age increased.

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Using the Econometric Models for Identification of Risk Factors for Albanian Smes (Case Study: Smes of Gjirokastra Region)

WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS ◽

10.37394/23207.2021.18.17 ◽

2021 ◽

Vol 18 ◽

pp. 163-170

Author(s):

Lorenc Koçiu ◽

Kledian Kodra

Keyword(s):

Logistic Regression ◽

Statistical Models ◽

Logistic Regression Model ◽

Qualitative Data ◽

Linear Models ◽

Binary Logistic Regression ◽

Random Variable ◽

Econometric Models ◽

Binary Logistic Regression Model

Using the econometric models, this paper addresses the ability of Albanian Small and Medium-sizedEnterprises (SMEs) to identify the risks they face. To write this paper, we studied SMEs operating in theGjirokastra region. First, qualitative data gathered through a questionnaire was used. Next, the 5-level Likertscale was used to measure it. Finally, the data was processed through statistical software SPSS version 21,using the binary logistic regression model, which reveals the probability of occurrence of an event when allindependent variables are included. Logistic regression is an integral part of a category of statistical models,which are called General Linear Models. Logistic regression is used to analyze problems in which one or moreindependent variables interfere, which influences the dichotomous dependent variable. In such cases, the latteris seen as the random variable and is dependent on them. To evaluate whether Albanian SMEs can identifyrisks, we analyzed the factors that SMEs perceive as directly affecting the risks they face. At the end of thepaper, we conclude that Albanian SMEs can identify risk

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