<p>Possible models of HDL-C, LDL-C, TG can contain up to 15 covariables (age, sex, BMI SDS, dominant and recessive effect of six SNPs). We present most probable models, corresponding posterior probabilities and Bayes factors. Models are ranked according to their plausibility. A cumulative probability of 95% served as cut-off for model presentation.</p><p>Results of Bayesian model analysis.</p
Statistical inference of genome-wide association studies (GWAS) on a variety of epidemiological phen...
<p>(<b>A</b>) Posterior probability and (<b>B</b>) Bayes factors for the three models we compared, s...
Although complex diseases and traits are thought to have multifactorial genetic basis, the common me...
<p>We present the structure of the Bayesian model analysed. Black arrows represent possible impacts ...
<p>The estimates for the percentage of markers affecting the phenotype (1–π) and its heritability (<...
In general, model selection is an important prelude to subsequent statistical inference in risk asse...
In the analysis of any data using statistical modelling, it is imperative that the choice of model i...
Motivation: There often are many alternative models of a biochemical system. Distinguishing models a...
<p>The Bayes Factor (BF) of each model, mode and 90% highest posterior density (in parentheses) for ...
In the analysis of any data using statistical modelling, it is imperative that the choice of model i...
(A) Aspects of linear regression model assessed by model selection and model averaging (see Fig 1A)....
We investigate a Bayesian approach to modelling the statistical association between markers at multi...
<p>Our most probable model (bolded) included the composite variable of population age and population...
<p>(A–B) Given a group of single traits (APOA1, APOB, HDL, LDL and TG), we constructed two top-down ...
In this paper we review the concepts of Bayesian evidence and Bayes factors, also known as log odds ...
Statistical inference of genome-wide association studies (GWAS) on a variety of epidemiological phen...
<p>(<b>A</b>) Posterior probability and (<b>B</b>) Bayes factors for the three models we compared, s...
Although complex diseases and traits are thought to have multifactorial genetic basis, the common me...
<p>We present the structure of the Bayesian model analysed. Black arrows represent possible impacts ...
<p>The estimates for the percentage of markers affecting the phenotype (1–π) and its heritability (<...
In general, model selection is an important prelude to subsequent statistical inference in risk asse...
In the analysis of any data using statistical modelling, it is imperative that the choice of model i...
Motivation: There often are many alternative models of a biochemical system. Distinguishing models a...
<p>The Bayes Factor (BF) of each model, mode and 90% highest posterior density (in parentheses) for ...
In the analysis of any data using statistical modelling, it is imperative that the choice of model i...
(A) Aspects of linear regression model assessed by model selection and model averaging (see Fig 1A)....
We investigate a Bayesian approach to modelling the statistical association between markers at multi...
<p>Our most probable model (bolded) included the composite variable of population age and population...
<p>(A–B) Given a group of single traits (APOA1, APOB, HDL, LDL and TG), we constructed two top-down ...
In this paper we review the concepts of Bayesian evidence and Bayes factors, also known as log odds ...
Statistical inference of genome-wide association studies (GWAS) on a variety of epidemiological phen...
<p>(<b>A</b>) Posterior probability and (<b>B</b>) Bayes factors for the three models we compared, s...
Although complex diseases and traits are thought to have multifactorial genetic basis, the common me...