Non-proportional odds multivariate logistic regression of ordinal family data.
Biom J
; 57(2): 286-303, 2015 Mar.
Article
em En
| MEDLINE
| ID: mdl-25287055
ABSTRACT
Methods to examine whether genetic and/or environmental sources can account for the residual variation in ordinal family data usually assume proportional odds. However, standard software to fit the non-proportional odds model to ordinal family data is limited because the correlation structure of family data is more complex than for other types of clustered data. To perform these analyses we propose the non-proportional odds multivariate logistic regression model and take a simulation-based approach to model fitting using Markov chain Monte Carlo methods, such as partially collapsed Gibbs sampling and the Metropolis algorithm. We applied the proposed methodology to male pattern baldness data from the Victorian Family Heart Study.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Linhagem
/
Biometria
Tipo de estudo:
Health_economic_evaluation
/
Prognostic_studies
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Risk_factors_studies
Limite:
Female
/
Humans
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Male
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article