ArticleStatistics & probability letters2016
Nonparametric Bayes modeling with sample survey weights.
Article in Statistics & probability letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Article
- Identifying dietary consumption patterns from survey data: a Bayesian nonparametric latent class model.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2024Article
- Bayesian estimation methods for survey data with potential applications to health disparities research.Wiley interdisciplinary reviewsArticle
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Authors and funding
4 authors.
Funding
Abstract
In population studies, it is standard to sample data via designs in which the population is divided into strata, with the different strata assigned different probabilities of inclusion. Although there have been some proposals for including sample survey weights into Bayesian analyses, existing methods require complex models or ignore the stratified design underlying the survey weights. We propose a simple approach based on modeling the distribution of the selected sample as a mixture, with the mixture weights appropriately adjusted, while accounting for uncertainty in the adjustment. We focus for simplicity on Dirichlet process mixtures but the proposed approach can be applied more broadly. We sketch a simple Markov chain Monte Carlo algorithm for computation, and assess the approach via simulations and an application.
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Registered trials
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