ArticleBiostatistics (Oxford, England)2023
Multivariate Bayesian spatio-temporal P-spline models to analyze crimes against women.
Article in Biostatistics (Oxford, England), 2023. 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.
- A multivariate spatio-temporal model for the incidence of imported COVID-19 cases and COVID-19 deaths in Cuba.Spatial and spatio-temporal epidemiology · 2023Article
- Bayesian disease mapping: Past, present, and future.Spatial statistics · 2022Article
- A Spatially Correlated Model with Generalized Autoregressive Conditionally Heteroskedastic Structure for Counts of Crimes.Entropy (Basel, Switzerland) · 2022Article
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3 authors.
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Abstract
Univariate spatio-temporal models for areal count data have received great attention in recent years for estimating risks. However, models for studying multivariate responses are less commonly used mainly due to the computational burden. In this article, multivariate spatio-temporal P-spline models are proposed to study different forms of violence against women. Modeling distinct crimes jointly improves the precision of estimates over univariate models and allows to compute correlations among them. The correlation between the spatial and the temporal patterns may suggest connections among the different crimes that will certainly benefit a thorough comprehension of this problem that affects millions of women around the world. The models are fitted using integrated nested Laplace approximations and are used to analyze four distinct crimes against women at district level in the Indian state of Maharashtra during the period 2001-2013.
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