Department of Statistics, Computer Science, and Mathematics, Public University of Navarre, Campus de Arrosadia, 31006 Pamplona, Spain and Institute Institute for Advanced Materials and Mathematics (INAMAT2), Campus de Arrosadia, 31006 Pamplona, Spain.
Department of Statistics, Computer Science, and Mathematics, Public University of Navarre, Campus de Arrosadia, 31006 Pamplona, Spain and Institute Institute for Advanced Materials and Mathematics (INAMAT2), Campus de Arrosadia, 31006 Pamplona, Spain and IdiSNA, Health Research Institute of Navarre Recinto de Complejo Hospitalario de Navarra C/ Irunlarrea, 3 31008 Pamplona, Spain.
Biostatistics. 2023 Jul 14;24(3):562-584. doi: 10.1093/biostatistics/kxab042.
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.
近年来，用于估计风险的单变量时空模型在医学研究领域受到了广泛关注。然而，由于计算负担较大，用于研究多变量响应的模型则较少使用。本文提出了多元时空 P-样条模型，用于研究不同形式的针对妇女的暴力行为。联合建模不同犯罪行为可以提高单变量模型的估计精度，并允许计算它们之间的相关性。空间和时间模式之间的相关性可能表明不同犯罪行为之间存在联系，这对于深入理解这一影响全球数百万妇女的问题肯定会有帮助。该模型使用集成嵌套拉普拉斯近似进行拟合，并用于分析印度马哈拉施特拉邦 2001 年至 2013 年期间区县级的四种不同的针对妇女的暴力犯罪。
