Now, we will extend the results of Theorem 2.1 to the multivariate context.
Although the novel algorithms are presented for univariate target densities, we show how they can be easily extended to the multivariate context by embedding them within a Gibbs-type sampler or the hit and run algorithm.
Due to the fact that several of these factors most likely are intercorrelated it is important to understand how they relate to WSP in a more comprehensive (multivariate) context when planning for instance prevention, health care and social security systems.
In a multivariate context, Fisher (1930) used his classical 'geometric model' to argue that alleles (i.e., mutations) with large effect that pleiotropically affect multiple traits are most likely to be deleterious.
To examine these associations in a multivariate context, after considering the sampling weight, a Binary Logistic Regression analysis was performed, in which self-reported suicide attempts were regressed on suicidal ideation and the NSSI, along with controlling for the participants' levels of depressive symptoms and demographic characteristics.
We used multiple regression analyses to assess the associations of QOL in the multivariate context, with scores on the general facet and each of the domains as dependent variables.
In the same multivariate context, this paper aims at an extension of the double-sampling strategies to monotone designs accounting for differences between the costs of subsets of covariates.
This metabolomics approach allowed us to identify a number of metabolites that in the multivariate context differed in abundance between MYA and CON.
In order to identify the variables that predicted HRQoL in the multivariate context, we employed multiple linear regression analyses with the EQ-5D Indexes after one and 2.5 years as dependent variables.
First, only a few studies reported information on most of the predictor variables simultaneously so multivariate meta-regression analyses could not be conducted to understand the importance of the factors identified in a multivariate context.
