In statistical practice multicollinearity of predictor variables is rather the rule than the exception and appropriate models are needed to avoid instability of predictions. Feature extraction methods reflect the idea that latent variables not measurable directly are underlying the original...

In statistical practice multicollinearity of predictor variables is rather the rule than the exception and appropriate models are needed to avoid instability of predictions. Feature extraction methods reflect the idea that latent variables not measurable directly are underlying the original...

This paper analyzes house price data belonging to three hierarchical levels of spatial units. House selling prices with associated individual attributes (the elementary level-1) are grouped within municipalities (level-2), which form districts (level-3), which are themselves nested in counties...

Models with structured additive predictor provide a very broad and rich framework for complex regression modeling. They can deal simultaneously with nonlinear covariate effects and time trends, unit- or cluster specific heterogeneity, spatial heterogeneity and complex interactions between...

Applications of multiple imputation have long outgrown the traditional context of dealing with item nonresponse in cross-sectional datasets. Nowadays multiple imputation is also applied to impute missing values in hierarchical datasets, address confidentiality concerns, combine data from...

Abstract This article presents original mixed method research to describe the use of rare illicit psychoactive substances, with special emphasis on crack cocaine in France. We first introduce a unique monitoring system committed to the observation of hard-to-reach populations. Qualitative...