Influence diagnostics for elliptical semiparametric mixed models

In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

Do pets reduce the likelihood of sudden unexplained death in epilepsy?

Purpose: To assess the relationship between the presence of pets in homes of epilepsy patients and the occurrence of sudden unexpected death in epilepsy (SUDEP). Methods: Parents or relatives of SUDEP patients collected over a ten-year period (2000-2009) in a large epilepsy unit were asked if the patient lived together with any domestic pet at the time of death or not. Patients who did not experience SUDEP served as controls. Results and conclusions: Eleven out of the 1092 included patients (1%) experienced SUDEP, all with refractory symptomatic epilepsy, but none of them had pets in their homes at the time of death. In contrast, the frequency of pet-ownership in the control group (n = 1081) was 61%. According to previous studies there are some indications that human health is directly related to companionship with animals in a way that domestic animals prevent illness and facilitate recovery of patients. Companion animals can buffer reactivity against acute stress, diminish stress perception and improve physical health. These factors may reduce cardiac arrhythmias and seizure frequency, factors related to SUDEP. Companion animals may have a positive effect on well-being, thus irnproving epilepsy outcome. (c) 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Likelihood-based inference for power distributions

This paper considers likelihood-based inference for the family of power distributions. Widely applicable results are presented which can be used to conduct inference for all three parameters of the general location-scale extension of the family. More specific results are given for the special case of the power normal model. The analysis of a large data set, formed from density measurements for a certain type of pollen, illustrates the application of the family and the results for likelihood-based inference. Throughout, comparisons are made with analogous results for the direct parametrisation of the skew-normal distribution.