Grieving the Loss of a Pet Needs the Health System Recognition

Globally there is increased presence of pets in the households. This non-human relationship, with its dimensions of physical and emotional bonds, can get severely jolted on the death of the companion animal. It sets a feeling, ‘our life is now left with a void and the house feels utterly empty’. Unlike the loss of a child, spouse or parent which become a shared tragedy; others may not understand the depth of sadness and a sense of void in a grieving pet owner. Emotional pain and physical distress due to the loss of a companion animal are likely to be pronounced. A big challenge for the medical community is to anticipate, identify and address physical and psychosocial symptom burdens in a timely manner.     

Estimating the Probability of Rare Events Occurring Using a Local Model Averaging

In statistical applications, logistic regression is a popular method for analyzing binary data accompanied by explanatory variables. But when one of the two outcomes is rare, the estimation of model parameters has been shown to be severely biased and hence estimating the probability of rare events occurring based on a logistic regression model would be inaccurate. In this article, we focus on estimating the probability of rare events occurring based on logistic regression models. Instead of selecting a best model, we propose a local model averaging procedure based on a data perturbation technique applied to different information criteria to obtain different probability estimates of rare events occurring. Then an approximately unbiased estimator of Kullback‐Leibler loss is used to choose the best one among them. We design complete simulations to show the effectiveness of our approach. For illustration, a necrotizing enterocolitis (NEC) data set is analyzed.     

A proportional-reduction-in-impurity measure of association for categorical variables

This paper presents a proportional-reduction-in-impurity (PRI) measure for categorical association, that employs application-dependent loss functions which make the measure widely applicable. The well-known proportional -reduction-in-error (PRE) measure is shown to be a special case of the new PRI measure. Moreover, the asymptotic variance of the maximum likelihood estimator (MLE) of the measure is derived to facilitate its use for statistical inference. An extension of the PRI measure to compositional association is made to show that it can have a variety of applications. Selected loss functions are treated to illustrate the derivation of the measure.     

Bayes and robust Bayes predictions in a subfamily of scale parameters under a precautionary loss function

ABSTRACT

This paper deals with Bayes, robust Bayes, and minimax predictions in a subfamily of scale parameters under an asymmetric precautionary loss function. In Bayesian statistical inference, the goal is to obtain optimal rules under a specified loss function and an explicit prior distribution over the parameter space. However, in practice, we are not able to specify the prior totally or when a problem must be solved by two statisticians, they may agree on the choice of the prior but not the values of the hyperparameters. A common approach to the prior uncertainty in Bayesian analysis is to choose a class of prior distributions and compute some functional quantity. This is known as Robust Bayesian analysis which provides a way to consider the prior knowledge in terms of a class of priors Γ for global prevention against bad choices of hyperparameters. Under a scale invariant precautionary loss function, we deal with robust Bayes predictions of Y based on X. We carried out a simulation study and a real data analysis to illustrate the practical utility of the prediction procedure.     

The Lorenz Curve for Model Assessment in Exponential Order Statistic Models

A goodness-of-fit technique for random samples from the exponential distribution based on the sample Lorenz curve is adapted for use in the exponential order statistic (EOS) model. In the EOS model, only those observations in a random sample from the exponential distribution of unknown size N that are less than some known stopping time T are observable. The model is known as the Jelinski-Moranda model in software reliability, where it is used to estimate the number of bugs in software during development. Distributional results are derived for the distance between the sample Lorenz curve and the population Lorenz curve so that it can be used as a goodness-of-fit test statistic. Simulations show that the test has good power against several alternative distributions. Simulations also indicate that in some cases, model misspecification leads to poor parameter estimation. A plotting procedure provides a means of graphical assessment of fit.     

试论生物多样性的丧失与保护

本文介绍了生物多样性丧失的直接原因及根源,提出了经济与空间并重的保护措施.     

Order-preserving Estimators and an Inequality on the Integration of Zonal Polynomial

ABSTRACT

Suppose X , p × p p.d. random matrix, has the distribution which depends on a p × p p.d. parameter matrix Σ and this distribution is orthogonally invariant. The orthogonally invariant estimator of Σ which has the eigenvalues of the same order as the eigenvalues of X is called order-preserving. We conjecture that a non-order-preserving estimator is dominated by modified order-preserving estimators with respect to the entropy (Stein's) loss function. We show that an inequality on the integration of zonal polynomial is sufficient for this conjecture. We also prove this inequality for the case p = 2.     

Stein-type estimation using ranked set sampling

In this study, we consider the application of the James–Stein estimator for population means from a class of arbitrary populations based on ranked set sample (RSS). We consider a basis for optimally combining sample information from several data sources. We succinctly develop the asymptotic theory of simultaneous estimation of several means for differing replications based on the well-defined shrinkage principle. We showcase that a shrinkage-type estimator will have, under quadratic loss, a substantial risk reduction relative to the classical estimator based on simple random sample and RSS. Asymptotic distributional quadratic biases and risks of the shrinkage estimators are derived and compared with those of the classical estimator. A simulation study is used to support the asymptotic result. An over-riding theme of this study is that the shrinkage estimation method provides a powerful extension of its traditional counterpart for non-normal populations. Finally, we will use a real data set to illustrate the computation of the proposed estimators.     

Bayes estimators of the reliability of the logistic distribution

Bayes estimators of the reliability function of the logistic distribution are obtained using the methods of Lindley (1980) and Tierney & Kadane (1986). Squared-error and log-odds squared-error loss functions are used. A numerical example is presented. Comparisons are made between these two procedures, based on a Monte Carlo simulation study.     

History of perinatal loss and maternal–fetal attachment behaviors

BackgroundMaternal–fetal attachment (MFA) is an important requirement for optimal maternal–infant adaptation. Current studies showed conflicting findings about whether a history of perinatal loss (fetal/neonatal death) affects maternal attachment in pregnancy.Research question“Does a history of perinatal loss affect maternal–fetal attachment behaviors?”MethodsOne hundred women with and without a history of PL were recruited using a convenience method of sampling, from prenatal care services affiliated to Shahid Behesti University of Medical Sciences. Data collected by questionnaires from a convenience sample of multiparous women in the 3rd trimester of pregnancy with no surviving children were compared with data from a selected cohort of primigravid women. The two groups of women were matched for health and literacy. The data collected included demographic characteristics and responses to 24 questions in five groups of behaviors on the Persian version of Cranly's Maternal–Fetal Attachment Scale. Data were analyzed by SPSS 13 and using t, ANOVA, Chi square, Pearson correlation and Mann–Whitney tests.FindingsFinding showed that total score of MFA for women with a history of PL (68.95 ± 9.20%) is not significantly different from this score for women without such a history (71.22 ± 11.75%; p < 0.05). Women with a history of PL had a significantly lower score for a subgroup of behaviors “differentiation of self from fetus” compared to women without of a history of PL (78.25 vs. 83.21%; p < 0.05). But, there were no statistically significant differences between two groups respecting to other subgroups of behaviors between two groups.ConclusionIn this study, a history of pregnancy loss was found to be associated with disturbances in the group of maternal–fetal attachment behaviors related to “differentiation of self from fetus” in a subsequent pregnancy.