Classification rules for triply multivariate data with an AR(1) correlation structure on the repeated measures over time

In this article we study the problem of classification of three-level multivariate data, where multiple q$q$-variate observations are measured on u$u$-sites and over p$p$-time points, under the assumption of multivariate normality. The new classification rules with certain structured and unstructured mean vectors and covariance structures are very efficient in small sample scenario, when the number of observations is not adequate to estimate the unknown variance–covariance matrix. These classification rules successfully model the correlation structure on successive repeated measurements over time. Computation algorithms for maximum likelihood estimates of the unknown population parameters are presented. Simulation results show that the introduction of sites in the classification rules improves their performance over the existing classification rules without the sites.     

A likelihood based estimator for vector autoregressive processes

A onestep estimator, which is an approximation to the unconditional maximum likelihood estimator (MLE) of the coefficient matrices of a Gaussian vector autoregressive process is presented. The onestep estimator is easy to compute and can be computed using standard software. Unlike the computation of the unconditional MLE, the computation of the onestep estimator does not require any iterative optimization and the computation is numerically stable. In finite samples the onestep estimator generally has smaller mean square error than the ordinary least squares estimator. In a simple model, where the unconditional MLE can be computed, numerical investigation shows that the onestep estimator is slightly worse than the unconditional MLE in terms of mean square error but superior to the ordinary least squares estimator. The limiting distribution of the onestep estimator for processes with some unit roots is derived.     

缺少的分享——喜马拉雅东部(中国云南西北部)作为“整体社会事实”的分享的仪式语言

中华人民共和国成立以前,云南西北部怒江、独龙江流域居住的独龙族、怒族等邻近族群之间存在着一种共通的"议式语言".这种仪式语言通过宗教祭祀活动以及分享杀牲后的肉食过程体现出来.在这一地域社会中,各种社会、政治和经济关系都依赖于这种仪式语言展开.虽然目前这种分享的仪式日渐式微,但分享的意识依然体现着族群内部的"社会结合"方式.通过独龙族仪式语言的个案分析,旨在与利奇关于克钦社会的"仪式语言"研究进行对话.     

“They Make Me Not Wanna Have a Child”: Effects of Companion Animals on Fertility Intentions of the Childfree

This article argues that for some who are childfree, the increasing perception of the companion animal as a sentient being with agency provides a deep, meaningful relationship with the power to inform fertility intentions. Qualitative, in‐depth interviews with childfree companion animal owners reveal that this relationship serves to reinforce previous fertility choices such as delaying or completely opting out of childbirth, thus affecting present household structure. This is reflected in the active choice by some participants to have companion animals instead of human children, the presence of a cost‐benefit analysis concerning animal companions and human children, and narratives that express a desire to mother or nurture as fulfilled in the relationship with the companion animal. Implications of these findings for both demography and marriage and family research in the United States are discussed.     

Life Course Changes in Smoking by Gender and Education: A Cohort Comparison Across France and the United States

Widening of educational disparities and a narrowing female advantage in mortality stem in good part from disparities in smoking. The changes in smoking and mortality disparities across cohorts and countries have been explained by an epidemic model of cigarette use but are also related to life course changes. To better describe and understand changing disparities over the life course, we compare age patterns of smoking in three cohorts and two nations (France and the US) using smoking history measures from the 2010 French health barometer (N = 20,940) and the 2010 US National Health Interview Survey Sample Adult File (N = 20,444). The results demonstrate statistically significant widening of gender and educational differences from adolescence to early and middle adulthood, thus accentuating the disparities already emerging during adolescence. In addition, the widening disparities over the life course have been changing across cohorts: age differences in educational disparities have grown in recent cohorts (especially in France), while age differences in gender disparities have narrowed. The findings highlight the multiple sources of inequality in smoking and health in high-income nations.     

Adjustment for nonresponse with variables from different sources: Bias correction and precision loss,with application to the Swiss European Social Survey 2012

ABSTRACT

Adjustment for nonresponse should reduce the nonresponse bias without decreasing the precision of the estimates. Adjustment for nonresponses are commonly based on socio-demographic variables, although these variables may be poorly correlated with response propensities and with variables of interest. Such variables nevertheless have the advantage of being available for all sample units, whether or not they are participating in the survey. Alternatively, adjustment for nonresponse can be obtained from a follow-up survey aimed at sample units which did not participate in the survey and from which the variables are designed to be correlated with response propensities. However, information collected through these follow-up surveys is not available for people in the sample who participated neither in the survey nor in its nonresponse follow-up. These two sets of variables when used in a nonresponse model for the Swiss European Social Survey 2012 differ only slightly with regard to their effect on bias correction and on the precision of estimates. The variables from the follow-up are performing slightly better. In both cases, the adjustment for nonresponse performs poorly.     

Optimal and lead-in adaptive allocation for binary outcomes: A comparison of Bayesian methods

We compare posterior and predictive estimators and probabilities in response-adaptive randomization designs for two- and three-group clinical trials with binary outcomes. Adaptation based upon posterior estimates are discussed, as are two predictive probability algorithms: one using the traditional definition, the other using a skeptical distribution. Optimal and natural lead-in designs are covered. Simulation studies show that efficacy comparisons lead to more adaptation than center comparisons, though at some power loss, skeptically predictive efficacy comparisons and natural lead-in approaches lead to less adaptation but offer reduced allocation variability. Though nuanced, these results help clarify the power-adaptation trade-off in adaptive randomization.