A social interaction model with an extreme order statistic

In this paper, we introduce a social interaction econometric model with an extreme order statistic to model peer effects. We show that the model is a well‐defined system of equations and that it is a static game with complete information. The social interaction model can include exogenous regressors and group effects. Instrumental variables estimators are proposed for the general model that includes exogenous regressors. We also consider distribution‐free methods that use recurrence relations to generate moment conditions for estimation. For a model without exogenous regressors, the maximum likelihood approach is computationally feasible.     

我国互联网药品交易政策的发展与监管研究

目的：梳理我国互联网药品交易政策,为我国互联网药品交易监管提出相应建议。方法：通过国家食品药品监督管理总局（CFDA）网站,收集和整理我国互联网药品交易的相关政策,梳理我国互联网药品市场的演变历史和脉络,总结政策对于我国互联网药品交易的影响,并对当前监管工作中存在的问题进行分析。结果与结论：我国互联网药品监管政策对互联网药品交易的企业规模、药品种类以及物流运输方面都产生了深远影响。今后要继续完善法律法规、加强行业自律性建设、加强对网站的监督、运用信息化进行智能监管,促进我国互联网药品交易市场持续健康发展。     

Non‐trading day effects in asymmetric conditional and stochastic volatility models

Summary It is well known that non‐trading days (or holidays) can have significant effects on the returns in financial series. In this paper, we analyze three models of non‐trading day effects in stochastic volatility models with leverage effects, namely (i) the approach based on the dummy variable in conditional volatility models; (ii) the approach based on a discrete time approximation of a continuous time stochastic volatility model and (iii) the twin non‐trading day stochastic volatility model which nests the above two models. The three models are also estimated and tested within the asymmetric and exponential conditional volatility frameworks. All the models within the stochastic, asymmetric conditional and exponential conditional volatility frameworks are estimated and compared using a selection of financial returns series.     

Identification‐robust inference for endogeneity parameters in linear structural models

We provide a generalization of the Anderson–Rubin (AR) procedure for inference on parameters that represent the dependence between possibly endogenous explanatory variables and disturbances in a linear structural equation (endogeneity parameters). We stress the distinction between regression and covariance endogeneity parameters. Such parameters have intrinsic interest (because they measure the effect of latent variables, which induce simultaneity) and play a central role in selecting an estimation method (such as ordinary least‐squares or instrumental variable methods). We observe that endogeneity parameters might not be identifiable and we give the relevant identification conditions. These conditions entail a simple identification correspondence between regression endogeneity parameters and the usual structural parameters, while the identification of covariance endogeneity parameters typically fails as soon as global identification fails. We develop identification‐robust finite‐sample tests for joint hypotheses involving structural and regression endogeneity parameters, as well as marginal hypotheses on regression endogeneity parameters. For Gaussian errors, we provide tests and confidence sets based on standard Fisher critical values. For a wide class of parametric non‐Gaussian errors (possibly heavy‐tailed), we show that exact Monte Carlo procedures can be applied using the statistics considered. As a special case, this result also holds for usual AR‐type tests on structural coefficients. For covariance endogeneity parameters, we supply an asymptotic (identification‐robust) distributional theory. Tests for partial exogeneity hypotheses (for individual potentially endogenous explanatory variables) are covered as special cases. The proposed tests are applied to two empirical examples: the relation between trade and economic growth, and the widely studied problem of returns to education.     

Realized kernels in practice: trades and quotes

Summary Realized kernels use high‐frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same stock and find a remarkable level of agreement. We identify some features of the high‐frequency data, which are challenging for realized kernels. They are when there are local trends in the data, over periods of around 10 minutes, where the prices and quotes are driven up or down. These can be associated with high volumes. One explanation for this is that they are due to non‐trivial liquidity effects.     

A review of covariate selection for non‐experimental comparative effectiveness research

This paper addresses strategies for selecting variables for adjustment in non‐experimental comparative effectiveness research and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for a common cause pathway between treatment and outcome can remove confounding, whereas adjustment for other structural types may increase bias. For this reason, variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely known. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high‐dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses high‐dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher's knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. Copyright © 2013 John Wiley & Sons, Ltd.     

六味地黄丸市场透析

目的了解我国六味地黄丸的市场现状及发展趋势。方法对六味地黄丸的应用进展以及生产和销售概况进行介绍,并对其热销原因进行分析。结果与结论我国六味地黄丸市场潜力较大,企业应在密切关注市场变化的同时,逐步完善自身条件,以求进一步发展。     

Peer effects in bedtime decisions among adolescents: a social network model with sampled data

Using unique information on a representative sample of US teenagers, we investigate peer effects in adolescent bedtime decisions. We extend the nonlinear least‐squares estimator for spatial autoregressive models to estimate network models with network fixed effects and sampled observations on the dependent variable. We show the extent to which neglecting the sampling issue yields misleading inferential results. When accounting for sampling, we find that, besides the individual, family and peer characteristics, the bedtime decisions of peers help to shape one's own bedtime decision.     

My friend far,far away: a random field approach to exponential random graph models

We explore the asymptotic properties of strategic models of network formation in very large populations. Specifically, we focus on (undirected) exponential random graph models. We want to recover a set of parameters from the individuals' utility functions using the observation of a single, but large, social network. We show that, under some conditions, a simple logit‐based estimator is coherent, consistent and asymptotically normally distributed under a weak version of homophily. The approach is compelling as the computing time is minimal and the estimator can be easily implemented using pre‐programmed estimators available in most statistical packages. We provide an application of our method using the Add Health database.     

虎杖解毒无糖颗粒成型工艺的优选研究

目的：优选虎杖解毒无糖颗粒的成型工艺。方法：通过单因素实验,以颗粒的成型率、溶化性、吸湿率和流动性为评价指标,确定辅料种类;采用星点设计-效应面法和总评归一值法,优选虎杖解毒无糖颗粒的辅料总量、混合辅料的比例以及润湿剂乙醇的体积分数,并验证优化结果是否可靠。结果：最佳成型工艺条件为稠膏-辅料用量比（0.41∶1）,糊精-乳糖（2.79∶1）,润湿剂为60.9%乙醇;工艺试验验证结果与二项式拟合方程预测结果的偏差小于5%。结论：优选的成型工艺稳定可靠,实验方法简单直观,制得颗粒成型性、溶化性、抗湿性、流动性俱佳,为生产提供科学依据。     

Resting‐state fMRI and social cognition: An opportunity to connect

Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task‐based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting‐state fMRI may be just as important in understanding the biology and network nature of social processing. Resting‐state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so‐called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context‐dependent aberrations to context‐independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting‐state brain networks shows promise in linking results of task‐based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition—which may prove crucial in furthering our understanding of the social brain.     

我国互联网药品交易现状及发展趋势研究

目的：分析我国互联网药品交易现状及发展趋势,为互联网药品交易健康有序发展提供参考依据。方法：以国家食品药品监督管理总局（CFDA）的数据库为数据源,分析我国互联网药品交易服务资格证、企业与消费者之间交易平台（B2C）的交易规模、网上药店在第三方的平台分布、互联网药品交易现有政策以及监管现状。结果与结论：当前,我国互联网药品交易政策环境较好,医药电商企业数量和市场规模将持续增长。虽然还存在着法律规范不够健全、行业自律性不强、监管模式尚需完善等问题,但随着改革的不断深入,我国互联网药品交易市场必将进入快速发展阶段。     

Standard error correction in two‐stage estimation with nested samples

Data at different levels of aggregation are often used in two‐stage estimation, with estimates obtained at the higher level of aggregation entering the estimation at the lower level of aggregation. An example is customers within markets: first‐stage estimates on market data provide variables that enter the second‐stage model on customers. We derive the asymptotic covariance matrix of the second‐stage estimates for situations such as these. We implement the formulae in the Petrin–Train application of households’ choice of TV reception and compare the calculated standard errors with those obtained without correction. In this application, ignoring the sampling variance in the first‐stage estimates would be seriously misleading.     

Pupillometry in psychopharmacologic experiments

Considering data of various clinical pharmacological studies, in which computer-assisted pupillometry was utilized, we investigated the following questions: What are the effects of drugs of 7 psychopharmacological classes on the human pupil? Do dose-efficacy and time-efficacy curves based on pupillary variables provide cues about pharmacodynamic properties of psychotropic substances? Is there a relationship between pupillometric and critical flicker frequency measures? Is there a relation between pupillometric and quantitative electroencephalographic changes? Are there correlations between static pupillometric and pharmacokinetic (e.g. blood levels) variables? Our investigations demonstrated that static pupillometry-utilized in the described manner and under certain experimental conditions - provide valuable information about effects of psychotropic drugs on the central and autonomous nervous system.     

完全随机型神经网络在1,6-二磷酸果糖制备条件优化上的应用

采用改进模拟退火法作为人工神经网络的学习算法,提出了适用于连续型输入变量、整体优化的完全随机型神经网络,并在1,6-二磷酸果糖制备条件优化中得到了成功应用,单位体积产率显著提高,为工业化生产提供了有利条件。     

Estimation of fixed effects panel data partially linear additive regression models

In this paper, we investigate the estimation problem of fixed effects panel data partially linear additive regression models. Semi‐parametric fixed effects panel data regression models are tools that are well suited to econometric analysis and the analysis of cDNA micro‐arrays. By applying a polynomial spline series approximation and a profile least‐squares procedure, we propose a semi‐parametric least‐squares dummy variables estimator (SLSDVE) for the parametric component and a series estimator for the non‐parametric component. Under very weak conditions, we show that the SLSDVE is asymptotically normal and that the series estimator achieves the optimal convergence rate of the non‐parametric regression. In addition, we propose a two‐stage local polynomial estimation for the non‐parametric component by applying the additive structure and the series estimator. The resultant estimator is asymptotically normal and the asymptotic distribution of each additive component is the same as it would be if the other components were known with certainty. We conduct simulation studies to demonstrate the finite sample performance of the proposed procedures and we also present an illustrative empirical application.     

Influence of transport and time on blood variables commonly measured for the athlete biological passport

Some recent studies have characterized the stability of blood variables commonly measured for the Athlete Biological Passport. The aim of this study was to characterize the impact of different shipments conditions and the quality of the results returned by the haematological analyzer. Twenty‐two healthy male subjects provided five EDTA tubes each. Four shipment conditions (24, 36, 48, 72 h) under refrigerated conditions were tested and compared to a set of samples left in the laboratory also under refrigerated conditions (group control). All measurements were conducted using two Sysmex XT‐2000i analyzers. Haemoglobin concentration, reticulocytes percentage, and OFF‐score numerical data were the same for samples analyzed just after collection and after a shipment under refrigerated conditions up to 72 h. Detailed information reported especially by the differential (DIFF) channel scatterplot of the Sysmex XT‐2000i indicated that there were signs of blood deterioration, but were not of relevance for the variables used in the Athlete Biological Passport. As long as the cold chain is guaranteed, the time delay between the collection and the analyses of blood variables can be extended. Copyright© 2015 John Wiley & Sons, Ltd.     

阿苯达唑市场调查分析

目的:为临床合理、安全应用阿苯达唑提供参考。方法:通过搜索引擎及国内、外各医药网站、数据库,对阿苯达唑的研发情况、市场信息、适应证等情况进行分析。结果与结论:目前阿苯达唑有片剂、胶囊剂、颗粒剂、口服液、糖浆剂5种剂型;近几年其在国内销售额基本列居抗寄生虫药的前3位,生产厂家国内达39家;可用于治疗21种人体寄生虫病。阿苯达唑临床使用广泛,但是引发少见的脑炎综合征、过敏性休克等严重不良反应隐藏着治疗风险,须加强管理。     

The effects of caffeine on two computerized tests of attention and vigilance

Single doses of caffeine (250 mg, 500 mg) or placebo were administered double-blind to healthy volunteer subjects (n = 12), using a fully balanced crossover design (Williams square) with 1-week washout. Assessments were made predrug, and at 45 min and 165 min post-drug administration. The test battery comprised physiological measures (blood pressure, heart rate and urinary volume), subjective measures of alertness, a letter cancellation task (one-target, two-target and four-target versions), and two computerized measures of attention and vigilance: a rapid information processing task and a continuous attention task. Physiological variables did not alter following caffeine administration, but subjective and cognitive variables showed significant changes in the predicted direction. Thus, doserelated changes in subjective calmness and interest were observed, together with changes in performance for the letter cancellation task at low and intermediate difficulty levels. A dose-related performance improvement was observed for the rapid information processing task. The continuous attention task was also sensitive to the effects observed for the rapid information processing task. The continuous attention task was also sensitive to the effects of caffeine. The 250 mg dose offset the decline in attention observed under placebo, and indeed facilitated performance at both post-drug administration times. The 500 mg dose impaired performance at 45 min and improved it at the 165 min post-administration time. Sensitivity to vigilance change was also observed within test sessions for this test, indicating that the continuous attention task was more sensitive to caffeine-induced changes in attention than the rapid information processing task.