Trajectory and Predictors of Early Adolescent Alcohol Use

The aim of this study was to identify the developmental trajectory and predictors of Korean early adolescents’ alcohol use. The sample comprised 2844 adolescents who participated in the five‐wave longitudinal Korea Youth Panel Study, in which students were assessed annually from grade 4 (aged 11 years) in 2004 to grade 8 (aged 15 years) in 2008. Latent growth curve (LGC) modeling was conducted and a quadratic (J‐shaped) LGC model was supported. Personality‐ and environment‐system predictors, based on problem‐behavior theory, were specified to account for variation in intra‐individual changes in alcohol use. Self‐control, depressive affect, parental abuse, number of drinking friends, and gender significantly predicted the initial level of alcohol use. Self‐control, depressive affect, parental abuse, peer attachment, gender, and family structure predicted the quadratic slope that was associated with the rate of acceleration of alcohol use. These findings suggest that more effort needs to be directed toward the implementation of alcohol prevention programs early in elementary schools and practitioners who are involved in effective alcohol‐prevention and intervention programs that are aimed at delaying the initiation of alcohol use and reducing drinking during adolescence should consider various psychosocial factors.     

关于出版社针对农业科技类图书发行的思考

随着现代农业的快速发展和国家惠农政策的陆续出台,相关出版社对农业科技类图书的出版发行工作愈发重视,尤其是近年来“农家书屋”工程的实施,使得农科类图书出版的品种和数量大幅增长.但是,其发行的现状与农村读者的要求尚有较大差距,同质化严重、发行渠道不健全等问题是制约该类图书发行的严重障碍.尝试从出版社的角度出发,针对农科类图书在发行工作中存在的问题提出一些解决对策和建议.     

高职院校师德建设的对策研究

教师是人类灵魂的工程师,他担负着教书育人,传播人类文明,培养合格人才,提高民族素质的重任。师德建设既是一种职业要求．也是一种历史责任。本文拟从教师及学校两个角度出发探讨提升师德建设的对策,以期为解决目前师德建设方面存在的问题建言献策。     

《卡勒瓦拉》与《格萨尔王传》之比较研究

芬兰民族史诗《卡勒瓦拉》已被各国研究家公认为世界伟大的史诗之一,联合国教科文组织也确认它是世界性的民族史诗,是芬兰民族文化的基石。它与藏族英雄史诗《格萨尔王传》之间存在着很多相似之处,但也有不少个性的差异。从多角度入手,对藏族《格萨尔王传》和芬兰《卡勒瓦拉》进行分析和比较研究。从而较为系统、全面地研究和分析这些异同,必将有助于深入理解《格萨尔王传》的艺术魅力、文化内涵和文学价值。     

读《清人别集总目》零札——以“漫社”社友为主体

《清人别集总目》是一部十分重要的工具书,但同时也存在大量的疏忽。现在依原书次序,以＂漫社＂社友作为主体,就其中殳庆源、邱翊华、向迪琮、杨济、吴宗元、陈韬、宗威、俞寿沧、姚宗堂、商宝慈十位作家做一些考辨。     

Average run length comparison of multivariate control charts

In this paper we use Monte Carlo Simulation methodology to compare the effectiveness of five multivariate quality control methods, namely Hotelling T ², Multivariate Shewhart Char, Discriminant Analysis, Decomposition Method, and Multivariate Ridge Residual Chart-developed by Authors-, for controlling the mean vector in a multivariate process. P-dimensional multivariate normal data generated using different covariance structures. Various amount of shift in the mean vector is induced and the resulting Average Run Length (ARL) is computed. The effectiveness of each method with regard to ARL is discussed.     

Formulating robust regression estimation as an optimum allocation problem

The Mallows-type estimator, one of the most reasonable bounded influence estimators, often downweights leverage points regardless of the magnitude of the corresponding residual, and this could imply a loss of efficiency. In this article, we consider whether the efficiency of this bounded influence estimator could be improved by regarding both the robust x -distance and the residual size. We develop a new robust procedure based on the ideas of the Mallows-type estimator and the general robust recipe, where data been cleaned by pulling outliers towards their fitted values. Our basic idea is to formulate the robust estimation as an allocation problem, where the objective function is a Huber-type "loss" function, but the pulling resource is restricted. Using a mathematical programming technique, the pulling resource is optimally allocated to influential points <$>({x}_i, y_i)<$> with respect to residual size and given weights, <$>w({x}_i)<$>. Three previously published approaches are compared to our proposal via simulated experiments. In the case of contaminated data by regression outliers and "good" leverage points, the proposed robust estimator is a reasonable bounded influence estimator concerning both efficiency and norm of bias. In addition, the proposed approach offers the potential to establish constraints for the regression parameters and also may potentially provide insight regarding outlier detection.     

Testing Chaos Based on Empirical Distribution Function: A Simulation Study

It is well known that many classical statistical tests of randomness generally fail to distinguish chaos generated by some lower-dimensional deterministic dynamical systems from independent and identically distributed (i.i.d.) random series. In this paper, we suggest a powerful statistical testing method based on empirical distribution function that can well detect chaos and i.i.d. random series.     

Efficient computation of the performance of bootstrap and jackknife estimators of the variance of L-statistics

Calculation of the bootstrap and the jackknife estimators of the variance of a statistic often relies on approximation techniques because the exact values are difficult if not impossible to obtain analytically. For the special case where the statistic is a linear combination of order statistics we propose to calculate the exact values combinatorically, thus completely eliminating the second-stage simulation error.     

Sequential sampling in the search for new shared species

In microbial sciences, as well as other disciplines, it is often valuable to sample communities in a sequential or group sequential manner, in order to determine their structure or their similarity. We develop sequential sampling procedures to accomplish this by first assuming that one observation is drawn with replacement from each population at a time. Suppose that the sampling is terminated after n pairs of observations and k shared species were discovered, and assume that we receive payoff h(k)−cn, where h(k) is non-decreasing and the sampling cost c is non-negative. Similar to Rasmussen and Starr (1979), we show that an optimal stopping rule exists if h(k+1)−h(k) is non-increasing. An analogous result holds for group sequential sampling. This leads to using an estimate of the probability of discovering new shared species as a stopping indicator for comparing two populations with respect to the similarity index. We show by simulation and real examples that this is a feasible approach which can help to reduce the sample size.