Inappropriate Comparisons: The LGB Population's Missing Reference Group

ABSTRACT

Given that many professional organizations emphasize the need for comparing assessment results to appropriate reference groups in their codes of ethics, we consider this practice through an ecological perspective as it applies to the lesbian, gay, and bisexual (LGB) population. The purpose of norming and types of assessment bias is discussed with respect to LGB population, which frequently lack specific norming data. The authors discuss whether the LGB population has characteristics similar to other commonly normed for groups and explore how group-shared constructs such as minority stress and internalized homophobia may introduce bias and affect the validity of assessments. A social anxiety assessment as well as a personality disorder inventory are examined for bias as case examples explaining how these assessments may exhibit bias when used with the LGB population. Increases in validity and effects on treatment planning are discussed as benefits of providing LGB-specific norms. Risks of providing these norms, such as minimizing subgroup differences and possibly increasing the risk of discrimination are also addressed before providing clinicians with recommendations as to how they may minimize the risk of bias in their assessment process.     

Merging data from multiple sources: pretest and shrinkage perspectives

In this article, we have developed asymptotic theory for the simultaneous estimation of the k means of arbitrary populations under the common mean hypothesis and further assuming that corresponding population variances are unknown and unequal. The unrestricted estimator, the Graybill-Deal-type restricted estimator, the preliminary test, and the Stein-type shrinkage estimators are suggested. A large sample test statistic is also proposed as a pretest for testing the common mean hypothesis. Under the sequence of local alternatives and squared error loss, we have compared the asymptotic properties of the estimators by means of asymptotic distributional quadratic bias and risk. Comprehensive Monte-Carlo simulation experiments were conducted to study the relative risk performance of the estimators with reference to the unrestricted estimator in finite samples. Two real-data examples are also furnished to illustrate the application of the suggested estimation strategies.     

Variable selection for semiparametric proportional hazards model under progressive Type-II censoring

Variable selection is an effective methodology for dealing with models with numerous covariates. We consider the methods of variable selection for semiparametric Cox proportional hazards model under the progressive Type-II censoring scheme. The Cox proportional hazards model is used to model the influence coefficients of the environmental covariates. By applying Breslow’s “least information” idea, we obtain a profile likelihood function to estimate the coefficients. Lasso-type penalized profile likelihood estimation as well as stepwise variable selection method are explored as means to find the important covariates. Numerical simulations are conducted and Veteran’s Administration Lung Cancer data are exploited to evaluate the performance of the proposed method.     

A class of exponential-type ratio estimators of a general parameter

This paper addresses the problem of estimating a general parameter using information on an auxiliary variable X. We have suggested a class of exponential-type ratio estimators for the parameter and its properties are studied. It is identified that the estimators due to Upadhyaya et al. [Journal of Statistical Theory and Practice (2011), 5(2), 285–302] and Yadav and Kadilar [Revista Columbiana de Estadistica, (2013), 36(1), 145–152] are members of the proposed estimator. We have also shown that the suggested estimator is more efficient than the estimators of Upadhyaya et al. (2011 Upadhyaya, L.N., Singh, H.P., Chatterjee, S., Yadav, R. (2011). Improved ratio and product exponential type estimators. J. Stat. Theo. Pract. 5 (2): 285–302.[Taylor &; Francis Online] , [Google Scholar]) and Yadav and Kadilar (2013 Yadav, S.K., Kadilar, C. (2013). Improved exponential type ratio estimator of population variance. Revis. Colum. de Estadist. 36(1): 145–152. [Google Scholar]). Numerical illustration is provided in support of the present study.     

均值绝对偏差资产组合选择模型的算法

对均值绝对偏差模型进行了简化,并利用一种旋转算法求解。这种算法比单纯形算法的计算简便,且计算量更小。利用上海和深圳股市1 072支股票70期周末收盘价所作的实验结果表明,对于资产无上界限制的模型,计算20个不同最优投资组合需要1 274次旋转运算,上界为10%时需要1 570次旋转运算,每 次旋转运算约需1 14171次加法和乘法运算。     

非自由劳工与现代资本主义劳动关系的多样性

在马克思那里,资本主义生产方式的确立和发展,是以“双重自由的”雇佣工人的存在为基础的;并且,在从形式隶属到实际隶属、从绝对剩余价值生产到相对剩余价值生产的过渡,是作为资本主义发展的自然结果而出现的。一些当代马克思主义学者的研究则表明：资本积累与特定社会历史条件的互动。不仅会使绝对剩余价值生产和形式隶属长期延续下去,而且会重新创造出各种形态的非自由劳动关系,以维持资本的赢利能力。这些研究证实了资本主义发展的不平衡性,以及现代资本主义劳动关系的多样性和在特定条件下退化的可能性。     

学前儿童性别教育的研究现状及其启示

学前儿童性别教育的有关研究表明,社会上还存在着根深蒂固的性别歧视和性别偏见,身处特定环境中的学前教育教师以及图画书、教学媒体等仍然带有较强的性别歧视和性别偏见等性别刻板印记。为此,国家需要在学前儿童性别教育研究的基础上重视学前教育阶段的性别平等教育,制定相关的政策,建立性别教育的终身教育体系,构建教师性别平等教育的培训网络平台,以现代性别教育理念为指导,基于对儿童生理差异的尊重,设计出适合学前儿童身心发展特点的性别教育课程,全面有效地实施性别平等教育。     

城市群可持续发展水平演化及其影响因素研究——来自中国十大城市群的证据

采用基于变异系数的灰色关联分析方法,度量2002-2011年中国十大城市群可持续发展水平并分析其收敛性和影响因素。研究发现:十大城市群在经济发展水平、社会进步程度、生态环境状况、资源供给能力方面呈现显著的差异,城市群可持续发展水平并没有与经济增长的大趋势保持一致;城市群可持续发展水平收敛特征具有分区域特点,全国样本具有非绝对收敛但条件收敛的特征,东部地区城市群绝对收敛特征不显著,但条件收敛特征较明显,而中部与西部城市群具有绝对收敛和条件收敛特征;经济发展水平、社会进步程度等变量与城市群可持续发展水平之间正向相关,但其影响程度在不同区域具有显著差异。     

中国投资者股利偏好行为的实证分析

运用超额收益法对深圳和上海证券市场的股利政策市场效应进行实证研究,探析不同类型股利的市场效应及投资者行为。结果表明,中国证券投资者在投资决策过程由于受心理因素的影响,对于不同类型的股利政策做出了不同的市场反应,并表现出一定的股利偏好行为,即证券投资者对现金股利政策,尤其稳定的现金股利政策表现出明显的喜好行为,而对于不分配股利政策却表现出了漠视效应行为。     

Influence measure for the L1 regression

Because outliers and leverage observations unduly affect the least squares regression, the identification of influential observations is considered an important and integrai part of the analysis. However, very few techniques have been developed for the residual analysis and diagnostics for the minimum sum of absolute errors, L₁ regression. Although the L₁ regression is more resistant to the outliers than the least squares regression, it appears that outliers (leverage) in the predictor variables may affect it. In this paper, our objective is to develop an influence measure for the L₁ regression based on the likelihood displacement function. We illustrate the proposed influence measure with examples.