大学生自我和谐与心理健康的关系研究

探讨大学生自我和谐与性别、专业之间的关系，自我与经验、自我刻板性因子与心理健康各因子之间的关系，有助于我们有针对性地开展学校心理健康教育，提高大学生的心理健康水平。     

An EM Algorithm for Smoothing the Self-consistent Estimator of Survival Functions with Interval-censored Data

Interval-censored data arise in a wide variety of application and research areas such as, for example, AIDS studies (Kim et al ., 1993) and cancer research (Finkelstein, 1986; Becker & Melbye, 1991). Peto (1973) proposed a Newton–Raphson algorithm for obtaining a generalized maximum likelihood estimate (GMLE) of the survival function with interval-cen sored observations. Turnbull (1976) proposed a self-consistent algorithm for interval-censored data and obtained the same GMLE. Groeneboom & Wellner (1992) used the convex minorant algorithm for constructing an estimator of the survival function with "case 2" interval-censored data. However, as is known, the GMLE is not uniquely defined on the interval [0, ∞]. In addition, Turnbull's algorithm leads to a self-consistent equation which is not in the form of an integral equation. Large sample properties of the GMLE have not been previously examined because of, we believe, among other things, the lack of such an integral equation. In this paper, we present an EM algorithm for constructing a GMLE on [0, ∞]. The GMLE is expressed as a solution of an integral equation. More recently, with the help of this integral equation, Yu et al . (1997a, b) have shown that the GMLE is consistent and asymptotically normally distributed. An application of the proposed GMLE is presented     

Pseudo Self-Consistent Estimation of a Copula Model with Informative Censoring

Abstract.  We consider the case where a terminal event censors a non-terminal event, but not vice versa. When the events are dependent, estimation of the distribution of the non-terminal event is a competing risks problem, while estimation of the distribution of the terminal event is not. The dependence structure of the event times is formulated with the gamma frailty copula on the upper wedge, with the marginal distributions unspecified. With a consistent estimator of the association parameter, pseudo self-consistency equations are derived and adapted to the semiparametric model. Existence, uniform consistency and weak convergence of the new estimator for the marginal distribution of the non-terminal event is established using theories of empirical processes, U -statistics and Z -estimation. The potential practical utility of the methodology is illustrated with simulated and real data sets.     

Nonparametric estimation with left-truncated and right-censored data when the sample size before truncation is known

In this article, we consider nonparametric estimation of the survival function when the data are subject to left-truncation and right-censoring and the sample size before truncation is known. We propose two estimators. The first estimator is derived based on a self-consistent estimating equation. The second estimator is obtained by using the constrained expectation-maximization algorithm. Simulation results indicate that both estimators are more efficient than the product-limit estimator. When there is no censoring, the performance of the proposed estimators is compared with that of the estimator proposed by Li and Qin [Semiparametric likelihood-based inference for biased and truncated data when total sample size is known, J. R. Stat. Soc. B 60 (1998), pp. 243–254] via simulation study.     

临床医生自我和谐现状及影响因素探究

采用自我和谐量表、临床医生工作压力源问卷和中文版医患关系问卷,调查了湖南省22所医院的363名临床医生。结果表明,临床医生在自我和谐量表各维度的得分均低于常模(P<0.01),其自我和谐现状不容乐观,且在年龄、性别、学历、职称、医院级别等人口学变量上存在差异(P<0.05);临床医生的工作压力源及医患关系均与自我和谐水平有高相关(P<0.001)。文章从工作压力和医患关系两角度探讨了影响临床医生自我和谐的主要因素。     

A Nonparametric Estimator of Survival Functions for Arbitrarily Truncated and Censored Data

It is well-known that the nonparametric maximum likelihood estimator (NPMLE) may severely under-estimate the survival function with left truncated data. Based on the Nelson estimator (for right censored data) and self-consistency we suggest a nonparametric estimator of the survival function, the iterative Nelson estimator (INE), for arbitrarily truncated and censored data, where only few nonparametric estimators are available. By simulation we show that the INE does well in overcoming the under-estimation of the survival function from the NPMLE for left-truncated and interval-censored data. An interesting application of the INE is as a diagnostic tool for other estimators, such as the monotone MLE or parametric MLEs. The methodology is illustrated by application to two real world problems: the Channing House and the Massachusetts Health Care Panel Study data sets.     

Generalized Self-Consistency: Multinomial logit model and Poisson likelihood

A generalized self-consistency approach to maximum likelihood estimation (MLE) and model building was developed in Tsodikov [2003. Semiparametric models: a generalized self-consistency approach. J. Roy. Statist. Soc. Ser. B Statist. Methodology 65(3), 759–774] and applied to a survival analysis problem. We extend the framework to obtain second-order results such as information matrix and properties of the variance. Multinomial model motivates the paper and is used throughout as an example. Computational challenges with the multinomial likelihood motivated Baker [1994. The Multinomial–Poisson transformation. The Statist. 43, 495–504] to develop the Multinomial–Poisson (MP) transformation for a large variety of regression models with multinomial likelihood kernel. Multinomial regression is transformed into a Poisson regression at the cost of augmenting model parameters and restricting the problem to discrete covariates. Imposing normalization restrictions by means of Lagrange multipliers [Lang, J., 1996. On the comparison of multinomial and Poisson log-linear models. J. Roy. Statist. Soc. Ser. B Statist. Methodology 58, 253–266] justifies the approach. Using the self-consistency framework we develop an alternative solution to multinomial model fitting that does not require augmenting parameters while allowing for a Poisson likelihood and arbitrary covariate structures. Normalization restrictions are imposed by averaging over artificial “missing data” (fake mixture). Lack of probabilistic interpretation at the “complete-data” level makes the use of the generalized self-consistency machinery essential.     

An approach to non-linear principal components analysis using radially symmetric kernel functions

An approach to non-linear principal components using radially symmetric kernel basis functions is described. The procedure consists of two steps: a projection of the data set to a reduced dimension using a non-linear transformation whose parameters are determined by the solution of a generalized symmetric eigenvector equation. This is achieved by demanding a maximum variance transformation subject to a normalization condition (Hotelling's approach) and can be related to the homogeneity analysis approach of Gifi through the minimization of a loss function. The transformed variables are the principal components whose values define contours, or more generally hypersurfaces, in the data space. The second stage of the procedure defines the fitting surface, the principal surface, in the data space (again as a weighted sum of kernel basis functions) using the definition of self-consistency of Hastie and Stuetzle. The parameters of this principal surface are determined by a singular value decomposition and crossvalidation is used to obtain the kernel bandwidths. The approach is assessed on four data sets.     

电商平台品牌形象对消费者购买意愿的影响——消费者自我一致性的调节作用

随着平台经济的兴起以及电子商务的迅速发展,诸多种类的电子商务平台涌现出来,竞争的加剧使得电子商务平台企业越来越重视品牌形象的建设以吸引更多的消费者。以电子商务平台为研究对象,将电商平台品牌形象划分为三个维度:电商平台品牌表现、电商平台品牌个性、电商平台公司形象三个维度,构建电商平台品牌形象、购买意愿和自我一致性之间关系的理论模型。研究结果表明:电商平台品牌形象三维度均正向影响着消费者购买意愿;消费者自我一致性越高,电商平台品牌个性和公司形象对消费者购买意愿的影响越强,反之越弱;消费者自我一致性在电商平台品牌表现与购买意愿之间无调节作用。     

不同家庭教养方式大学生的自我和谐调查分析

文章采用《自我和谐量表》对民主型、权威型、放纵型家庭教养方式下成长起来的大学生进行测量,分析结果表明：民主型家庭教养方式下成长的大学生的自我和谐程度显著高于大学生常模;权威型、放纵型家庭教养方式下成长的大学生相对大学生常模表现出更大的不和谐;相同家庭教养方式对不同性别大学生的自我和谐程度影响是相似的。