A model-based approach to multivariate principal component regression: Selecting principal components and estimating standard errors for unstandardized regression coefficients

Principal component regression (PCR) is a popular technique in data analysis and machine learning. However, the technique has two limitations. First, the principal components (PCs) with the largest variances may not be relevant to the outcome variables. Second, the lack of standard error estimates for the unstandardized regression coefficients makes it hard to interpret the results. To address these two limitations, we propose a model-based approach that includes two mean and covariance structure models defined for multivariate PCR. By estimating the defined models, we can obtain inferential information that will allow us to test the explanatory power of individual PCs and compute the standard error estimates for the unstandardized regression coefficients. A real example is used to illustrate our approach, and simulation studies under normality and nonnormality conditions are presented to validate the standard error estimates for the unstandardized regression coefficients. Finally, future research topics are discussed.     

A simulated annealing methodology for clusterwise linear regression

In many regression applications, users are often faced with difficulties due to nonlinear relationships, heterogeneous subjects, or time series which are best represented by splines. In such applications, two or more regression functions are often necessary to best summarize the underlying structure of the data. Unfortunately, in most cases, it is not known a priori which subset of observations should be approximated with which specific regression function. This paper presents a methodology which simultaneously clusters observations into a preset number of groups and estimates the corresponding regression functions' coefficients, all to optimize a common objective function. We describe the problem and discuss related procedures. A new simulated annealing-based methodology is described as well as program options to accommodate overlapping or nonoverlapping clustering, replications per subject, univariate or multivariate dependent variables, and constraints imposed on cluster membership. Extensive Monte Carlo analyses are reported which investigate the overall performance of the methodology. A consumer psychology application is provided concerning a conjoint analysis investigation of consumer satisfaction determinants. Finally, other applications and extensions of the methodology are discussed.     

The Italian Red Brigades and the structure and dynamics of terrorist groups

One of the problems in dealing with terrorism is that we have virtually no access to individual terrorists; only their actions are visible. The founders of the Italian terrorist group, the Red Brigades, on the other hand, have written about their experiences and have exhaustively explained their motivations. The author’s premise is that these autobiographies and her interviews with several of the group’s members give us access to the unconscious processes involved in the formation and operation of the group. After terrorist attacks, it is natural to ask whether the terrorists’ capacity for collective violence is an indication of personal pathology. This paper argues that the relevant pathology in the terrorist enterprise is not that of the individual but that of the group. Relying on the theories of groups of Freud (1921), Bion (1961), Anzieu (1984) and Kaes (2007), the author argues that psychoanalytic theory is essential to understanding the motivations and actions of violent groups which otherwise remain obscure. Although the discussion has been confined to one terrorist group, the author hopes that it can also be useful for understanding the unconscious dynamics of other groups structured around an ideology which mandates the destruction of human life.     

Integration,unintegration, disintegration: an introduction

This introduction to the two papers that follow by Anne Alvarez and Edna O'Shaughnessy is a revised version of the introduction to the ACP Study Day in February 2005 on ‘Integration, Unintegration, Disintegration’, at which Alvarez and O'Shaughnessy had presented and which the author had chaired. The background to the debate is given in terms of how the ACP Study Day itself came about, and the central theme is highlighted in terms of the question of whether unintegration is conceived of as a normal stage of development or only a temporary state of mind in response to catastrophic anxieties. Brief clinical material from a case supervised by the author is discussed in order to elaborate this central question.     

用层级相合性指标探测反应数据中噪音大小

不同的认知诊断模型（CDM）对反应数据中噪音的抗干扰能力不同,在评估CDM性能的模拟实验中,反应数据中所含噪音的大小是十分重要的实验条件。由于噪音的内隐性,为应用中选用相应的CDM带来困难。本文在认知模型已知条件下,欲使用MHCI和NHCI指标评估认知诊断测验的反应数据（0, 1评分）中噪音的大小。模拟实验表明,两指标与噪音存在明显的统计规律。尤其是以NHCI为主要自变量对噪音进行预测的回归方程中,回归模型解释率均接近90%;以此实现对噪音的有效预测,从而为选择CDM提供一个参考。     

领导-下属外向性人格匹配性与下属工作投入的关系:基于支配补偿理论

基于支配补偿理论,本研究考察领导与下属外向性人格的匹配性对下属工作投入的影响。对743对领导-下属进行配对问卷调查,在两个时间点获取调查数据。多项式回归与响应面分析表明,下属与领导外向性人格差异越大,下属工作投入水平越高。在下属与领导外向性人格存在差异的情形下,高下属外向性、低领导外向性组合比低下属外向性、高领导外向性组合,下属的工作投入水平更高。在下属与领导外向性人格一致的情形下,下属的工作投入和外向性人格存在倒U型曲线关系。研究证明了在外向性维度上领导和下属是支配互补的关系时,下属的工作投入水平更高。     

Regression and new beginnings: Michael, Alice and Enid Balint and the circulation of ideas

This article offers a new evaluation of Michael Balint's history. It starts with his growing up in Hungary and examines the central concepts of his writing: the analytic pair, regression and the basic fault and creativity, up to and including his renowned work on the eponymous Balint groups (which forged a unique link between psychoanalysis and medicine). While his name is, of course, well known, this article aims to bring his ideas to the attention of a modern analytic audience. Having trained in the 1920s with Ferenczi, Balint brought Ferenczi's literary inheritance to England where he lived until his death in 1970. His connections to Klein, Winnicott and Lacan, all of whom respected his analytic stance, are also examined. Furthermore, this article argues that his ideas were filtered through the theoretical lens of his first wife Alice Balint and later through Enid Balint, both of whom played a key - and rarely recognised - role in the development of his thought. It ends with a brief discussion of his ideas on analytic training and his quest, successful only after his death, to publish the complete Freud-Ferenczi correspondence, together with Ferenczi's diary.     

What Causes the Mean Bias of the Likelihood Ratio Statistic with Many Variables?

Abstract

Survey data often contain many variables. Structural equation modeling (SEM) is commonly used in analyzing such data. However, conventional SEM methods are not crafted to handle data with a large number of variables (p). A large p can cause T_ml, the most widely used likelihood ratio statistic, to depart drastically from the assumed chi-square distribution even with normally distributed data and a relatively large sample size N. A key element affecting this behavior of T_ml is its mean bias. The focus of this article is to determine the cause of the bias. To this end, empirical means of T_ml via Monte Carlo simulation are used to obtain the empirical bias. The most effective predictors of the mean bias are subsequently identified and their predictive utility examined. The results are further used to predict type I errors of T_ml. The article also illustrates how to use the obtained results to determine the required sample size for T_ml to behave reasonably well. A real data example is presented to show the effect of the mean bias on model inference as well as how to correct the bias in practice.     

子女越孝顺老年人越幸福吗?老年人孝道期待的作用

孝道是影响老年人幸福感的重要变量之一, 然而, 以往研究却得出相互矛盾的结论, 其中可能的重要原因之一是没有聚焦老年人孝道期待的实现程度。采用二次响应面回归分析探究老年人孝道期待和子女孝道支持行为之间的匹配度对老年人生活满意度和孤独感的影响。研究结果表明, 对于生活满意度而言, 和不匹配相比, 情感期待和情感支持以及联络期待和联络支持匹配时老年人生活满意度更高; 在期待和支持匹配的情况下, 生活满意度随信息期待和信息支持的增加而提高; 并且老年人的生活满意度仅随工具支持的增加而提高, 但与工具期待没有关系。对于孤独感而言, 在情感期待和情感支持二者不匹配时, 较于情感期待低于情感支持, 情感期待高于情感支持时老年人的孤独感更高; 孤独感仅随联络支持和信息支持的增加而降低, 与联络期待、信息期待、工具期待以及工具支持没有关系。该研究得出以下结论：老年人孝道期待的实现程度是提高其生活满意度的重要因素, 而情感期待高于情感支持是影响老年人孤独感的重要因素。     

Drivers’ and cyclists’ safety perceptions in overtaking maneuvers

Drivers overtaking cyclists on rural roads are a safety concern, as drivers need to handle the interaction with the cyclist and possibly an oncoming vehicle. Improving the maneuver’s outcome requires an understanding of not only the objective, measurable safety metrics, but also the subjective, perceived safety of each road user. Previous research has shown that the perceived safety of the cyclist is most at risk at the passing moment, when driver and cyclist are closest to each other. However, to develop safety measures, it is necessary to know how both road users perceive safety, by understanding the factors that influence their perceptions during the overtaking maneuver. This study measured the perceived safety of drivers in a test-track experiment in Sweden and the perceived safety of cyclists in a field test in Spain. For both drivers and cyclists, we developed Bayesian ordinal logistic regression models of perceived safety scores that take as input objective safety metrics representing the different crash risks at the passing moment. Our results show that while drivers’ perceived safety decreases when there is an oncoming vehicle with a low time-to-collision, cyclists’ perceived safety is reduced by a small lateral clearance and a high overtaking speed. Although our datasets are heterogeneous and limited, our results are in line with previous research. In addition, the Bayesian models presented in this paper are novel and may be improved in future studies once more naturalistic data become available. We discuss how our models may support infrastructure development and regulation, policymaking, driver coaching, the development of active safety systems, and automated driving by providing a possible method for predicting perceived safety.