Stepwise variable selection in factor analysis

It is very important to choose appropriate variables to be analyzed in multivariate analysis when there are many observed variables such as those in a questionnaire. What is actually done in scale construction with factor analysis is nothing but variable selection.In this paper, we take several goodness-of-fit statistics as measures of variable selection and develop backward elimination and forward selection procedures in exploratory factor analysis. Once factor analysis is done for a certain numberp of observed variables (thep-variable model is labeled the current model), simple formulas for predicted fit measures such as chi-square, GFI, CFI, IFI and RMSEA, developed in the field of the structural equation modeling, are provided for all models obtained by adding an external variable (so that the number of variables isp + 1) and for those by deleting an internal variable (so that the number isp – 1), provided that the number of factors is held constant.A programSEFA (Stepwise variable selection in Exploratory Factor Analysis) is developed to actually obtain a list of the fit measures for all such models. The list is very useful in determining which variable should be dropped from the current model to improve the fit of the current model. It is also useful in finding a suitable variable that may be added to the current model. A model with more appropriate variables makes more stable inference in general.The criteria traditionally often used for variable selection is magnitude of communalities. This criteria gives a different choice of variables and does not improve fit of the model in most cases.The URL of the programSEFA is http://koko15.hus.osaka-u.ac.jp/~harada/factor/stepwise/.     

Optimal scaling by alternating length-constrained nonnegative least squares, with application to distance-based analysis

An important feature of distance-based principal components analysis, is that the variables can be optimally transformed. For monotone spline transformation, a nonnegative least-squares problem with a length constraint has to be solved in each iteration. As an alternative algorithm to Lawson and Hanson (1974), we propose the Alternating Length-Constrained Non-Negative Least-Squares (ALC-NNLS) algorithm, which minimizes the nonnegative least-squares loss function over the parameters under a length constraint, by alternatingly minimizing over one parameter while keeping the others fixed. Several properties of the new algorithm are discussed. A Monte Carlo study is presented which shows that for most cases in distance-based principal components analysis, ALC-NNLS performs as good as the method of Lawson and Hanson or sometimes even better in terms of the quality of the solution. Supported by The Netherlands Organization for Scientific Research (NWO) by grant nr. 030-56403 for the “PIONEER” project “Subject Oriented Multivariate Analysis” to the third author. We would like to thank the anonymous referees for their valuable remarks that have improved the quality of this paper.     

Single Session Treatment of Test Anxiety with Eye Movement Desensitization and Reprocessing (EMDR)

One session of Eye Movement Desensitization and Reprocessing (EMDR) appeared to be an effective treatment for test anxiety, reducing reported physiological distress, worry, and fears of negative evaluation. The research design included two components: a comparison study, comparing Immediate Treatment and Wait List groups, and a replication study, comparing the treatment response of Immediate and Delayed (Treated Wait List) groups. Seventeen test anxious university students were randomly assigned to one session of EMDR or Wait List. At post-test, the Immediate group demonstrated significant improvement, compared to the Wait List group, on the Test Anxiety Inventory (TAI) and Fear of Negative Evaluation Scale. Treatment effects were maintained at follow-up. The Wait List group received treatment after post-measures were taken. Treatment of the Delayed group replicated effects. Improvement was reflected by large treatment effect sizes and a decrease in percentile ranking on the TAI from the 90th to the 50th percentile.     

元记忆监测与人格特征相互关系的实验研究

运用ＲＪＲ标准程序,考察了元记忆监测与两种人格维度（内外向以及情绪性）的关系,结果表明：元记忆监测水平受到了人格自身优势倾向性及其行为定向性的影响,人格的内外向特点和情绪稳定性特点直接制约着元记忆监测的准确性和稳定性。据此认为元记忆能力的度量和开发,应充分考虑人格因素的影响。     

连绵词语音类似的启动效应

研究采用快速启动范型考察了视觉连绵词加工中语音的自动激活.两个实验发现,无论是首字同音还是尾字同音启动都可以促进对连绵词的命名反应,且基本不受目标词熟悉性(词频高低)及真假词的影响.可以推断,至少在连绵词--这种单词素词的词汇通达中存在语音的自动激活,这种语音的激活可以说是前词的装配与词水平上的改变.     

序列位置内隐学习产生机制的实验研究

内隐学习是当今认知和学习领域继内隐记忆之后又一重要的研究课题。该研究利用序列反应时研究程式,通过两个实验,对序列位置内隐学习产生的机制进行了探讨。结果表明：（１）在序列反应时任务程式中,随着反应一刺激间隔的延长,序列位置内隐学习的学习量逐渐减少;（２）异形同模式迁移组和异形异模式迁移组被试间内隐学习量无显著差异,被试未能内隐地习得抽象的序列模式。说明序列位置内隐学习产生的基础是水平联结,在该实验条件下没有发现垂直联结存在的证据。     

Rank disagreement: A comparison of multi-criteria methodologies

A number of multi-criteria decision support techniques have emerged in recent years that use varying computational approaches to arrive at the most desirable solution and thereby ‘recommend’ a course of action. Decision makers who use the results of this analytic work should be assured that the computational schemes used by their supporting analysts or decision support software produce the appropriate solutions. We conducted a series of simulation experiments that compared the top-ranked options resulting from the computational algorithms that support Multi-Attribute Value Theory (MAVT) and three methods that are reported in the literature that allow rank reversals, the change in rank order of two options when an unrelated option is added or deleted from the analysis: the Analytical Hierarchy Process (AHP), Percentaging and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). We also included a Fuzzy algorithm proposed by Yager to gauge its consistency with the other algorithms, even though it is not subject to rank reversals. These experiments demonstrated that the MAVT and AHP techniques, when provided with the same decision outcome data, very often identify the same alternative as ‘best’. The other techniques are noticeably less consistent with MAVT, the Fuzzy algorithm being the least consistent. The situations under which the most frequent and significant differences occurred were dependent upon the method. The results of our experiments indicate that other issues (e.g. the processes used for problem structuring and the elicitation of value weights) are likely to be of greater significance to problem outcome (based on our experience) than the choice between the computational algorithms of MAVT and AHP. The results cause us to be concerned about the use of the other methods.     

The role of TPH2 variant rs4570625 in shaping infant attention to social signals

TPH2, the rate-limiting enzyme in the synthesis of serotonin, has been connected to several psychiatric outcomes. Its allelic variant, rs4570625, has been found to relate to individual differences in cognitive and emotion regulation during infancy with T-carriers of rs4570625 showing a relatively heightened attention bias for fearful faces. A significant gene-environment interaction was also reported with the T-carriers of mothers with depressive symptoms showing the highest fear bias.We investigated these associations in a sample of 8-month old infants (N = 330), whose mothers were prescreened for low/high levels of prenatal depressive and/or anxiety symptoms. Attention disengagement from emotional faces (neutral, happy, fearful, and phase-scrambled control faces) to distractors was assessed with eye tracking and an overlap paradigm. Maternal depressive symptoms were assessed at several time points during pregnancy and postpartum. The mean levels of symptoms at six months postpartum and the trajectories of symptoms from early pregnancy until six months postpartum were used in the analyses (N = 274).No main effect of the rs4570625 genotype on attention disengagement was found. The difference in fear bias between the genotypes was significant but in an opposite direction compared to a previous study. The results regarding the interaction of the genotype and maternal depression were not in accordance with the previous studies.These results show inconsistencies in the effects of the rs4570625 genotype on attention biases in separate samples of infants from the same population with only slight differences in age.