反应风格的测量与统计控制

反应风格是共同方法偏差的主要来源之一。本文首先讨论反应风格的定义和类型,梳理其危害,认为反应风格能使测验分数出现偏差,影响测验信效度分析和变量关系分析,有必要控制其危害。然后介绍了常用的反应风格测量方法,包括计数法和模型法两大类,对测量方法的选择给出了建议,在此基础上,就如何结合反应风格的测量方法与残差回归法、偏相关法来控制反应风格危害给出建议。     

Graph coloring, minimum-diameter partitioning, and the analysis of confusion matrices

It is well known that minimum-diameter partitioning of symmetric dissimilarity matrices can be framed within the context of coloring the vertices of a graph. Although confusion data are typically represented in the form of asymmetric similarity matrices, they are also amenable to a graph-coloring perspective. In this paper, we propose the integration of the minimum-diameter partitioning method with a neighborhood-based coloring approach for analyzing digraphs corresponding to confusion data. This procedure is capable of producing minimum-diameter partitions with the added desirable property that vertices with the same color have similar in-neighborhoods (i.e., directed edges entering the vertex) and out-neighborhoods (i.e., directed edges exiting the vertex) for the digraph corresponding to the minimum partition diameter.     

关系研究的新取向：社会网络分析

社会网络分析（Social Network Analysis, SNA）是用社会实体之间的关系来描述、解释和预测社会现象的一种研究取向。SNA提供了深入探究社会环境特征及其对个体心理发展影响的一种方法。本文基于SNA的发展历程,依次介绍了中心性分析、小团体分析、位置分析、QAP以及统计模型法。SNA在社会学研究中得到了较多应用,近年来在心理学研究中开始受到重视。     

加速追踪设计的方法和应用

加速追踪设计(ALD)是一种选择相邻多个群组同时进行短期追踪研究, 获得在测量上有重叠的多个群组追踪数据, 对多个群组数据进行合并建构一条在时间跨度上较长的发展趋势或增长曲线的方法。ALD结合真追踪和横断设计的特征, 既保持真追踪设计的大部分优点, 克服真追踪研究中由于重测效应和被试缺失导致的问题, 又尝试分离年龄、群组和历史时间效应, 在发展心理研究有重要应用。已有研究探讨ALD的数据分析方法、ALD的有效性及设计特征。未来研究应关注拓展设计条件下ALD的适应性, 探索非线性假设或群组效应显著时的数据分析方法和ALD中缺失数据处理问题。     

追踪研究方法在国内心理研究中的应用述评

以1982~2012年中国期刊网收录的88例追踪研究为对象,从应用现状、设计特征、数据处理三方面分析和评估追踪研究方法在国内心理研究的应用情况及存在的问题。结果显示,2005年之前追踪研究方法应用增长缓慢,2005年开始呈显著增长趋势,研究对象以未成年及成年早期群体为主。主要采用固定样本追踪设计,大部分研究测量2-3次、样本量在10~300之间、持续时间在3年内。61例有缺失的研究中,38例用删除法处理缺失;主要运用 HLM、方差分析、t检验和SEM分析追踪数据。相当部分研究存在测量次数少、样本量较小、持续时间短、被试缺失严重及数据处理方法相对陈旧问题。追踪研究方法的应用应注意,根据理论模型和研究有效性要求确定设计类型和设计特征,根据数据特征选择缺失处理方法和追踪数据分析方法。     

计划缺失设计——通过有意缺失让研究更高效

缺失值是社会科学研究中非常普遍的现象。全息极大似然估计和多重插补是目前处理缺失值最有效的方法。计划缺失设计利用特殊的实验设计有意产生缺失值, 再用现代的缺失值处理方法来完成统计分析, 获得无偏的统计结果。计划缺失设计可用于横断面调查减少(或增加)问卷长度和纵向调查减少测量次数, 也可用于提高测量有效性。常用的计划缺失设计有三式设计和两种方法测量。     

Parents' description of conduct problems in their children - a test of the Eyberg Child Behavior Inventory (ECBI) in a Swedish sample aged 3-10

The Eyberg Child Behavior Inventory (ECBI) is a widely used 36-item uni-dimensional parent rating scale constructed to measure disruptive behavior problems in children. However, in an American sample a 22-item version, including three subscales, has been suggested in order to increase the usefulness of the ECBI. Two studies were conducted to test the ECBI in a Swedish sample (N = 841). The aims of Study I were (a) examine the psychometric properties of the ECBI (b) to investigate the correspondence between mothers' and fathers' ratings, and (c) to obtain Swedish norms. The aim of Study II was to test the suggested three-factor solution in the Swedish sample using a confirmatory factor analysis (CFA). The ECBI showed good psychometric properties also in the present study, and Swedish normative data is presented. The best-fitting CFA-model was identical to the previously suggested three-factor model, which thus might be a useful alternative to the 36-item version.     

Treatment of Missing Data: Beyond Ends and Means

The ethical decision making process behind the treatment of missing data has yet to be examined in the research literature in any discipline. The purpose of the current paper is to begin to discuss this decision-making process in view of a Foucauldian framework. The paper suggests how the ethical treatment of missing data should be considered from the adoption of this theoretical framework.     

Limited information estimation and testing of discretized multivariate normal structural models

Discretized multivariate normal structural models are often estimated using multistage estimation procedures. The asymptotic properties of parameter estimates, standard errors, and tests of structural restrictions on thresholds and polychoric correlations are well known. It was not clear how to assess the overall discrepancy between the contingency table and the model for these estimators. It is shown that the overall discrepancy can be decomposed into a distributional discrepancy and a structural discrepancy. A test of the overall model specification is proposed, as well as a test of the distributional specification (i.e., discretized multivariate normality). Also, the small sample performance of overall, distributional, and structural tests, as well as of parameter estimates and standard errors is investigated under conditions of correct model specification and also under mild structural and/or distributional misspecification. It is found that relatively small samples are needed for parameter estimates, standard errors, and structural tests. Larger samples are needed for the distributional and overall tests. Furthermore, parameter estimates, standard errors, and structural tests are surprisingly robust to distributional misspecification. This research was supported by the Department of Universities, Research and Information Society (DURSI) of the Catalan Government, and by grants BSO2000-0661 and BSO2003-08507 of the Spanish Ministry of Science and Technology.