A method for analyzing changes in response efficiency.

Although experimental effects typically are evaluated by summarizing levels of responding across time (e.g., calculating the mean levels of problem behavior during 10‐min sessions), these data summaries may obscure important mechanisms that may be responsible for changes in responding. A case study is reported to illustrate alternative methods of data analysis when decreasing trends in responding may be due to increases in response efficiency.     

A variable-selection heuristic for K-means clustering

One of the most vexing problems in cluster analysis is the selection and/or weighting of variables in order to include those that truly define cluster structure, while eliminating those that might mask such structure. This paper presents a variable-selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. The heuristic was subjected to Monte Carlo testing across more than 2200 datasets with known cluster structure. The results indicate the heuristic is extremely effective at eliminating masking variables. A cluster analysis of real-world financial services data revealed that using the variable-selection heuristic prior to the K-means algorithm resulted in greater cluster stability.     

幽默平面广告的适用性研究

为了探讨哪一类别商品的平面广告更适合于采用幽默的诉求方式,研究随机选取160大学生为被试,以16则改编平面广告为实验材料,以广告类型（幽默,非幽默）、商品类别为自变量,以广告评价、广告顺序为协变量,以商品的印象程度、喜爱程度、购买意向为因变量,进行平衡设计实验。结果表明,幽默广告具有较好广告效果,可以提高受众对大宗工具、小奖赏和小工具型商品的记忆;幽默平面广告更适用于低风险、功能性商品,不适用于高风险、享乐性商品。     

两水平研究中单维测验信度的估计

在心理、教育和管理等研究领域中,经常会碰到两水平（两层）的数据结构,如学生嵌套在班级中,员工嵌套在企业中。在两水平研究中,被试通常不是独立的,如果直接用单水平信度公式进行估计,会高估测验信度。文献上已有研究讨论如何更准确地估计两水平研究中单维测验的信度。本研究指出了现有的估计公式的不足之处,用两水平验证性因子分析推导出一个新的信度公式,举例演示如何计算,并给出简单的计算程序。     

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。     

Discourse analysis: Rich pickings for counsellors and therapists

Aim: It is only relatively recently that discourse analysis has begun to rise to prominence in the fields of counselling and psychotherapy. This paper briefly explains ways of understanding discourse analysis, discussing what the approach can offer counselling research and practice. Approach: An initial categorisation of recent discourse analysis studies is offered, to demonstrate diverse ways in which this type of research can address issues relevant to counselling practice. The five categories proposed range from the examination of language use in therapy to analyses that focus on the social structures, meanings and power relations related to therapy. Implications: The paper demonstrates that through the critical analysis of counselling sessions, research interviews, written texts and other materials, discourse analysis can provide insight into ways in which counselling operates as a social practice, and so help counsellors to contextualise their work within broader social structures and processes.     

A methodological investigation of the Intermodal Preferential Looking paradigm: Methods of analyses,picture selection and data rejection criteria

The Intermodal Preferential Looking paradigm provides a sensitive measure of a child's online word comprehension. To complement existing recommendations (Fernald, Zangl, Portillo, & Marchman, 2008), the present study evaluates the impact of experimental noise generated by two aspects of the visual stimuli on the robustness of familiar word recognition with and without mispronunciations: the presence of a central fixation point and the level of visual noise in the pictures (as measured by luminance saliency). Twenty-month-old infants were presented with a classic word recognition IPL procedure in 3 conditions: without a fixation stimulus (No Fixation – noisiest condition), with a fixation stimulus before trial onset (Fixation, intermediate), and with a fixation stimulus, a neutral background and equally salient images (Fixation Plus – least noisy). Data were systematically analyzed considering a range of data selection criteria and dependent variables (proportion of looking time towards the target, longest look, and time-course analysis). Critically, the expected pronunciation and naming interaction was only found in the Fixation Plus condition. We discuss the impact of data selection criteria and the dependent variable choice on the modulation of these effects across the different conditions.     

Transformation to achieve a longitudinally stationary factor pattern matrix

Meredith's method of extracting a factorially invariant solution is adapted to longitudinal settings. An explorational estimation procedure is presented which attempts to identify the longitudinal factor components of an across occasion variance-covariance matrix. This is effected by transforming an initial factor pattern matrix to stationarity. The estimation is performed in two parts, the first employing a stepwise algorithm to ascertain the dimensionality and existence of the longitudinal components and the second being the direct estimation of the existing factor pattern.     

A note on structural models for the circumplex

Jöreskog (1974) developed a latent variable model for the covariance structure of the circumplex which, under certain conditions, includes a model for a patterned correlation matrix (Browne, 1977). This model is of limited usefulness, however, in that it employs a known matrix that is rank deficient for many problems. Furthermore, the model is inappropriate for the circumplex which contains negative covariances. This paper presents alternative models for the perfect circumplex and quasi-circumplex that avoids these difficulties, and that includes the important model for a patterned correlation circumplex matrix. Two numerical examples are provided.This research was supported in part by a grant from the Graduate School of the University of Minnesota. I wish to thank M. W. Browne for suggesting the final model presented in this paper. James Steiger and the Editor also made several valuable suggestions.