K-means may perform as well as mixture model clustering but may also be much worse: Comment on Steinley and Brusco (2011).

Steinley and Brusco (2011) presented the results of a huge simulation study aimed at evaluating cluster recovery of mixture model clustering (MMC) both for the situation where the number of clusters is known and is unknown. They derived rather strong conclusions on the basis of this study, especially with regard to the good performance of K-means (KM) compared with MMC. I agree with the authors' conclusion that the performance of KM may be equal to MMC in certain situations, which are primarily the situations investigated by Steinley and Brusco. However, a weakness of the paper is the failure to investigate many important real-world situations where theory suggests that MMC should outperform KM. This article elaborates on the KM–MMC comparison in terms of cluster recovery and provides some additional simulation results that show that KM may be much worse than MMC. Moreover, I show that KM is equivalent to a restricted mixture model estimated by maximizing the classification likelihood and comment on Steinley and Brusco's recommendation regarding the use of mixture models for clustering. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Evaluating mixture modeling for clustering: Recommendations and cautions.

This article provides a large-scale investigation into several of the properties of mixture-model clustering techniques (also referred to as latent class cluster analysis, latent profile analysis, model-based clustering, probabilistic clustering, Bayesian classification, unsupervised learning, and finite mixture models; see Vermunt & Magdison, 2002). Focus is given to the multivariate normal distribution, and 9 separate decompositions (i.e., class structures) of the covariance matrix are investigated. To provide a link to the current literature, comparisons are made with K-means clustering in 3 detailed Monte Carlo studies. The findings have implications for applied researchers in that mixture-model clustering techniques performed best when the covariance structure and number of clusters were known. However, as the information about the shape and number of clusters became unknown, degraded performance was observed for both K-means clustering and mixture-model clustering. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Integrative data analysis: The simultaneous analysis of multiple data sets.

There are both quantitative and methodological techniques that foster the development and maintenance of a cumulative knowledge base within the psychological sciences. Most noteworthy of these techniques is meta-analysis, which allows for the synthesis of summary statistics drawn from multiple studies when the original data are not available. However, when the original data can be obtained from multiple studies, many advantages stem from the statistical analysis of the pooled data. The authors define integrative data analysis (IDA) as the analysis of multiple data sets that have been pooled into one. Although variants of IDA have been incorporated into other scientific disciplines, the use of these techniques is much less evident in psychology. In this article the authors present an overview of IDA as it may be applied within the psychological sciences, discuss the relative advantages and disadvantages of IDA, describe analytic strategies for analyzing pooled individual data, and offer recommendations for the use of IDA in practice. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The analysis of profile data.

"Methods were suggested for handling 3 problems in the analysis of test profiles: measuring the similarity of profiles, discriminating the typical profiles of two or more groups, and clustering profiles into homogeneous groups. The suggested methods were, respectively, picturing profiles as interpoint distances in Euclidean space, use of the linear multiple-discriminant function, and factor analysis of profile cross-product terms. Some suggestions were given about transformations of profile data before further analysis." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The p-value fallacy and how to avoid it.

Null hypothesis significance tests are commonly used to provide a link between empirical evidence and theoretical interpretation. However, this strategy is prone to the "p-value fallacy" in which effects and interactions are classified as either "noise" or "real" based on whether the associated p value is greater or less than .05. This dichotomous classification can lead to dramatic misconstruals of the evidence provided by an experiment. For example, it is quite possible to have similar patterns of means that lead to entirely different patterns of significance, and one can easily find the same patterns of significance that are associated with completely different patterns of means. Describing data in terms of an inventory of significant and nonsignificant effects can thus completely misrepresent the results. An alternative analytical technique is to identify competing interpretations of the data and then use likelihood ratios to assess which interpretation provides the better account. Several different methods of calculating the likelihood ratios are illustrated. It is argued that this approach satisfies a principle of "graded evidence," according to which similar data should provide similar evidence. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The school as a psychological laboratory.

"Current training opportunities leading the graduate student of psychology to real understanding of children are… extremely limited… . Perhaps as good an explanation for the profession's neglect of such an important aspect of its field [child psychology] is to be found in the swings of academic fashion." To date, the public schools as settings for practicum experiences and internships have not been much exploited. Large city school systems present exciting possibilities. Courses of the Department of Psychology at the University of Chicago have used the Chicago public schools since the 1930s. Typical research studies in which the Chicago schools have made facilities and subjects available are enumerated. "On the employment side, the positions for school psychologists in the Chicago schools jumped from 66 in 1957 to 90 in 1958." Psychological work in the schools requires thoughtful preparation. "Psychology must sell its wares to skeptical, if not openly hostile, teachers and administrators." Psychologists "must drop their supercilious attitude toward some of the basic tasks of school psychology… . The tremendous potential of the schools as a laboratory for research and training in almost all phases of psychological study must be more fully realized." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An array of qualitative data analysis tools: A call for data analysis triangulation.

One of the most important steps in the qualitative research process is analysis of data. The purpose of this article is to provide elements for understanding multiple types of qualitative data analysis techniques available and the importance of utilizing more than one type of analysis, thus utilizing data analysis triangulation, in order to understand phenomenon more fully for school psychology research and beyond. The authors describe seven qualitative analysis tools: methods of constant comparison, keywords-in-context, word count, classical content analysis, domain analysis, taxonomic analysis, and componential analysis. Then, the authors outline when to use each type of analysis. In so doing, the authors use real qualitative data to help distinguish the various types of analyses. Furthermore, flowcharts and tables are provided to help delineate when to choose each type of analysis. Finally, the role of computer-assisted software in the qualitative data-analytic process is discussed. As such, use of the analyses outlined in this article should help to promote rigor in qualitative research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Virtual social environments as a tool for psychological assessment: Dynamics of interaction with a virtual spouse.

Computer games are advocated as a promising tool bridging the gap between the controllability of a lab experiment and the mundane realism of a field experiment. At the same time, many authors stress the importance of observing real behavior instead of asking participants about possible or intended behaviors. In this article, the authors introduce an online virtual social environment, which is inhabited by autonomous agents including the virtual spouse of the participant. Participants can freely explore the virtual world and interact with any other inhabitant, allowing the expression of spontaneous and unprompted behavior. The authors investigated the usefulness of this game for the assessment of interactions with a virtual spouse and their relations to intimacy and autonomy motivation as well as relationship satisfaction with the real-life partner. Both the intimacy motive and the satisfaction with the real-world relationship showed significant correlations with aggregated in-game behavior, which shows that some sort of transference between the real world and the virtual world took place. In addition, a process analysis of interaction quality revealed that relationship satisfaction and intimacy motive had different effects on the initial status and the time course of the interaction quality. Implications for psychological assessment using virtual social environments are discussed. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Profiling local optima in K-means clustering: Developing a diagnostic technique.

Using the cluster generation procedure proposed by D. Steinley and R. Henson (2005), the author investigated the performance of K-means clustering under the following scenarios: (a) different probabilities of cluster overlap; (b) different types of cluster overlap; (c) varying samples sizes, clusters, and dimensions; (d) different multivariate distributions of clusters; and (e) various multidimensional data structures. The results are evaluated in terms of the Hubert-Arabie adjusted Rand index, and several observations concerning the performance of K-means clustering are made. Finally, the article concludes with the proposal of a diagnostic technique indicating when the partitioning given by a K-means cluster analysis can be trusted. By combining the information from several observable characteristics of the data (number of clusters, number of variables, sample size, etc.) with the prevalence of unique local optima in several thousand implementations of the K-means algorithm, the author provides a method capable of guiding key data-analysis decisions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A double-structure structural equation model for three-mode data.

Structural equation models are commonly used to analyze 2-mode data sets, in which a set of objects is measured on a set of variables. The underlying structure within the object mode is evaluated using latent variables, which are measured by indicators coming from the variable mode. Additionally, when the objects are measured under different conditions, 3-mode data arise, and with this, the simultaneous study of the correlational structure of 2 modes may be of interest. In this article the authors present a model with a simultaneous latent structure for 2 of the 3 modes of such a data set. They present an empirical illustration of the method using a 3-mode data set (person by situation by response) exploring the structure of anger and irritation across different interpersonal situations as well as across persons. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The psychology of the Monty Hall problem: Discovering psychological mechanisms for solving a tenacious brain teaser.

The Monty Hall problem (or three-door problem) is a famous example of a "cognitive illusion," often used to demonstrate people's resistance and deficiency in dealing with uncertainty. The authors formulated the problem using manipulations in 4 cognitive aspects, namely, natural frequencies, mental models, perspective change, and the less-is-more effect. These manipulations combined led to a significant increase in the proportion of correct answers given by novice participants, largely because of the synergy of frequency-based formulation and perspective change (Experiments 1, 2). In a training study (Experiment 3) frequency formulation and mental models, but not Bayes's rule training, showed significant positive transfer in solving related problems. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

International psychological research that matters for policy and practice.

After a brief history of the Committee on International Relations of the American Psychological Association, 3 points are made about international psychological research that matters. First, it matters when the definition of the research problem area and the findings can potentially be reflected in policy change, in the practice of educators or psychologists, or in the mindsets of a new generation of researchers. Person-centered analysis of adolescents’ social and political attitudes has this potential and can complement variable-centered analysis. A cluster analysis of the IEA Civic Education Study’s data in 5 Western European and 5 Eastern European countries illustrates this. The following 5 clusters of adolescents were identified: those supportive of social justice but not participative, those active in conventional politics and the community, those indifferent, those disaffected, and a problematic cluster of alienated adolescents. Second, research that matters is situated in a cultural context. It is proposed that publications using data from any single country be required to include information about the cultural context in which the research was conducted. Finally, it matters that attention be given to the dynamics of the collaborative international research process, not only to research results. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The seemingly quixotic pursuit of a cumulative psychological science: Introduction to the special issue.

The goal of any empirical science is to pursue the construction of a cumulative base of knowledge upon which the future of the science may be built. However, there is mixed evidence that the science of psychology can accurately be characterized by such a cumulative progression. Indeed, some argue that the development of a truly cumulative psychological science is not possible with the current paradigms of hypothesis testing in single-study designs. The author explores this controversy as a framework to introduce the 6 articles that make up this special issue on the integration of data and empirical findings across multiple studies. The author proposes that the methods and techniques described in this set of articles can significantly propel researchers forward in their ongoing quest to build a cumulative psychological science. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Validation of the Abstraction Index as a tool for content-effects analysis and content analysis.

How does the degree of abstractness (Abstraction Index) of a magazine article affect reader interest and satisfaction? 340 readers of a magazine were interviewed about readership and satisfaction of items read. 10 hypotheses were tested. Abstractness discourages persistence but favors satisfaction. The Abstraction Index is useful. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Communication neuroscience as a tool for health psychologists.

Comments on the original article, Increased attention but more efficient disengagement: Neuroscientific evidence for defensive processing of threatening health information by L. T. E. Kessels, R. A. C. Ruiter, and B. M. Jansma (see record 2010-14873-005). Kessler et al present an example of Communication Neuroscience as a tool for understanding the mechanisms that lead some health messages to be processed in a way that facilitates impact whereas other messages are ignored. Kessels et al used event-related brain potentials (ERPs), a high temporal resolution method, to monitor neural activity in the moment that messages are presented. They use this technology to provide insight about the low-level attention processes through which individuals at highest risk (in this case, smokers) disengage from self-relevant health messages (threatening and nonthreatening smoking images). The findings of Kessels et al are convergent with prior theory and empirical work demonstrating that high threat messages may not achieve the desired effect if presented in isolation (Brown & Locker, 2009; Leventhal, Safer, & Panagis, 1983; Liberman & Chaiken, 1992). By using the tools of neuroscience, however, Kessels et al elucidate a mechanism that was not apparent through self-report or implicit (reaction time) measures. They demonstrate that high threat messages lead to increased attention capture, but more efficient disengagement when threatening messages are self-relevant; this in turn helps to explain why high threat messages may not have the desired effect, despite successfully capturing people’s attention. As such, this study illustrates one benefit of combining the tools of neuroscience with more familiar methods in health psychology. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Pooling data from multiple longitudinal studies: The role of item response theory in integrative data analysis.

There are a number of significant challenges researchers encounter when studying development over an extended period of time, including subject attrition, the changing of measurement structures across groups and developmental periods, and the need to invest substantial time and money. Integrative data analysis is an emerging set of methodologies that allows researchers to overcome many of the challenges of single-sample designs through the pooling of data drawn from multiple existing developmental studies. This approach is characterized by a host of advantages, but this also introduces several new complexities that must be addressed prior to broad adoption by developmental researchers. In this article, the authors focus on methods for fitting measurement models and creating scale scores using data drawn from multiple longitudinal studies. The authors present findings from the analysis of repeated measures of internalizing symptomatology that were pooled from three existing developmental studies. The authors describe and demonstrate each step in the analysis and conclude with a discussion of potential limitations and directions for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

K-balance partitioning: An exact method with applications to generalized structural balance and other psychological contexts.

Structural balance theory (SBT) has maintained a venerable status in the psychological literature for more than 5 decades. One important problem pertaining to SBT is the approximation of structural or generalized balance via the partitioning of the vertices of a signed graph into K clusters. This K-balance partitioning problem also has more general psychological applications associated with the analysis of similarity/dissimilarity relationships among stimuli. Accordingly, K-balance partitioning can be gainfully used in a wide variety of SBT applications, such as attraction and child development, evaluation of group membership, marketing and consumer issues, and other psychological contexts not necessarily related to SBT. We present a branch-and-bound algorithm for the K-balance partitioning problem. This new algorithm is applied to 2 synthetic numerical examples as well as to several real-world data sets from the behavioral sciences literature. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Sell decision: Implications for psychological assessment and treatment.

This article describes 2 important practice considerations affirmed in the U.S. Supreme Court's Sell v. United States (2002) decision: (a) the importance of providing least restrictive services prior to interventions that violate patients' liberty interests, and (b) contextual and environmental factors may be considered in clinical determinations of dangerousness. The psychological treatment of behavior disorders fall within the purview of least restrictive or intrusive interventions compared with the involuntary administration of psychoactive medications. To legitimately comply with the least restrictive criterion, the provision of psychological services is essential. This long-held criterion is rarely acknowledged today as providers use restricted service arrays and attempt to resolve complex and co-occurring behavior problems with medications and restraints. Less restrictive psychological interventions are required for effective treatment of challenging behaviors. A 2nd significant implication lies in the court's affirmation that it is legitimate to consider contextual factors such as history and current environmental conditions in determining dangerousness. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Using "mark sense" for ratings and personal data collection.

The use of IBM "mark sense" cards for data collection, followed by standard machine handling of the punched cards, is described in connection with the analysis of hospital admissions data, correctional school data, ratings analysis, and similar applications. (PsycINFO Database Record (c) 2010 APA, all rights reserved)