Using Taxometric Analysis to Distinguish a Small Latent Taxon From a Latent Dimension With Positively Skewed Indicators: The Case of Involuntary Defeat Syndrome.

Joining the debate on the structure of depression, S. R. H. Bearh and N. Amir (2003) analyzed college students' responses to 6 Beck Depression Inventory (BDI) items with predominantly somatic content and concluded that they identified a small latent taxon corresponding to involuntary defeat syndrome. An exact replication of these analyses yielded virtually identical taxometric results, but parallel analyses of simulated taxonic and dimensional comparison data matching the intercorrelations and skewed distributions of the BDI items showed the results to be more consistent with dimensional than with taxonic latent structure. Analyses in a clinical sample with nonskewed indicators further supported a dimensional interpretation. The authors discuss methodological strategies for conducting and interpreting taxometric analyses under the adverse conditions commonly encountered in psychopathology research, including skewed indicators and small putative taxa. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Using comparison data to differentiate categorical and dimensional data by examining factor score distributions: Resolving the mode problem.

Factor-analytic research is common in the study of constructs and measures in psychological assessment. Latent factors can represent traits as continuous underlying dimensions or as discrete categories. When examining the distributions of estimated scores on latent factors, one would expect unimodal distributions for dimensional data and bimodal or multimodal distributions for categorical data. Unfortunately, identifying modes is subjective, and the operationalization of counting local maxima has not performed very well. Rather than locating and counting modes, the authors propose performing parallel analyses of categorical and dimensional comparison data and calculating an index of the relative fit of these competing structural models. In an extensive Monte Carlo study, the authors replicated prior results for mode counting and found that trimming distributions' tails helped. However, parallel analyses of comparison data achieved much greater accuracy, improved base rate estimation, and afforded consistency checks with other taxometric procedures. Two additional studies apply this approach to empirical data either known to be categorical or presumed to be dimensional. Each study supports this new method for factor-analytic research on the latent structure of constructs and measures in psychological assessment. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Comparing the relative fit of categorical and dimensional latent variable models using consistency tests.

A number of recent studies have used Meehl’s (1995) taxometric method to determine empirically whether one should model assessment-related constructs as categories or dimensions. The taxometric method includes multiple data-analytic procedures designed to check the consistency of results. The goal is to differentiate between strong evidence of categorical structure, strong evidence of dimensional structure, and ambiguous evidence that suggests withholding judgment. Many taxometric consistency tests have been proposed, but their use has not been operationalized and studied rigorously. What tests should be performed, how should results be combined, and what thresholds should be applied? We present an approach to consistency testing that builds on prior work demonstrating that parallel analyses of categorical and dimensional comparison data provide an accurate index of the relative fit of competing structural models. Using a large simulation study spanning a wide range of data conditions, we examine many critical elements of this approach. The results provide empirical support for what marks the first rigorous operationalization of consistency testing. We discuss and empirically illustrate guidelines for implementing this approach and suggest avenues for future research to extend the practice of consistency testing to other techniques for modeling latent variables in the realm of psychological assessment. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The role of complex thought in clinical prediction: Social accountability and the need for cognition.

Research shows that clinical predictions are less accurate than statistical predictions and are held with unreasonable confidence. Because there are obstacles to the implementation of statistical prediction, factors that improve clinical judgment must be identified. One hundred twelve individuals participated in an experiment investigating the role of complex thought in clinical prediction. Results revealed marked performance differences related to the amount of available clinical information. Participants' assessed need for cognition was associated with their consistency, accuracy, and cue-weighting strategies. Social accountability improved confidence performance under certain task conditions but was unrelated to accuracy. Theoretical and practical implications of these results are discussed, with emphasis on the restructuring of tasks and the selection and training of human forecasters to promote accurate and appropriately confident clinical predictions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The latent structure of analogue depression: Should the Beck Depression Inventory be used to classify groups?

Research on depression is often conducted with analogue samples that have been divided into depressed and nondepressed groups using a cutoff score on the Beck Depression Inventory (BDI). Although the relative merits of different cut scores are frequently debated, no study has yet determined whether the use of any cut score is valid, that is, whether the latent structure of BDI depression is categorical or dimensional in analogue samples. The BDI responses of 2,260 college students were submitted to 3 taxometric procedures whose results were compared with those of simulated data sets with equivalent parameters. Analyses provided converging evidence for the dimensionality of analogue depression, arguing against the use of the BDI to classify analogue participants into groups. Analyses also illustrated the notable impact of pronounced skew on taxometric results and the value of using simulated comparison data as an interpretive aid. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Informing the continuity controversy: A taxometric analysis of depression.

Researchers and practitioners have long debated the structural nature of mental disorders. Until recently, arguments favoring categorical or dimensional conceptualizations have been based primarily on theoretical speculation and indirect empirical evidence. Within the depression literature, methodological limitations of past studies have hindered their capacity to inform this important controversy. Two studies were conducted using MAXCOV and MAMBAC, taxometric procedures expressly designed to assess the underlying structure of a psychological construct. Analyses were performed in large clinical samples with high base rates of major depression and a broad range of depressive symptom severity. Results of both studies, drawing on 3 widely used measures of depression, corroborated the dimensionality of depression. Implications for the conceptualization, investigation, and assessment of depression are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Detecting small taxa using simulated comparison data: A reanalysis of Beach, Amir, and Bau's (2005) data.

On the basis of taxometric analyses of data sets that they created to pose interpretive challenges, S. R. H. Beach, N. Amir, and J. J. Bau (2005) cautioned that using comparison data simulated by J. Ruscio's programs can lead to inaccurate conclusions. Careful examination of S. R. H. Beach et al.'s methods and results plus reanalysis of their data fails to substantiate this concern: Using comparison data identified the taxonic structure of S. R. H. Beach et al.'s data sets, even when the taxon base rate was very low. The authors show that J. Ruscio's simulation programs generate comparison data appropriately and that analyzing these data provides a useful interpretive aid. Additionally, the authors discuss and illustrate the effective use of the inchworm consistency test to disambiguate taxometric results for small taxa and dimensional constructs with positively skewed indicators. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The latent structure of posttraumatic stress disorder: A taxometric investigation of reactions to extreme stress.

Mental health professionals have debated whether posttraumatic stress disorder (PTSD) can be qualitatively distinguished from normal reactions to traumatic events. This debate has been fueled by indications that many trauma-exposed individuals evidence partial presentations of PTSD that are associated with significant impairment and help-seeking behavior. The authors examined the latent structure of PTSD in a large sample of male combat veterans. Three taxometric procedures--MAMBAC, MAXEIG, and L-Mode--were performed with 3 indicator sets drawn from a clinical interview and a self-report measure of PTSD. Results across procedures, consistency tests, and analysis of simulated comparison data all converged on a dimensional solution, suggesting that PTSD reflects the upper end of a stress-response continuum rather than a discrete clinical syndrome. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Correction to: Evaluation of a machine learning classifier for metamodels

Software and Systems Modeling -     

具有创新意义的达涅利动态自调节电弧炉

达涅利开发的由多个模块组成的DanExpert电炉成套控制系统,在过程状态出现任何变化时,均可实时动态更新设定值,从而可通过改善电炉运行稳定性,提高设备生产能力,降低生产成本.