Self-report measures of adult attachment are typically scored in ways (e.g., averaging or summing items) that can lead to erroneous inferences about important theoretical issues, such as the degree of continuity in attachment security and the differential stability of insecure attachment patterns. To determine whether existing attachment scales suffer from scaling problems, the authors conducted an item response theory (IRT) analysis of 4 commonly used self-report inventories: Experiences in Close Relationships scales Attachment theory is being used by an increasing number of researchers as a framework for investigating adult psychological dynamics. For instance, many researchers use this framework to study the continuity of close-relationship patterns over time

Construct explication through factor or components analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In

This article examined evidence for dimensional and typological models of dissociation. The authors reviewed previous research with the Dissociative Experiences Scale (DBS; E. B. Bernstein-Carlson & F. W. Putnam, 1986) and note that this scale, like other dissociation questionnaires, was developed to measure that socalled dissociative continuum. Next, recently developed taxometric methods for distinguishing typological from dimensional constructs are described and applied to DBS item-response data from 228 adults with diagnosed multiple personality disorder and 228 normal controls. The taxometric findings empirically justify the distinction between two types of dissociative experiences. Nonpathological dissociative experiences are manifestations of a dissociative trait, whereas pathological dissociative experiences are manifestations of a latent class variable. The taxometric findings also indicate that there are two types of dissociators. Individuals in the pathological dissociative class (taxon) can be identified with a brief, 8-item questionnaire called the DES-T. Scores on the DES-T and DBS are compared in 11 clinical and nonclinical samples. It is concluded that the DES-T is a sensitive measure of pathological dissociation, and the implications of these taxometric results for the identification, treatment, and understanding of multiple personality disorder and allied pathological dissociative states are discussed. In his original formulation of the construct, Pierre Janet (1889) viewed clinical dissociation as a discontinuity in awareness that is rarely experienced by healthy individuals (Perry & Laurence, 1984). His

In this review, we examine studies that use item response theory (IRT) to explore the psychometric properties of clinical measures. Next, we consider how IRT has been used in clinical research for: scale linking, computerized adaptive testing, and differential item functioning analysis. Finally, we consider the scale properties of IRT trait scores. We conclude that there are notable differences between cognitive and clinical measures that have relevance for IRT modeling. Future research should be directed toward a better understanding of the metric of the latent trait and the psychological processes that lead to individual differences in item response behaviors.

This article reviews methodological issues that arise in the application of exploratory factor analysis (EFA) to scale revision and refinement. The authors begin by discussing how the appropriate use of EFA in scale revision is influenced by both the hierarchical nature of psychological constructs and the motivations underlying the revision. Then they specifically address (a) important issues that arise prior to data collection (e.g., selecting an appropriate sample), (b) technical aspects of factor analysis (e.g., determining the number of factors to retain), and (c) procedures used to evaluate the outcome of the scale revision (e.g., determining whether the new measure functions equivalently for different populations).

Because structural equation modeling (SEM) has become a very popular data-analytic technique, it is important for clinical scientists to have a balanced perception of its strengths and limitations. We review several strengths of SEM, with a particular focus on recent innovations (e.g., latent growth modeling, multilevel SEM models, and approaches for dealing with missing data and with violations of normality assumptions) that underscore how SEM has become a broad data-analytic framework with flexible and unique capabilities. We also consider several limitations of SEM and some misconceptions that it tends to elicit. Major themes emphasized are the problem of omitted variables, the importance of lower-order model components, potential limitations of models judged to be well fitting, the inaccuracy of some commonly used rules of thumb, and the importance of study design. Throughout, we offer recommendations for the conduct of SEM analyses and the reporting of results.

Taxometric and biometric analyses were conducted on 2 North American samples to investigate the prevalence and biometric structure of pathological dissociation. Results indicated that approximately 3.3% of the general population belongs to a pathological dissociative taxon. A brief 8-item self-report scale called the DES-T can be used to calculate taxon membership probabilities in clinical and nonclinical samples of adults (a SAS scoring program is provided for this purpose). The genetic and environmental architecture of pathological dissociative symptoms was explored by conducting a biometric analysis on DES-T ratings from 280 identical and 148 fraternal twins. The findings suggest that approximately 45% of the observed variance on the DES-T can be attributed to shared environmental influences. The remaining variance is due to nonshared environmental influences.

The assessment of model fit is a more complex and indeterminate process than is commonly acknowledged by researchers who use structural equation modeling (SEM) techniques. Even models that are well fitting according to commonly used statistical tests and descriptive fit indices can have significant problems and ambiguities. The authors discuss 7 potential difficulties that can arise and that should temper researchers' conclusions: equivalent models, nonequivalent but well-fitting alternative models, omitted variables, problematic lower-order model components, the failure to parse composite models into meaningful partitions (e.g., measurement vs. structural), inattention to the multiple factors that affect the sensitivity of measures of fit to model misspecifications, and reliance on specification searches. In addition to providing examples of each of these problems, the authors offer recommendations for psychopathologists who conduct SEM analyses.