Taxometric analysis supports a dimensional latent structure for schizotypy

The existence of a discrete class of people vulnerable to schizophrenia spectrum disorders is the most replicated finding of taxometric research. Evidence for such a “taxon” has been obtained with diverse measures of schizotypy in clinical, high-risk, and normal samples. However, recent demonstrations that skewed indicators of a latent dimension can yield a spuriously taxonic pattern of results may call some of these findings into question. Normal adults (N = 1073) completed measures of positive (perceptual aberration, magical ideation) and negative (physical and social anhedonia) components of schizotypy. Taxometric curves resembled those obtained previously, but when a simulation procedure took skew into account, dimensional models of schizotypy received stronger support than taxonic models for most schizotypy components, with findings for magical thinking inconclusive. A re-evaluation of previous taxonic conclusions regarding the latent structure of schizotypy is indicated.     

Detecting latent taxa: Monte Carlo comparison of taxometric, mixture model, and clustering procedures

A Monte Carlo evaluation of four procedures for detecting taxonicity was conducted using artificial data sets that were either taxonic or nontaxonic. The data sets were analyzed using two of Meehl's taxometric procedures, MAXCOV and MAMBAC, Ward's method for cluster analysis in concert with the cubic clustering criterion and a latent variable mixture modeling technique. Performance of the taxometric procedures and latent variable mixture modeling were clearly superior to that of cluster analysis in detecting taxonicity. Applied researchers are urged to select from the better procedures and to perform consistency tests.     

Is schizotypy taxonic? Response to

Beauchaine, Lenzenweger, and Waller (2008) criticize our taxometric study of schizotypy (Rawlings, Williams, Haslam, & Claridge, in press) on a variety of methodological and philosophical grounds. We argue that their critique selectively applies more stringent standards to our work than to studies supporting their view that schizotypy is taxonic (i.e., categorical). Many of their criticisms apply at least equally to existing studies that offer support for a schizotypy taxon, and these studies are vulnerable to biases favouring taxonic conclusions that were controlled for in our study. Contrary to their criticisms, we did not claim to have disconfirmed previous taxonic findings about schizotypy, and our findings positively support dimensional models of schizotypy rather than merely being null results. Similarly, our findings are not artefacts of the sampling or measurement decisions that they question. Even well-replicated taxometric findings are not immune to empirical challenge, and evaluation of such challenges must be even-handed.     

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.     

Does attention-deficit/hyperactivity disorder have a dimensional latent structure? A taxometric analysis

An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667 and 1,078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD.     

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.     

Between-group differences and taxometrics

In psychological research it can be of interest to differentiate between the categorical (taxonic) vs dimensional (nontaxonic) nature of phenomena, for example in the field of psychopathology. For categorical (taxonic) structures a further differentiation is possible: between categorical structures with dimensional equivalence and a substantial main effect, and structures without dimensional equivalence (independent of the main effect). Previous taxometric studies have not concentrated in an explicit way on the case of nonequivalence. It is shown here that under favorable circumstances both types of categorical structures can be detected using the taxometric procedure L-Mode, but that they cannot be differentiated from one another.     

Anxiety sensitivity taxonicity across gender among youth

The present investigation comparatively evaluated the latent class structure and parameters of anxiety sensitivity (AS) among female and male youth using the Childhood Anxiety Sensitivity Index. Participants were 4462 adolescents (2189 females) in grades 7-12 (M(age)=15.6 years). Consistent with prediction, taxometric analyses indicated the latent structure of AS was taxonic in both males and females, demonstrating the taxonic latent structure of AS is similarly observed across gender. Also consistent with prediction, the base rate of the AS taxon differed between genders -- higher for females (12%) compared to males (7%). These findings are discussed in terms of their implications for the study of AS and panic vulnerability among youth.     

Applying the Bootstrap to Taxometric Analysis: Generating Empirical Sampling Distributions to Help Interpret Results

Meehl's taxometric method was developed to distinguish categorical and continuous constructs. However, taxometric output can be difficult to interpret because expected results for realistic data conditions and differing procedural implementations have not been derived analytically or studied through rigorous simulations. By applying bootstrap methodology, one can generate empirical sampling distributions of taxometric results using data–based estimates of relevant population parameters. We present iterative algorithms for creating bootstrap samples of taxonic and dimensional comparison data that reproduce important features of the research data with good precision and negligible bias. In a series of studies, we demonstrate the utility of these comparison data as an interpretive aid in taxometric research. Strengths and limitations of the approach are discussed along with directions for future research.     

Somatic symptom reporting has a dimensional latent structure: Results from taxometric analyses

Medically unexplained symptoms (MUS) are one of the key features of somatoform disorders. Although MUS are currently treated as both categorical (in terms of the diagnosis of somatoform disorders) and dimensional (in terms of quantitative measures of somatization/somatic symptom reporting), little is known about the empirical latent structure of MUS. Using taxometric analyses, the latent structure of somatic symptom reporting was analyzed with the Patient Health Questionnaire (PHQ)-15 in two student samples (N = 782 and N = 2,577) and a primary care sample (N = 519). We applied three popular taxometric methods: Maximum Eigenvalue (MAXEIG), Mean Above Minus Below a Cut (MAMBAC) and Latent-Mode (L-Mode). Simulation data were created to evaluate the appropriateness of the data for our analyses and to create the comparison curve fit index (CCFI) as an objective outcome measure. The results of all taxometric methods in any of the three data sets were in favor of a dimensional solution (CCFI < .50). Simulated taxonic and dimensional datasets differed substantially and the samples were appropriate for taxometric analysis. Accordingly, the latent structure of somatization/somatic symptom reporting as assessed by the PHQ-15 is dimensional in both primary care and student samples. Implications regarding the practical application as well as models of etiology and pathogenesis of somatic symptom reporting are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved).     

Type or dimension? A taxometric investigation of flashbulb memories

Flashbulb memories (FBMs) have been defined as vivid and detailed memory of a reception context under which one first heard of a public and unexpected emotional event. One of the issues still open for research on FBMs is to understand whether this latent construct has to be conceptualised as a continuum with other autobiographical memories, or whether it represents a special cluster of memories. This theoretical distinction has some implications for the measurement of the phenomenon, that could be assessed by a dimensional or categorical (taxonic) model. The current study attempted to provide an empirical answer to the problem of FBM measurement, by adopting a taxometric analysis. The main strength of these analyses is to treat taxonic and dimensional models as two competing hypotheses and to evaluate the relative support for each of them. Taxometric analyses were applied to FBM data for the Pope's death, and results supported the taxonic structure of FBMs.     

Type or dimension? A taxometric investigation of flashbulb memories

Flashbulb memories (FBMs) have been defined as vivid and detailed memory of a reception context under which one first heard of a public and unexpected emotional event. One of the issues still open for research on FBMs is to understand whether this latent construct has to be conceptualised as a continuum with other autobiographical memories, or whether it represents a special cluster of memories. This theoretical distinction has some implications for the measurement of the phenomenon, that could be assessed by a dimensional or categorical (taxonic) model. The current study attempted to provide an empirical answer to the problem of FBM measurement, by adopting a taxometric analysis. The main strength of these analyses is to treat taxonic and dimensional models as two competing hypotheses and to evaluate the relative support for each of them. Taxometric analyses were applied to FBM data for the Pope's death, and results supported the taxonic structure of FBMs.     

Assigning cases to groups using taxometric results: an empirical comparison of classification techniques

Determining whether individuals belong to different latent classes (taxa) or vary along one or more latent factors (dimensions) has implications for assessment. For example, no instrument can simultaneously maximize the efficiency of categorical and continuous measurement. Methods such as taxometric analysis can test the relative fit of taxonic and dimensional models, but it is not clear how best to assign individuals to groups using taxometric results. The present study compares the performance of two classification techniques-Bayes' theorem and a base-rate technique--across a wide range of data conditions. The base-rate technique achieves greater classification accuracy and a more even balance between sensitivity and specificity. In addition, the base-rate classification technique is easier to implement than Bayes' theorem and is more versatile in that it can be used when the context of assessment requires that cases be classified despite the absence of latent classes.     

A taxometric analysis of actual Internet sports gambling behavior

This article presents findings from the first taxometric study of actual gambling behavior to determine whether we can represent the characteristics of extreme gambling as qualitatively distinct (i.e., taxonic) or as a point along a dimension. We analyzed the bets made during a 24-month study period by the 4,595 most involved gamblers among a cohort of 48,114 people using an Internet service to gamble on sporting events. We applied two taxometric procedures (i.e., MAMBAC and MAXCOV) to three indicators of betting behavior: total money lost, total number of bets, and total money wagered. The results fail to provide support for the view that the most involved Internet sports gamblers include a distinct category of gamblers. More research is necessary to clarify the similar features of recreational and extreme gamblers and the dimensions that scientists can use to measure these behaviors. Finally, we discuss the implications of these findings for clinical, research, and public policy activities.     

Hedonic capacity and schizotypy revisited: a taxometric analysis of social anhedonia

P. E. Meehl (1962) originally conjectured that hedonic capacity was an indicator of the latent class or taxon of schizotypy. However, P. E. Meehl (1989, 1990) subsequently diminished the role of hedonic capacity in his theory, indicating that hypohedonia is one of a dozen normal-range (nontaxonic) individual-differences factors that may potentiate the expression of schizophrenia. This dimensional-only view of hedonic capacity was tested by applying taxometric procedures to the Revised Social Anhedonia Scale (RSAS; M. L. Eckblad, L. J. Chapman, J. P. Chapman, & M. Mishlove, 1982) in a sample of college students (N = 1,526). Analyses indicated that the construct measured by the RSAS is taxonic in nature with a base rate approximating .10. These data are interpreted in the context of other findings suggesting that social anhedonia is an indicator of schizotypy.     

The maxslope taxometric procedure: mathematical derivation, parameter estimation, consistency tests

This article first explains concepts in taxometrics, including the meaning of "taxon" in relation to taxometric procedures. It then mathematically develops the MAXSLOPE procedure of Grove and Meehl which relies on nonlinear regression of one taxometric indicator variable on another. Sufficient conditions for MAXSLOPE's validity are set forth. The relationship between the point of maximum regression slope (MAXSLOPE point) and the HITMAX cut, i.e., the point on a variable which, if used as a diagnostic cut-off score, yields maximum classification accuracy, is analyzed. A sufficient condition is given for the MAXSLOPE point to equal the HITMAX cut; however, most distributions have different MAXSLOPE and HITMAX points. Equations and an algorithm are spelled out for making a graphical test for the existence of a taxon, estimating taxometric parameters, and conducting consistency tests; the latter serve as stringent checks on the validity of a taxonic conjecture. The plausibility of assumptions made, in deriving MAXSLOPE equations, is discussed, and the qualitative effects of violations of these assumptions are explained.     

Malingering as a categorical or dimensional construct: the latent structure of feigned psychopathology as measured by the SIRS and MMPI-2

The 6 nonoverlapping primary scales of the Structured Interview of Reported Symptoms (SIRS) were subjected to taxometric analysis in a group of 1,211 criminal and civil examinees in order to investigate the latent structure of feigned psychopathology. Both taxometric procedures used in this study, mean above minus below a cut (MAMBAC) and maximum covariance (MAXCOV), produced dimensional results. A subgroup of participants (n = 711) with valid Minnesota Multiphasic Personality Inventory-2 (MMPI-2) protocols were included in a second round of analyses in which the 6 nonoverlapping primary scales of the SIRS and the Infrequency (F), Infrequency-Psychopathology (Fp), and Dissimulation (Ds) scales of the MMPI-2 served as indicators. Again, the results were more consistent with dimensional latent structure than with taxonic latent structure. On the basis of these findings, it is concluded that feigned psychopathology forms a dimension (levels of fabrication or exaggeration) rather than a taxon (malingering-honest dichotomy) and that malingering is a quantitative distinction rather than a qualitative one. The theoretical and clinical practice implications of these findings are discussed.     

The Behavioral Approach System (BAS) Model of Vulnerability to Bipolar Disorder: Evidence of a Continuum in BAS Sensitivity across Adolescence

Behavioral Approach System (BAS) sensitivity has been implicated in the development of a variety of different psychiatric disorders. Prominent among these in the empirical literature are bipolar spectrum disorders (BSDs). Given that adolescence represents a critical developmental stage of risk for the onset of BSDs, it is important to clarify the latent structure of BAS sensitivity in this period of development. A statistical approach especially well-suited for delineating the latent structure of BAS sensitivity is taxometric analysis, which is designed to evaluate whether the latent structure of a construct is taxonic (i.e., categorical) or dimensional (i.e., continuous) in nature. The current study applied three mathematically non-redundant taxometric procedures (i.e., MAMBAC, MAXEIG, and L-Mode) to a large community sample of adolescents (n = 12,494) who completed two separate measures of BAS sensitivity: the BIS/BAS Scales Carver and White (Journal of Personality and Social Psychology, 67, 319–333. 1994) and the Sensitivity to Reward and Sensitivity to Punishment Questionnaire (Torrubia et al. Personality and Individual Differences, 31, 837–862. 2001). Given the significant developmental changes in reward sensitivity that occur across adolescence, the current investigation aimed to provide a fine-grained evaluation of the data by performing taxometric analyses at an age-by-age level (14–19 years; n for each age ≥ 883). Results derived from taxometric procedures, across all ages tested, were highly consistent, providing strong evidence that BAS sensitivity is best conceptualized as dimensional in nature. Thus, the findings suggest that BAS-related vulnerability to BSDs exists along a continuum of severity, with no natural cut-point qualitatively differentiating high- and low-risk adolescents. Clinical and research implications for the assessment of BSD-related vulnerability are discussed.     

Is perfectionism categorical or dimensional? A taxometric analysis

Considerable debate exists within the perfectionism literature regarding whether perfectionism is most accurately conceptualized as a dimensional or categorical construct. Specifically, some researchers have viewed perfectionism as a continuous construct, with extreme scores being associated with negative psychological outcomes (e.g., obsessive-compulsive disorder, eating disorders, etc.). In contrast, others have argued that two distinct forms of perfectionism exist (i.e., adaptive vs. maladaptive perfectionism) that are associated with both positive and negative outcomes. The purpose of this study was to examine the latent structure of perfectionism using taxometric procedures to determine whether perfectionism is most accurately conceptualized as taxonic (categorical) or dimensional (continuous). We applied four taxometric procedures (maximum eigenvalue [Waller & Meehl, 1998], maximum covariance [Meehl & Yonce, 1996], mean above minus below a cut [Meehl & Yonce, 1994], and latent-mode factor analysis [Waller & Meehl, 1998]) to perfectionism data collected from 2 large nonclinical samples. Results provided convergent evidence for a dimensional conceptualization of perfectionism across samples, perfectionism measures, and statistical procedures. We discuss the implications of these findings for the theory, assessment, and investigation of perfectionism are discussed.     

The latent structure and coincidence of hypohedonia and schizotypy and their validity as indices of psychometric risk for schizophrenia

Recent exchanges on the place of hypohedonia within Meehl's theory of schizotaxia, schizotypy, and schizophrenia focus on evidence of the taxonicity of asociality, not hedonic capacity per se. Two hypotheses were contrasted, one that hypohedonia is a nonpathological individual difference variable independent of schizotypy, the other that schizotypy and hypohedonia tap independent taxonic processes that predict the emergence of positive and negative signs of schizophrenia, respectively. Undergraduates (n = 1,543) completed a multifaceted measure of schizotypy and hypohedonia. A consecutive subsample of these (n = 284) also completed a continuous performance test and the Symptom Checklist 90-Revised. Independent taxometric analyses (maximum covariance and maximum eigenvalue) indicated schizotypy was taxonic and hypohedonia was dimensional. Their coincidence was no greater than chance. Schizotypy was associated with impaired attention and significant psychological distress, whereas hypohedonia was not. Hypohedonia does not behave like a core component of schizotypy.