Simulated Comparison Data Research Articles

Unicorns, snarks, and personality types: A review of the first 102 taxometric studies of personality

ObjectiveThe default assumption among most psychologists is that personality varies along a set of underlying dimensions, but belief in the existence of discrete personality types persists in some quarters. Taxometric methods were developed to adjudicate between these alternative dimensional and typological models of the latent structure of individual differences. The aim of the present review was to assess the taxometric evidence for the existence of personality types.MethodA comprehensive review yielded 102 articles reporting 194 taxometric findings for a wide assortment of personality attributes.ResultsStructural conclusions differed strikingly as a function of methodology. Primarily older studies that did not assess the fit of observed data to simulated dimensional and typological comparison data drew typological conclusions in 65.2% (60/92) of findings. Primarily newer studies employing simulated comparison data supported the typological model in only 3.9% (4/102) of findings, and these findings were largely in the domain of sexual orientation rather than personality in the traditional sense.ConclusionsIn view of strong Monte Carlo evidence for the validity of the simulated comparison data method, it is highly likely that personality types are exceedingly scarce or non‐existent, and that many early taxometric research findings claiming evidence for such types are spurious.

Stochastic Collision Attack

On the one hand, collision attacks have been introduced in the context of side-channel analysis for attackers who exploit repeated code with the same data without having any knowledge of the leakage model. On the other hand, stochastic attacks have been introduced to recover leakage models of internally processed intermediate secret variables. Both techniques have shown advantages and intrinsic limitations. Most collision attacks, for instance, fail in exploiting all the leakages (e.g., only a subset of matching samples are analyzed), whereas stochastic attacks cannot involve linear regression with the full basis (while the latter basis is the most informative one). In this paper, we present an innovative attacking approach, which combines the flavors of stochastic and collision attacks. Importantly, our attack is derived from the optimal distinguisher, which maximizes the success rate when the model is known. Notably, we develop an original closed-form expression, which shows many benefits by using the full algebraic description of the leakage model. Using simulated data, we show in the unprotected case that, for low noise, the stochastic collision attack is superior to the state of the art, whereas asymptotically and thus, for higher noise, it becomes equivalent to the correlation-enhanced collision attack. Our so-called stochastic collision attack is extended to the scenario where the implementation is protected by masking. In this case, our new stochastic collision attack is more efficient in all scenarios and, remarkably, tends to the optimal distinguisher. We confirm the practicability of the stochastic collision attack thanks to experiments against a public data set (DPA contest v4). Furthermore, we derive the stochastic collision attack in case of zero-offset leakage that occurs in protected hardware implementations and use simulated data for comparison. Eventually, we underline the capability of the new distinguisher to improve its efficiency when the attack multiplicity increases.

Evidence for the continuous latent structure of mania and depression in out-patients with bipolar disorder: results from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD).

Evidence supporting the continuous latent structure of mood phenomena has not been incorporated into psychiatric diagnostic systems, in part because the evidence has been incomplete. For example, no studies have investigated the boundary between 'sick' and 'well' periods in individuals with bipolar disorder, despite agreement that characterization of mood disorders as having a discrete episodic course is inaccurate. The present study examined the validity of mood episode symptom thresholds in out-patients with bipolar disorder using multiple methodologies: taxometrics and information-theoretic latent distribution modeling (ITLDM), to evaluate the continuity/discontinuity of mood symptoms; and structural equation mixture modeling (SEMM), to evaluate the continuity/discontinuity of associations between mood symptoms and general functioning. A total of 3721 out-patients with bipolar disorder from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) were available for analysis. Data were collected at participants' baseline STEP-BD visit. Taxometric [maximum covariance/means above minus below a cut (MAXCOV/MAMBAC) with simulated comparison data], ITLDM and SEMM methods were applied twice, once to the Montgomery-Åsberg Depression Rating Scale and again to the Young Mania Rating Scale. Taxometric results unequivocally supported a continuous interpretation of the data. ITLDM results favored many valued 'discrete metrical' models, suggesting that mood symptoms have continuous, but potentially non-normally distributed, latent structures in out-patients with bipolar disorder. Finally, SEMM results demonstrated that latent associations between mood symptoms and general functioning were linear. Results from the present study argue against the validity of DSM mood episode thresholds and argue for a graded continuum of care of bipolar symptom management.

The latent structure of depression among Chinese: A taxometric analysis in a nationwide urban sample.

The latent structure of psychopathology is one of the fundamental issues in psychopathology research and one which has caused considerable and prolonged debate. To determine the latent structure of depression in the Chinese population, taxometric procedures were used to evaluate the latent structure of depressive symptoms as assessed using the Center for Epidemiologic Studies Depression Scale (CES-D). Four indicators were included: (1) depressed mood, (2) positive affect, (3) somatic, and (4) interpersonal symptoms. Participants were 6,132 individuals from a general population-based nationwide urban sample. We applied three taxometric analyses: mean above minus below a cut, maximum eigenvalue, and latent mode as well as simulated comparison data analyses to depression data. Results of the analyses provided converging evidence for a dimensional solution. Hence, the latent structure of depressive symptoms measured using the CES-D exists on a continuum rather than as discrete categories. Future studies using thresholds for dichotomizing depression and comparing depressed and nondepressed groups formed on the basis of CES-D scores could be reconsidered.

Categories versus dimensions in personality and psychopathology: a quantitative review of taxometric research

Taxometric research methods were developed by Paul Meehl and colleagues to distinguish between categorical and dimensional models of latent variables. We have conducted a comprehensive review of published taxometric research that included 177 articles, 311 distinct findings and a combined sample of 533 377 participants. Multilevel logistic regression analyses have examined the methodological and substantive variables associated with taxonic (categorical) findings. Although 38.9% of findings were taxonic, these findings were much less frequent in more recent and methodologically stronger studies, and in those reporting comparative fit indices based on simulated comparison data. When these and other possible confounds were statistically controlled, the true prevalence of taxonic findings was estimated at 14%. The domains of normal personality, mood disorders, anxiety disorders, eating disorders, externalizing disorders, and personality disorders (PDs) other than schizotypal yielded little persuasive evidence of taxa. Promising but still not definitive evidence of psychological taxa was confined to the domains of schizotypy, substance use disorders and autism. This review indicates that most latent variables of interest to psychiatrists and personality and clinical psychologists are dimensional, and that many influential taxonic findings of early taxometric research are likely to be spurious.

Comparison of GPS strain rate computing methods and their reliability

Using modelled and simulated data for comparison of several methods to compute GPS strain rate fields in terms of their precision and robustness reveals that least-squares collocation is superior. Large scale (75°E–135°E and 20°N–50°N) analyses of 1° grid sampling data and decimated 50 per cent data by resampling (then erasing data in two 5°× 10° region) reveal that the Delaunay method has poor performance and that the other three methods show high accuracy. The correlation coefficients between theoretical results and calculated results obtained with different errors in input data show that the order in terms of robustness, from good to bad, is least-squares collocation, spherical harmonics, multisurface function and the Delaunay method. The influence of data sparseness on different methods shows that least-squares collocation is better than spherical harmonics and multisurface function when sample data are distributed from a 2° grid to a 1° grid. Analysis to medium scale (90°E–120°E, 25°N–40°N) in 1°–0.5° grid sampling data reveals that least-squares collocation is superior to other methods in terms of robustness and sensitivity to data sparseness, but their difference is slight. Strain rate results obtained for the Chinese mainland using GPS data from 1999 to 2004 show that the spherical harmonics method has edge effects and that its value and range increase concomitantly with increased sparseness. The multisurface function method shows non-steady-state characteristics; the errors of results increase concomitantly with increased sparseness. The least-squares collocation method shows steady characteristics. The errors of results show no significant increase even though 50 per cent of input data are decimated by resampling. The spherical harmonics and multisurface function methods are affected by the geometric distribution of input data, but the least-squares collocation method is not.

Latent structure of aversion: Taxometric exploration

Recent research has identified specific disorders that appear to be better characterized by the experience of aversion, rather than anxiety, which evolve from disgust-related affect. Three mathematically distinct taxometric procedures – MAXEIG, MAMBAC, and L-Mode – were applied to data from a large undiagnosed sample ( N = 909) to determine whether aversion forms a distinct psychopathological category (i.e., an aversion taxon). Aversion was operationalized with self-report measures of the frequency of disgust experiences (Disgust Propensity), the perceived emotional impact of disgust experiences (Disgust Sensitivity), and contamination ideation and excessive washing (Contamination Fear). The collective results across procedures, consistency tests, and analysis of simulated comparison data produced converging evidence in support of the conclusion that the latent structure of aversion is dimensional. Implications of these findings for the clinical assessment of aversion and its disorders are discussed.

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.

A taxometric investigation of the latent structure of social anxiety disorder in outpatients with anxiety and mood disorders

The latent structure of social phobia was examined in a sample of 2,035 outpatients with anxiety and mood disorders to determine whether the disorder operates in a categorical or dimensional fashion. We performed three mathematically distinct taxometric procedures-MAMBAC, MAXEIG, and L-Mode-using five indicators constructed from clinical interview ratings and questionnaire measures of social anxiety symptoms. Results from screening analyses and simulated comparison data consistently indicated that the data were suitable for taxometric analysis. The collective results across procedures, consistency tests, and analysis of simulated comparison data produced converging evidence in support of the conclusion that the latent structure of social phobia is dimensional.

Modelling the correlation between the activities of adjacent genes in drosophila

BackgroundCorrelation between the expression levels of genes which are located close to each other on the genome has been found in various organisms, including yeast, drosophila and humans. Since such a correlation could be explained by several biochemical, evolutionary, genetic and technological factors, there is a need for statistical models that correspond to specific biological models for the correlation structure.ResultsWe modelled the pairwise correlation between the expressions of the genes in a Drosophila microarray experiment as a normal mixture under Fisher's z-transform, and fitted the model to the correlations of expressions of adjacent as well as non-adjacent genes. We also analyzed simulated data for comparison. The model provided a good fit to the data. Further, correlation between the activities of two genes could, in most cases, be attributed to either of two factors: the two genes both being active in the same age group (adult or embryo), or the two genes being in proximity of each other on the chromosome. The interaction between these two factors was weak.ConclusionsCorrelation between the activities of adjacent genes is higher than between non-adjacent genes. In the data we analyzed, this appeared, for the most part, to be a constant effect that applied to all pairs of adjacent genes.

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.

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.