Mean Above Minus Below A Cut Research Articles

Understanding the Latent Structure of Hypersexuality: A Taxometric Investigation.

We examined the latent structure and taxonicity of hypersexuality in large university and community samples of male and female respondents. Participants completed the Hypersexual Behavior Inventory (HBI) and Sexual Compulsivity Scale (SCS), each as part of larger anonymous online surveys of sexual behavior. Exploratory factor analyses (EFA) were performed in part to prepare the data for taxometric analysis and also to identify the putative dimensions underpinning each measure. Three latent dimensions were identified from each of the Sexual Compulsivity Scale (dyscontrol, consequences, and preoccupation) and Hypersexual Behavior Inventory (coping, dyscontrol, and consequences). Taxometric analyses of the generated factors using mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent mode factor analysis (L-Mode) broadly supported a dimensional latent structure for hypersexuality, particularly in female participants. Implications pertaining to the assessment of hypersexuality are discussed.

Child molestation and psychopathy: a taxometric analysis

ABSTRACTPrior taxometric research on child molesters and general sex offenders has produced inconsistent and contradictory results. There are theoretical, practical, and policy reasons, however, to assume that a psychopathy taxon may exist in sex offenders and that a taxometric study might shed light on this issue. The mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent-mode factor analysis (L-Mode) taxometric procedures were employed in three overlapping samples: 188 sex offenders with non-relative child victims, 555 sex offenders with non-relative child or adolescent victims or child incest victims, and a mixed sample of 1404 sex offenders. The taxometric analyses revealed evidence of continuous latent structure in all three samples. These results suggest that psychopathy in sex offenders, child molesters in particular, is organised quantitatively (continuous) rather than qualitatively (categorical).

The latent structure of alcohol misuse in young adults: Do taxometric results differ as a function of prior criminal history?

BackgroundThe purpose of this study was to determine whether the latent structure of alcohol misuse is categorical or continuous in male and female adults with and without a history of prior criminal offending. MethodsData from 3452 (1530 male, 1922 female) 27-to-32 year old members of the National Longitudinal Study of Adolescent to Adult Health (Add Health) were subjected to taxometric analysis using three nonredundant taxometric procedures—mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent mode factor analysis (L-Mode). ResultsAnalyses produced results consistent with categorical latent structure in males with a previous history of criminal offending but not in males without a previous history of criminal offending or females with or without a history of criminal offending. The findings from the other groups were indeterminate for the most part (i.e., neither categorical nor continuous). The presumptive taxon was validated by testing differences in age of onset and frequency of criminal arrest and drunkenness between the putative taxon and the upper portion of the complement. As predicted, all four validation outcomes were significantly worse in the taxon group. ConclusionsOn the basis of these results it is concluded that alcohol misuse in young adults may have features of both categorical and continuous latent structure and that the categorical aspects are more prominent in males with a history of offending behavior. Additional research is required to determine which aspects and features of alcohol misuse are categorical and which aspects and features are continuous.

Latent structure of depression in the elderly: a taxometric analysis

This study aimed to investigate the latent structure of depression with a non-clinical sample of elderly, using taxometric analysis. The latter consists of a family of statistical procedures conceived for testing whether a given psychological construct is best represented by categories or dimensions in which individuals vary. The sample consisted of 570 elderly with a mean age of 71.9 years (SD = 7.45), who answered the Brazilian version of the Geriatric Depression Scale, a cognitive test, and demographic questions. Three taxometric procedures were used: Mean Above Minus Below A Cut (MAMBAC), Maximum Eigenvalue (MAXEIG), and Latent Mode (L-mode). Sets of simulated categorical and dimensional data, along with the comparison curve fit indices (CCFI), oriented the study data's interpretation. The results with the three techniques pointed to a better fit with the dimensional format as opposed to the taxonic one, that is, depression represented better as a syndrome in which subjects are distributed along a continuum rather than as a discrete diagnostic entity.

Paralimbic biomarkers in taxometric analyses of psychopathy: does changing the indicators change the conclusion?

Although psychopathy has consistently been shown to distribute as a dimension, all prior studies have examined behavioral indicators that may be phenotypically distant from core biological correlates of the syndrome. The current studies attempted to determine whether biomarkers from a high-resolution structural MRI scan of selected limbic and paralimbic structures identified the latent structure of psychopathy as continuous. Participants were 254 adult male medium/maximum security inmates (Study 1) and 191 adolescent male maximum security inmates (Study 2) who volunteered to undergo research MRI scans. Indicators of gray matter concentration (GMC) in the adult sample and of gray matter volume (GMV) in the adolescent sample were subjected to taxometric analysis using three nonredundant taxometric procedures: mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent-mode factor analysis (L-Mode). Evidence of continuous latent structure was found across samples (adults, adolescents), measures (GMV, GMC, Psychopathy Checklist-Revised [PCL-R], Psychopathy Checklist: Youth Version [PCL:YV]), and procedures (MAMBAC, MAXCOV, L-Mode). Continuous latent structure was also noted when biomarker (GMV, GMC) and behavioral (PCL) indicators were included in the same analysis. The current results support the view that psychopathy is a quantitative construct on which people differ in degree ("more of" or "less of") rather than a qualitative construct that assigns people to distinct categories ("either/or"). Continued development of the psychopathy construct may depend on our ability to identify, understand, and make effective use of its apparent continuous latent structure.

The Latent Structure of Criminal Persistence: A Taxometric Analysis of Offending Behavior from Late Adolescence to Early Adulthood in Adjudicated Male Delinquents

This study examines the latent structure of offending persistence from late adolescence through early adulthood. Self-reported involvement in drug crimes, person crimes, and property crimes between the ages of 17 and 21 years were analyzed in 1,160 male members of the Pathways to Desistance study (Mulvey, 2012). Scores on the three indicators were subjected to longitudinal (by summing across the five time periods) and cross-sectional (by testing each individual time period) taxometric analysis. Outcomes obtained using the mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent mode factor analysis (L-Mode) taxometric procedures revealed consistent support for continuous latent structure in both the longitudinal and cross-sectional analyses. It would appear that continued criminal involvement beyond adolescence is not an all-or-nothing phenomenon and that it may be more productive to order individuals along a persistence-desistance continuum than assign them to mutually exclusive categories, trajectories, or typologies.

A taxometric analysis of the children’s sleep habits questionnaire

Sleep problems characterized by later bedtimes, insomnia and excessive daytime sleepiness occur in different populations. Sleep problems are highly prevalent, affecting approximately 20–30% of children, and they influence multiple domains of child and family functioning as proven studies using different methods. Sleep problems are connected with many psychiatric disorders, including ADHD, autism, cognitive functioning problems, and behavior problems et al. There is an old important issue in the psychopathology field as to whether the latent construct is dimensional or taxometric. This study examined the latent structure of the sleep problems measured by the Childrens Sleep Habits Questionnaire (CSHQ). Participants We took the cluster-stratified sampling procedure, and chose 4 districts in Shenzhen. In each district, a primary school was chosen, and in each school, one class was chosen in each grade. 950 parents of the selected children participated in the paper-and-pencil survey during parents’ meetings held at the schools between late February and early March in 2011. Finally, we had 912 questionnaires available. The sample population consisted of 912 children aged 6–14 years inclusive, including 495 boys (54.3%), 413 girls (45.3%) and 4 missing values about gender (0.4%), with a mean age of 8.9 years (SD = 1.9). The children were comprised of first through sixth grade and they came from schools in Shenzhen City, which is located in the south of China mainland. The number and the portion of each grade are as follows: the first grade 235 (25.8%), the second grade 135 (14.8%), the third grade 155 (17.0%), the fourth grade 133 (14.6%), the fifth grade 136 (14.9%), and the sixth grade 118 (12.9%). There were 170 missing values in total, and we took the expectation maximization (EM) method to replace them. Measures The CSHQ is a sleep questionnaire for children designed for screening a wide range of sleep problems among school age children. According to recall of a recent typical week, parents rated the occurrence of 33 sleep habits or sleep problems on a 3-point scale:3 = usually (5–7 times/week),2 = sometimes (2–4 times/week),1 = rarely (0–1 times/week). The questionnaire yields a total score and eight subscale scores: Bedtime Resistance, Sleep Onset Delay, Sleep Duration, Sleep Anxiety, Night Wakings, Parasomnias, Sleep Disordered Breathing and Daytime Sleepiness. The higher the score, the more likely to have sleep problems. A total score above 41 is considered to have a serious sleep problem. The CSHQ has demonstrated adequate reliability (coefficient alpha 0.68–0.78, testC¨retest reliability 0.62–0.79) and validity. In this study, we took the Chinese language version of the CSHQ. Reliability (coefficient alpha 0.71) and validity (content and construct) of the Chinese version of CSHQ are good. In order to identify the latent structure of CSHQ, we used three independent taxometric procedures: MAMBAC (mean above minus below a cut), MAXEIG (maximum eigenvalue) and L-Mode (latent-mode factor analysis). We applied three taxometric procedures to analysis our data and used Ruscio’s taxometric R program(http://www.tcnj.edu/∼ruscio/taxometrics.html) to get taxometric plots and ran all calculations. Sleep problems were measured by three main factors£ – we called F1–F3 (bad sleep habit⧹problems about sleep discords⧹problems about sleep time and daynapping). We took three taxometric analysis procedures (MAMBAC⧹MEIGN⧹LMODE) to apply in the latent structure analysis of the CSHQ. Three indicators were used in the taxometric analysis procedures, which have enough wide range and proper Skewness and Kurtosis. The correlations between indicators were around 0.3. Most of the Cohen’s d values except one are larger than 1.25SD, indicating the indicators deemed appropriate for taxometric analysis. The present study indicates that the latent structure of the CSHQ is dimensional. It aids in better understanding of the latent structure of CSHQ-measured sleep problems among Chinese school-aged children. The authors thank the lovely children and their parents and teachers. We also appreciate the efforts of Rui Ma (Nanshan Xuefu Primary School, Shenzhen, China), Lin Lin and her three classmates (Shenzhen University, China) for their help with data collection and entry.

Trajectories of Youthful Antisocial Behavior: Categories or Continua?

The purpose of this study was to determine whether qualitatively distinct trajectories of antisocial behavior could be identified in 1,708 children (843 boys, 865 girls) from the 1979 National Longitudinal Survey of Youth-Child Data (NLSY-C). Repeated ratings were made on the Behavior Problems Index (BPI: Peterson and Zill Journal of Marriage and the Family, 48, 295-307, 1986) antisocial scale by the mothers of these children when the children were 6, 8, 10, 12, and 14years of age. Scores on three indicators constructed from the six BPI Antisocial items (callousness, aggression, noncompliance) were then analyzed longitudinally (by summing across the rating periods) and cross-sectionally (by testing each individual rating period) in the full sample as well as in subsamples of boys and girls. Results obtained with the mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent mode factor analysis (L-Mode) taxometric procedures revealed consistent evidence of continuous latent structure despite the fact Growth Mixture Modeling (GMM) and Latent Class Growth Analysis (LCGA) identified between two and eight trajectories, depending on the stopping rule, in the three antisocial indicators. From these results, it is concluded that the structural model underlying these data is better represented as continuous rather than as categorical. The implications of these results for future research on developmental trajectories of antisocial behavior are discussed.

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.

A Taxometric Analysis of Problem Gambling Data from a South African National Urban Sample

We investigate the question whether problem gambling (PG) in a recent South African sample, as measured by the Problem Gambling Severity Index (PGSI), is dimensional or categorical. We use two taxometric procedures, Mean Above Minus Below A Cut (MAMBAC) and Maxim Covariance (MAXCOV), to investigate the taxonic structure of PG as constructed by the PGSI. Data are from the 2010 South African National Urban Prevalence Study of Gambling Behavior. A representative sample of the urban adult population in South Africa (N = 3,000). Responses are to the 9 item PGSI. MAMBAC provided positive but modest evidence that PG as measured by the PGSI was taxonic. MAXCOV pointed more strongly to the same conclusion. These analyses also provide evidence that a PGSI cutoff score of 10 rather than the standard 8 may be called for. PG as constructed by the PGSI may best be thought of as categorical, but further studies with more theory based measurements are needed to determine whether this holds in a wider range of samples and for other screens. A higher cutoff score may be called for on the PGSI when it is used for research purposes to avoid false positives.

Validation of HbA1c of 6.5% for Diagnosing Diabetes Mellitus via the Use of Taxometric Analysis

Previous studies in which authors examined the internal and external validity of a glycemic cut-point for diagnosis of diabetes mellitus have provided mixed results. The purpose of the current study was to test the internal validity of the HbA1c 6.5% cut-point with taxometric analysis. Data on 14,798 participants were obtained from the National Health and Nutrition Examination Survey, years 1999-2008. Fasting plasma glucose and HbA1c were submitted to the taxometric procedures MAMBAC (mean above minus below a cut) and MAXSLOPE (MAXimum SLOPE). The comparison curve fit index was the outcome measure, with values less than 0.40 and greater than 0.60 indicative of dimensional and categorical solutions, respectively. In the full sample, MAXSLOPE and MAMBAC procedures yielded CCFIs of 0.778 and 0.872, respectively. Analyses were repeated in subgroups by age, sex, fasting insulin level, ethnicity, and year; the lowest comparison curve fit index measurement from any analysis was 0.706. These results support a categorical overdimensional model of diabetes, consistent with the new HbA1c cut-point recommendation.

Taxometric Analyses of Specific Language Impairment in 6-Year-Old Children

To determine whether language scores at age 6 years suggest that specific language impairments (SLIs) distribute in a categorical or in a dimensional fashion. A taxometric analysis of language scores from 601 six-year-old children who were free of neonatal risk factors was performed. From among 4 candidate indicators of SLI, 2 were eligible for the mean above minus below a cut (MAMBAC) procedure (Meehl & Yonce, 1994): number of different words (NDW) produced in a language sample and average percentage phonemes repeated correctly in 3- and 4-syllable nonwords (3-4 PPC). Graphs of these MAMBAC variables were inspected to determine whether they patterned in a manner suggesting the presence of a discrete category, having either a central peak or a steep curve peaking near the final interval. MAMBAC curves for NDW and 3-4 PPC did not suggest the presence of a taxon, and results did not vary during consistency checks in which MAMBAC parameters and cutoff values for language deficits were manipulated. Results suggest that for these measures, children with specific language deficits are those falling at the lower end of a continuous distribution of language skills rather than a qualitatively distinct group.

Differentiating categorical and dimensional data with taxometric analysis: Are two variables better than none?

Taxometric analyses have proven helpful for distinguishing categorical and dimensional data. Many taxometric procedures require at least 3 variables for analysis. What if a construct is defined by only 2 conceptually nonredundant characteristics or a data set contains only 2 empirically nonredundant variables? In Study 1, we performed extensive simulations to determine whether informative results can be obtained when only 2 variables are available for taxometric analysis. The mean above minus below a cut (MAMBAC) and maximum slope (MAXSLOPE) procedures, used with parallel analyses of comparison data, successfully differentiated categorical and dimensional structure. With just 2 variables, it seems especially important that indicators vary across as many distinct values as possible and that investigators obtain as large a sample as possible. Additional findings address questions about the most effective way to implement taxometric analyses. In Study 2, the potential utility of 2-variable taxometric analysis is illustrated using data on proactive and reactive childhood aggression, where the results provided strong support for dimensional structure. As long as high-quality data are available, it appears that one can have confidence in the results of taxometric analyses performed with only 2 variables.

In search of the psychopathic sexuality taxon: Indicator size does matter

Recent research has suggested that a qualitatively distinct subtype of psychopathic sex offender can be identified via taxometric analyses (Harris et al., 2007). In this study we attempted to replicate the hypothesized psychopathic sexuality taxon in a group of 503 male sexual offenders using data from the Psychopathy Checklist-Revised (PCL-R:Hare, 2003) and five coercive and precocious sexuality items. Ambiguous to dimensional results were obtained when, in a replication of the Harris et al. (2007) study,dichotomized indicators were analyzed with summed input maximum covariance (MAXCOV). Clearly dimensional results, however, were obtained when higher correlating and more valid quasi-continuous indicators were analyzed with traditional (input variables not summed) MAXCOV, and both dichotomous and quasi-continuous indicators were analyzed with mean above minus below a cut (MAMBAC) and latent-mode factor analysis (L-Mode). These results suggest that Harris et al. (2007) may have mistaken the random fluctuations of weakly correlating and poorly differentiating indicators for a taxon. Consistent with the vast majority of earlier research,our results suggest that psychopathy (with or without coercive and precocious sexuality) is a dimensional construct.

The latent structure of dietary restraint, body dissatisfaction, and drive for thinness: A series of taxometric analyses.

Although the latent structure of various eating disorders has been explored in previous studies, no published studies have examined the latent structure of theoretically relevant variables that have been shown to cut across eating disorder diagnoses. The current study examined 3 such variables (dietary restraint, body dissatisfaction, and drive for thinness) among undergraduate women using the taxometric method. The 5 items from the Eating Disorders Examination Questionnaire's Dietary Restraint subscale were used as dietary restraint indicators, whereas items from the Eating Disorders Inventory Body Dissatisfaction and Drive for Thinness subscales were used as indicators of body dissatisfaction and drive for thinness, respectively. As hypothesized, MAXCOV (maximum covariance) and MAMBAC (mean above minus below a cut) analyses suggested that all 3 variables are dimensional; therefore, individuals with high levels of reported dietary restraint, body dissatisfaction, and drive for thinness appear to differ in degree, but not in kind, from those with lower levels. Implications for prevention, assessment, classification, and treatment are discussed.

Where Do We Draw the Line? Assigning Cases to Subsamples for MAMBAC, MAXCOV, and MAXEIG Taxometric Analyses

There are several important decisions that must be made when implementing taxometric procedures such as mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and maximum eigenvalue (MAXEIG). A Monte Carlo study was performed with 10,000 (5,000 categorical, 5,000 dimensional) samples to examine 5 ways to locate the first and last MAMBAC cuts and 24 ways to perform MAXCOV and MAXEIG. For MAMBAC, there was little difference across conditions, with slightly more accurate results obtained when a small, fixed number of cases (n = 10 or 25) was located beyond the most extreme cuts. For MAXCOV and MAXEIG, the results were more palpable: MAXCOV slightly outperformed MAXEIG, windows achieved significantly better results than intervals, and a larger number of cases per subsample were associated with more accurate results. Alcohol misuse data obtained from a group of male prisoners were used to illustrate relationships observed in the Monte Carlo study.

Latent Structure of a Two-Dimensional Model of Antisocial Personality Disorder: Construct Validation and Taxometric Analysis

Indicators from three different self-report measures-the Psychological Inventory of Criminal Thinking Styles (PICTS), the Levenson Self-Report Psychopathy (LSRP) scale, and the Antisocial Features (ANT) scale of the Personality Assessment Inventory-were organized into two dimensions, proactive and reactive, and subjected to construct validation and taxometric analysis in 637 male medium and maximum security inmates. Using three nonredundant and relatively independent taxometric procedures, mean above minus below a cut (MAMBAC), maximum eigenvalue (MAXEIG), and latent mode factor analysis (L-Mode), consistent evidence of dimensional latent structure was discerned for the proactive and reactive dimensions of antisociality, both of which correlated moderately with a measure of antisocial personality disorder. It is reasoned that the two-dimensional model may eventually be capable of bridging the gap between childhood aggression and adult criminality as well as provide guidance to clinicians working with criminal offenders.

Feigned neurocognitive deficit: Taxon or dimension?

The purpose of this study was to explore the latent structure of feigned neurocognitive deficit. Scores on the Test of Memory Malingering (TOMM), Letter Memory Test (LMT), and Victoria Symptom Validity Test (VSVT) served as indicators in a taxometric investigation of 527 compensation-seeking adults using three taxometric procedures—mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent-mode factor analysis (L-Mode). All three procedures showed evidence of dimensional latent structure. The fact that feigned neurocognitive symptomatology is ordered along a continuum rather than bifurcating into distinct categories has important implications for theory, research, and clinical practice.

A taxometric investigation of agoraphobia in a clinical and a community sample

The nosological status of agoraphobia is controversial. Agoraphobia may be a distinct diagnostic entity or a marker of avoidance severity. The current study examines the latent structure of agoraphobia through the use of taxometric analysis. The latent structure of agoraphobia was examined in two independent samples, one comprising outpatients presenting for treatment for panic disorder (PD) with or without agoraphobia ( n = 365), and the other comprising community volunteers to a national mental health survey who experienced fear or avoidance of at least one prototypic agoraphobic situation ( n = 640). Two taxometric procedures were carried out – maximum eigenvalue (MAXEIG) and mean above minus below a cut (MAMBAC) – using indicators derived from questionnaire measures of, and structured diagnostic interviews for, agoraphobia. Results show consistent evidence of dimensional latent structure in both samples. It is concluded that scores on measures of agoraphobia best represent an agoraphobic severity dimension.

A taxometric study of alcohol abuse and dependence in a general population sample: evidence of dimensional latent structure and implications for DSM-V

To explore, with the aid of taxometric analysis, whether alcohol abuse and alcohol dependence are each conceptualized most effectively as single latent dimensions or distinct latent categories. Data were taken from a nationally representative cross-sectional epidemiological survey of psychiatric and substance use disorders. General population of Australia. A subsample of all respondents who had consumed at least 12 drinks in the year prior to the survey and who had consumed at least three drinks on at least one single day (n = 4920 of a possible 10,641). DSM-IV criteria for alcohol abuse and dependence were assessed with the Composite International Diagnostic Interview, version 2.1. Two independent taxometric procedures, MAXimum EIGenvalue (MAXEIG) and mean above minus below a cut (MAMBAC), together with analysis of simulated dimensional and categorical data sets, were carried out. Findings Consistent evidence was found for a single latent dimension underlying the symptoms of alcohol dependence. Less consistent evidence of dimensionality was found for the symptoms of alcohol abuse. These findings support the growing consensus regarding the need for continuous measures of alcohol use disorders to complement the traditional categorical representations in upcoming versions of the major psychiatric classification systems.