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Mixture Factor Analysis for Approximating a Nonnormally Distributed Continuous Latent Factor with Continuous and Dichotomous Observed Variables

ERIC Educational Resources Information Center

Wall, Melanie M.; Guo, Jia; Amemiya, Yasuo

2012-01-01

Mixture factor analysis is examined as a means of flexibly estimating nonnormally distributed continuous latent factors in the presence of both continuous and dichotomous observed variables. A simulation study compares mixture factor analysis with normal maximum likelihood (ML) latent factor modeling. Different results emerge for continuous versus…
Use of Latent Profile Analysis in Studies of Gifted Students

ERIC Educational Resources Information Center

Mammadov, Sakhavat; Ward, Thomas J.; Cross, Jennifer Riedl; Cross, Tracy L.

2016-01-01

To date, in gifted education and related fields various conventional factor analytic and clustering techniques have been used extensively for investigation of the underlying structure of data. Latent profile analysis is a relatively new method in the field. In this article, we provide an introduction to latent profile analysis for gifted education…
Latent human error analysis and efficient improvement strategies by fuzzy TOPSIS in aviation maintenance tasks.

PubMed

Chiu, Ming-Chuan; Hsieh, Min-Chih

2016-05-01

The purposes of this study were to develop a latent human error analysis process, to explore the factors of latent human error in aviation maintenance tasks, and to provide an efficient improvement strategy for addressing those errors. First, we used HFACS and RCA to define the error factors related to aviation maintenance tasks. Fuzzy TOPSIS with four criteria was applied to evaluate the error factors. Results show that 1) adverse physiological states, 2) physical/mental limitations, and 3) coordination, communication, and planning are the factors related to airline maintenance tasks that could be addressed easily and efficiently. This research establishes a new analytic process for investigating latent human error and provides a strategy for analyzing human error using fuzzy TOPSIS. Our analysis process complements shortages in existing methodologies by incorporating improvement efficiency, and it enhances the depth and broadness of human error analysis methodology. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Factor Structure Invariance of the Kaufman Adolescent and Adult Intelligence Test across Male and Female Samples

ERIC Educational Resources Information Center

Immekus, Jason C.; Maller, Susan J.

2010-01-01

Multisample confirmatory factor analysis (MCFA) and latent mean structures analysis (LMS) were used to test measurement invariance and latent mean differences on the Kaufman Adolescent and Adult Intelligence Scale[TM] (KAIT) across males and females in the standardization sample. MCFA found that the parameters of the KAIT two-factor model were…
Bayesian Adaptive Lasso for Ordinal Regression with Latent Variables

ERIC Educational Resources Information Center

Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan

2017-01-01

We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…
Mean structure analysis from an IRT approach: an application in the context of organizational psychology.

PubMed

Revuelta Menéndez, Javier; Ximénez Gómez, Carmen

2012-11-01

The application of mean and covariance structure analysis with quantitative data is increasing. However, latent means analysis with qualitative data is not as widespread. This article summarizes the procedures to conduct an analysis of latent means of dichotomous data from an item response theory approach. We illustrate the implementation of these procedures in an empirical example referring to the organizational context, where a multi-group analysis was conducted to compare the latent means of three employee groups in two factors measuring personal preferences and the perceived degree of rewards from the organization. Results show that higher personal motivations are associated with higher perceived importance of the organization, and that these perceptions differ across groups, so that higher-level employees have a lower level of personal and perceived motivation. The article shows how to estimate the factor means and the factor correlation from dichotomous data, and how to assess goodness of fit. Lastly, we provide the M-Plus syntax code in order to facilitate the latent means analyses for applied researchers.
Realist identification of group-level latent variables for perinatal social epidemiology theory building.

PubMed

Eastwood, John Graeme; Jalaludin, Bin Badrudin; Kemp, Lynn Ann; Phung, Hai Ngoc

2014-01-01

We have previously reported in this journal on an ecological study of perinatal depressive symptoms in South Western Sydney. In that article, we briefly reported on a factor analysis that was utilized to identify empirical indicators for analysis. In this article, we report on the mixed method approach that was used to identify those latent variables. Social epidemiology has been slow to embrace a latent variable approach to the study of social, political, economic, and cultural structures and mechanisms, partly for philosophical reasons. Critical realist ontology and epistemology have been advocated as an appropriate methodological approach to both theory building and theory testing in the health sciences. We describe here an emergent mixed method approach that uses qualitative methods to identify latent constructs followed by factor analysis using empirical indicators chosen to measure identified qualitative codes. Comparative analysis of the findings is reported together with a limited description of realist approaches to abstract reasoning.
Modeling the Trajectory of Analgesic Demand Over Time After Total Knee Arthroplasty Using the Latent Curve Analysis.

PubMed

Lo, Po-Han; Tsou, Mei-Yung; Chang, Kuang-Yi

2015-09-01

Patient-controlled epidural analgesia (PCEA) is commonly used for pain relief after total knee arthroplasty (TKA). This study aimed to model the trajectory of analgesic demand over time after TKA and explore its influential factors using latent curve analysis. Data were retrospectively collected from 916 patients receiving unilateral or bilateral TKA and postoperative PCEA. PCEA demands during 12-hour intervals for 48 hours were directly retrieved from infusion pumps. Potentially influential factors of PCEA demand, including age, height, weight, body mass index, sex, and infusion pump settings, were also collected. A latent curve analysis with 2 latent variables, the intercept (baseline) and slope (trend), was applied to model the changes in PCEA demand over time. The effects of influential factors on these 2 latent variables were estimated to examine how these factors interacted with time to alter the trajectory of PCEA demand over time. On average, the difference in analgesic demand between the first and second 12-hour intervals was only 15% of that between the first and third 12-hour intervals. No significant difference in PCEA demand was noted between the third and fourth 12-hour intervals. Aging tended to decrease the baseline PCEA demand but body mass index and infusion rate were positively correlated with the baseline. Only sex significantly affected the trend parameter and male individuals tended to have a smoother decreasing trend of analgesic demands over time. Patients receiving bilateral procedures did not consume more analgesics than their unilateral counterparts. Goodness of fit analysis indicated acceptable model fit to the observed data. Latent curve analysis provided valuable information about how analgesic demand after TKA changed over time and how patient characteristics affected its trajectory.
Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

PubMed

Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

2017-01-01

Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.
Pain and the defense response: structural equation modeling reveals a coordinated psychophysiological response to increasing painful stimulation.

PubMed

Donaldson, Gary W; Chapman, C Richard; Nakamura, Yoshi; Bradshaw, David H; Jacobson, Robert C; Chapman, Christopher N

2003-03-01

The defense response theory implies that individuals should respond to increasing levels of painful stimulation with correlated increases in affectively mediated psychophysiological responses. This paper employs structural equation modeling to infer the latent processes responsible for correlated growth in the pain report, evoked potential amplitudes, pupil dilation, and skin conductance of 92 normal volunteers who experienced 144 trials of three levels of increasingly painful electrical stimulation. The analysis assumed a two-level model of latent growth as a function of stimulus level. The first level of analysis formulated a nonlinear growth model for each response measure, and allowed intercorrelations among the parameters of these models across individuals. The second level of analysis posited latent process factors to account for these intercorrelations. The best-fitting parsimonious model suggests that two latent processes account for the correlations. One of these latent factors, the activation threshold, determines the initial threshold response, while the other, the response gradient, indicates the magnitude of the coherent increase in response with stimulus level. Collectively, these two second-order factors define the defense response, a broad construct comprising both subjective pain evaluation and physiological mechanisms.
Characterising the latent structure and organisation of self-reported thoughts, feelings and behaviours in adolescents and young adults

PubMed Central

Neufeld, Sharon; Jones, Peter B.; Fonagy, Peter; Bullmore, Edward T.; Dolan, Raymond J.; Moutoussis, Michael; Toseeb, Umar; Goodyer, Ian M.

2017-01-01

Little is known about the underlying relationships between self-reported mental health items measuring both positive and negative emotional and behavioural symptoms at the population level in young people. Improved measurement of the full range of mental well-being and mental illness may aid in understanding the aetiological substrates underlying the development of both mental wellness as well as specific psychiatric diagnoses. A general population sample aged 14 to 24 years completed self-report questionnaires on anxiety, depression, psychotic-like symptoms, obsessionality and well-being. Exploratory and confirmatory factor models for categorical data and latent profile analyses were used to evaluate the structure of both mental wellness and illness items. First order, second order and bifactor structures were evaluated on 118 self-reported items obtained from 2228 participants. A bifactor solution was the best fitting latent variable model with one general latent factor termed ‘distress’ and five ‘distress independent’ specific factors defined as self-confidence, antisocial behaviour, worry, aberrant thinking, and mood. Next, six distinct subgroups were derived from a person-centred latent profile analysis of the factor scores. Finally, concurrent validity was assessed using information on hazardous behaviours (alcohol use, substance misuse, self-harm) and treatment for mental ill health: both discriminated between the latent traits and latent profile subgroups. The findings suggest a complex, multidimensional mental health structure in the youth population rather than the previously assumed first or second order factor structure. Additionally, the analysis revealed a low hazardous behaviour/low mental illness risk subgroup not previously described. Population sub-groups show greater validity over single variable factors in revealing mental illness risks. In conclusion, our findings indicate that the structure of self reported mental health is multidimensional in nature and uniquely finds improved prediction to mental illness risk within person-centred subgroups derived from the multidimensional latent traits. PMID:28403164
Characterising the latent structure and organisation of self-reported thoughts, feelings and behaviours in adolescents and young adults.

PubMed

St Clair, Michelle C; Neufeld, Sharon; Jones, Peter B; Fonagy, Peter; Bullmore, Edward T; Dolan, Raymond J; Moutoussis, Michael; Toseeb, Umar; Goodyer, Ian M

2017-01-01

Little is known about the underlying relationships between self-reported mental health items measuring both positive and negative emotional and behavioural symptoms at the population level in young people. Improved measurement of the full range of mental well-being and mental illness may aid in understanding the aetiological substrates underlying the development of both mental wellness as well as specific psychiatric diagnoses. A general population sample aged 14 to 24 years completed self-report questionnaires on anxiety, depression, psychotic-like symptoms, obsessionality and well-being. Exploratory and confirmatory factor models for categorical data and latent profile analyses were used to evaluate the structure of both mental wellness and illness items. First order, second order and bifactor structures were evaluated on 118 self-reported items obtained from 2228 participants. A bifactor solution was the best fitting latent variable model with one general latent factor termed 'distress' and five 'distress independent' specific factors defined as self-confidence, antisocial behaviour, worry, aberrant thinking, and mood. Next, six distinct subgroups were derived from a person-centred latent profile analysis of the factor scores. Finally, concurrent validity was assessed using information on hazardous behaviours (alcohol use, substance misuse, self-harm) and treatment for mental ill health: both discriminated between the latent traits and latent profile subgroups. The findings suggest a complex, multidimensional mental health structure in the youth population rather than the previously assumed first or second order factor structure. Additionally, the analysis revealed a low hazardous behaviour/low mental illness risk subgroup not previously described. Population sub-groups show greater validity over single variable factors in revealing mental illness risks. In conclusion, our findings indicate that the structure of self reported mental health is multidimensional in nature and uniquely finds improved prediction to mental illness risk within person-centred subgroups derived from the multidimensional latent traits.
Scalable non-negative matrix tri-factorization.

PubMed

Čopar, Andrej; Žitnik, Marinka; Zupan, Blaž

2017-01-01

Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining. Matrix factorization learns a latent data model that takes a data matrix and transforms it into a latent feature space enabling generalization, noise removal and feature discovery. However, factorization algorithms are numerically intensive, and hence there is a pressing challenge to scale current algorithms to work with large datasets. Our focus in this paper is matrix tri-factorization, a popular method that is not limited by the assumption of standard matrix factorization about data residing in one latent space. Matrix tri-factorization solves this by inferring a separate latent space for each dimension in a data matrix, and a latent mapping of interactions between the inferred spaces, making the approach particularly suitable for biomedical data mining. We developed a block-wise approach for latent factor learning in matrix tri-factorization. The approach partitions a data matrix into disjoint submatrices that are treated independently and fed into a parallel factorization system. An appealing property of the proposed approach is its mathematical equivalence with serial matrix tri-factorization. In a study on large biomedical datasets we show that our approach scales well on multi-processor and multi-GPU architectures. On a four-GPU system we demonstrate that our approach can be more than 100-times faster than its single-processor counterpart. A general approach for scaling non-negative matrix tri-factorization is proposed. The approach is especially useful parallel matrix factorization implemented in a multi-GPU environment. We expect the new approach will be useful in emerging procedures for latent factor analysis, notably for data integration, where many large data matrices need to be collectively factorized.
On the explaining-away phenomenon in multivariate latent variable models.

PubMed

van Rijn, Peter; Rijmen, Frank

2015-02-01

Many probabilistic models for psychological and educational measurements contain latent variables. Well-known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the 'explaining-away' phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well-known latent variable models by using both theoretical and real data examples. © 2014 The British Psychological Society.
Latent factor structure of a behavioral economic marijuana demand curve.

PubMed

Aston, Elizabeth R; Farris, Samantha G; MacKillop, James; Metrik, Jane

2017-08-01

Drug demand, or relative value, can be assessed via analysis of behavioral economic purchase task performance. Five demand indices are typically obtained from drug purchase tasks. The goal of this research was to determine whether metrics of marijuana reinforcement from a marijuana purchase task (MPT) exhibit a latent factor structure that efficiently characterizes marijuana demand. Participants were regular marijuana users (n = 99; 37.4% female, 71.5% marijuana use days [5 days/week], 15.2% cannabis dependent) who completed study assessments, including the MPT, during a baseline session. Principal component analysis was used to examine the latent structure underlying MPT indices. Concurrent validity was assessed via examination of relationships between latent factors and marijuana use, past quit attempts, and marijuana expectancies. A two-factor solution was confirmed as the best fitting structure, accounting for 88.5% of the overall variance. Factor 1 (65.8% variance) reflected "Persistence," indicating sensitivity to escalating marijuana price, which comprised four MPT indices (elasticity, O max , P max , and breakpoint). Factor 2 (22.7% variance) reflected "Amplitude," indicating the amount consumed at unrestricted price (intensity). Persistence factor scores were associated with fewer past marijuana quit attempts and lower expectancies of negative use outcomes. Amplitude factor scores were associated with more frequent use, dependence symptoms, craving severity, and positive marijuana outcome expectancies. Consistent with research on alcohol and cigarette purchase tasks, the MPT can be characterized with a latent two-factor structure. Thus, demand for marijuana appears to encompass distinct dimensions of price sensitivity and volumetric consumption, with differential relations to other aspects of marijuana motivation.
Comparing Factor, Class, and Mixture Models of Cannabis Initiation and DSM Cannabis Use Disorder Criteria, Including Craving, in the Brisbane Longitudinal Twin Study

PubMed Central

Kubarych, Thomas S.; Kendler, Kenneth S.; Aggen, Steven H.; Estabrook, Ryne; Edwards, Alexis C.; Clark, Shaunna L.; Martin, Nicholas G.; Hickie, Ian B.; Neale, Michael C.; Gillespie, Nathan A.

2014-01-01

Accumulating evidence suggests that the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying factor. However, it remains possible that models with additional factors, or latent class models or hybrid models, may better explain the data. Using structured interviews, 626 adult male and female twins provided complete data on symptoms of cannabis abuse and dependence, plus a craving criterion. We compared latent factor analysis, latent class analysis, and factor mixture modeling using normal theory marginal maximum likelihood for ordinal data. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-IV criteria and determine whether DSM-5 craving loads onto a general factor. When compared with latent class and mixture models, factor models provided a better fit to the data. When conditioned on initiation and cannabis use, the association between criteria for abuse, dependence, withdrawal, and craving were best explained by two correlated latent factors for males and females: a general risk factor to CUD and a factor capturing the symptoms of social and occupational impairment as a consequence of frequent use. Secondary analyses revealed a modest increase in the prevalence of DSM-5 CUD compared with DSM-IV cannabis abuse or dependence. It is concluded that, in addition to a general factor with loadings on cannabis use and symptoms of abuse, dependence, withdrawal, and craving, a second clinically relevant factor defined by features of social and occupational impairment was also found for frequent cannabis use. PMID:24588857
Pre-clinical cognitive phenotypes for Alzheimer disease: a latent profile approach.

PubMed

Hayden, Kathleen M; Kuchibhatla, Maragatha; Romero, Heather R; Plassman, Brenda L; Burke, James R; Browndyke, Jeffrey N; Welsh-Bohmer, Kathleen A

2014-11-01

Cognitive profiles for pre-clinical Alzheimer disease (AD) can be used to identify groups of individuals at risk for disease and better characterize pre-clinical disease. Profiles or patterns of performance as pre-clinical phenotypes may be more useful than individual test scores or measures of global decline. To evaluate patterns of cognitive performance in cognitively normal individuals to derive latent profiles associated with later onset of disease using a combination of factor analysis and latent profile analysis. The National Alzheimer Coordinating Centers collect data, including a battery of neuropsychological tests, from participants at 29 National Institute on Aging-funded Alzheimer Disease Centers across the United States. Prior factor analyses of this battery demonstrated a four-factor structure comprising memory, attention, language, and executive function. Factor scores from these analyses were used in a latent profile approach to characterize cognition among a group of cognitively normal participants (N = 3,911). Associations between latent profiles and disease outcomes an average of 3 years later were evaluated with multinomial regression models. Similar analyses were used to determine predictors of profile membership. Four groups were identified; each with distinct characteristics and significantly associated with later disease outcomes. Two groups were significantly associated with development of cognitive impairment. In post hoc analyses, both the Trail Making Test Part B, and a contrast score (Delayed Recall - Trails B), significantly predicted group membership and later cognitive impairment. Latent profile analysis is a useful method to evaluate patterns of cognition in large samples for the identification of preclinical AD phenotypes; comparable results, however, can be achieved with very sensitive tests and contrast scores. Copyright © 2014 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.
Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters

ERIC Educational Resources Information Center

Hoshino, Takahiro; Shigemasu, Kazuo

2008-01-01

The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…
Applying Latent Class Analysis to Risk Stratification for Perioperative Mortality in Patients Undergoing Intraabdominal General Surgery.

PubMed

Kim, Minjae; Wall, Melanie M; Li, Guohua

2016-07-01

Perioperative risk stratification is often performed using individual risk factors without consideration of the syndemic of these risk factors. We used latent class analysis (LCA) to identify the classes of comorbidities and risk factors associated with perioperative mortality in patients presenting for intraabdominal general surgery. The 2005 to 2010 American College of Surgeons National Surgical Quality Improvement Program was used to obtain a cohort of patients undergoing intraabdominal general surgery. Risk factors and comorbidities were entered into LCA models to identify the latent classes, and individuals were assigned to a class based on the highest posterior probability of class membership. Relative risk regression was used to determine the associations between the latent classes and 30-day mortality, with adjustments for procedure. A 9-class model was fit using LCA on 466,177 observations. After combining classes with similar adjusted mortality risks, 5 risk classes were obtained. Compared with the class with average mortality risk (class 4), the risk ratios (95% confidence interval) ranged from 0.020 (0.014-0.027) in the lowest risk class (class 1) to 6.75 (6.46-7.02) in the highest risk class. After adjusting for procedure and ASA physical status, the latent classes remained significantly associated with 30-day mortality. The addition of the risk class variable to a model containing ASA physical status and surgical procedure demonstrated a significant increase in the area under the receiver operator characteristic curve (0.892 vs 0.915; P < 0.0001). Latent classes of risk factors and comorbidities in patients undergoing intraabdominal surgery are predictive of 30-day mortality independent of the ASA physical status and improve risk prediction with the ASA physical status.
Examining Factors Associated with (In)Stability in Social Information Processing among Urban School Children: A Latent Transition Analytic Approach

ERIC Educational Resources Information Center

Goldweber, Asha; Bradshaw, Catherine P.; Goodman, Kimberly; Monahan, Kathryn; Cooley-Strickland, Michele

2011-01-01

There is compelling evidence for the role of social information processing (SIP) in aggressive behavior. However, less is known about factors that influence stability versus instability in patterns of SIP over time. Latent transition analysis was used to identify SIP patterns over one year and examine how community violence exposure, aggressive…

A Latent Class Analysis of Adolescent Gambling: Application of Resilience Theory

ERIC Educational Resources Information Center

Goldstein, Abby L.; Faulkner, Breanne; Cunningham, Rebecca M.; Zimmerman, Marc A.; Chermack, Stephen; Walton, Maureen A.

2013-01-01

The current study examined the application of resilience theory to adolescent gambling using Latent Class Analysis (LCA) to establish subtypes of adolescent gamblers and to explore risk and promotive factors associated with gambling group membership. Participants were a diverse sample of 249 adolescents ages 14 to 18 (30.1 % female, 59.4 % African…
Emotional rigidity negatively impacts remission from anxiety and recovery of well-being.

PubMed

Wiltgen, Anika; Shepard, Christopher; Smith, Ryan; Fowler, J Christopher

2018-08-15

Emotional rigidity is described in clinical literature as a significant barrier to recovery; however, few there are few empirical measures of the construct. The current study had two aims: Study 1 aimed to identify latent factors that may bear on the construct of emotional rigidity while Study 2 assessed the potential impact of the latent factor(s) on anxiety remission rates and well-being. This study utilized data from 2472 adult inpatients (1176 females and 1296 males) with severe psychopathology. Study 1 utilized exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to identify latent factors of emotional rigidity. Study 2 utilized hierarchical logistic regression analyses to assess the relationships among emotional rigidity factors and anxiety remission and well-being recovery at discharge. Study 1 yielded a two-factor solution identified in EFA was confirmed with CFA. Factor 1 consisted of neuroticism, experiential avoidance, non-acceptance of emotions, impaired goal-directed behavior, impulse control difficulties and limited access to emotion regulation strategies when experiencing negative emotions. Factor 2 consisted of lack of emotional awareness and lack of emotional clarity when experiencing negative emotions. Results of Study 2 indicated higher scores on Factor 1 was associated with lower remission rates from anxiety and poorer well-being upon discharge. Factor 2 was not predictive of outcome. Emotional rigidity appears to be a latent construct that negatively impacts remission rates from anxiety. Limitations of the present study include its retrospective design, and inefficient methods of assessing emotional rigidity. Copyright © 2018. Published by Elsevier B.V.
Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

PubMed

Kim, Eun Sook; Cao, Chunhua

2015-01-01

Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.
Analysis of Water Vapour Flux Between Alpine Wetlands Underlying the Surface and Atmosphere in the Source Region of the Yellow River

NASA Astrophysics Data System (ADS)

Xie, Y.; Wen, J.; Liu, R.; Wang, X.; JIA, D.

2017-12-01

Wetland underlying surface is sensitive to climate change. Analysis of the degree of coupling between wetlands and the atmosphere and a quantitative assessment of how environmental factors influence latent heat flux have considerable scientific significance. Previous studies, which focused on the forest, grassland and farmland ecosystems, lack research on the alpine wetlands. In addition, research on the environmental control mechanism of latent heat flux is still qualitative and lacks quantitative evaluations and calculations. Using data from the observational tests of the Maduo Observatory of Climate and Environment of the Northwest Institute of Eco-Environment and Resource, CAS, from June 1 to August 31, 2014, this study analysed the time-varying characteristics and causes of the degree of coupling between alpine wetlands underlying surface and the atmosphere and quantitatively calculated the influences of different environmental factors (solar radiation and vapour pressure deficit) on latent heat flux. The results were as follows: Due to the diurnal variations of solar radiation and wind speed, the diurnal variations of the Ω factor present a trend in which the Ω factor are small in the morning and large in the evening. Due to the vegetation growing cycle, the seasonal variations of the Ω factor present a reverse "U" trend . These trends are similar to the diurnal and seasonal variations of the absolute control exercised by solar radiation over the latent heat flux. This conforms to omega theory. The values for average absolute atmospheric factor (surface factor or total ) control exercised by solar radiation and water vapour pressure are 0.20 (0.02 or 0.22 ) and 0.005 (-0.07 or -0.06) W·m-2·Pa-1, respectively.. Generally speaking, solar radiation and water vapour pressure deficit exert opposite forces on the latent heat flux. The average Ω factor is high during the vegetation growing season, with a value of 0.38, and the degree of coupling between the alpine wetland surface and the atmosphere system is low. The actual measurements agree with omega theory. The latent heat flux is mainly influenced by solar radiation. From the above, our study has provided reference information for exploring the influences of environmental factors on the latent heat flux over the alpine wetlands of the Yellow River source region.
Latent Model Analysis of Substance Use and HIV Risk Behaviors among High-Risk Minority Adults

ERIC Educational Resources Information Center

Wang, Min Qi; Matthew, Resa F.; Chiu, Yu-Wen; Yan, Fang; Bellamy, Nikki D.

2007-01-01

Objectives: This study evaluated substance use and HIV risk profile using a latent model analysis based on ecological theory, inclusive of a risk and protective factor framework, in sexually active minority adults (N=1,056) who participated in a federally funded substance abuse and HIV prevention health initiative from 2002 to 2006. Methods: Data…
Heritabilities of Facial Measurements and Their Latent Factors in Korean Families

PubMed Central

Kim, Hyun-Jin; Im, Sun-Wha; Jargal, Ganchimeg; Lee, Siwoo; Yi, Jae-Hyuk; Park, Jeong-Yeon; Sung, Joohon; Cho, Sung-Il; Kim, Jong-Yeol; Kim, Jong-Il; Seo, Jeong-Sun

2013-01-01

Genetic studies on facial morphology targeting healthy populations are fundamental in understanding the specific genetic influences involved; yet, most studies to date, if not all, have been focused on congenital diseases accompanied by facial anomalies. To study the specific genetic cues determining facial morphology, we estimated familial correlations and heritabilities of 14 facial measurements and 3 latent factors inferred from a factor analysis in a subset of the Korean population. The study included a total of 229 individuals from 38 families. We evaluated a total of 14 facial measurements using 2D digital photographs. We performed factor analysis to infer common latent variables. The heritabilities of 13 facial measurements were statistically significant (p < 0.05) and ranged from 0.25 to 0.61. Of these, the heritability of intercanthal width in the orbital region was found to be the highest (h2 = 0.61, SE = 0.14). Three factors (lower face portion, orbital region, and vertical length) were obtained through factor analysis, where the heritability values ranged from 0.45 to 0.55. The heritability values for each factor were higher than the mean heritability value of individual original measurements. We have confirmed the genetic influence on facial anthropometric traits and suggest a potential way to categorize and analyze the facial portions into different groups. PMID:23843774
Bootstrap Standard Error Estimates in Dynamic Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Browne, Michael W.

2010-01-01

Dynamic factor analysis summarizes changes in scores on a battery of manifest variables over repeated measurements in terms of a time series in a substantially smaller number of latent factors. Algebraic formulae for standard errors of parameter estimates are more difficult to obtain than in the usual intersubject factor analysis because of the…
Augmenting Latent Dirichlet Allocation and Rank Threshold Detection with Ontologies

DTIC Science & Technology

2010-03-01

Probabilistic Latent Semantic Indexing (PLSI) is an automated indexing information retrieval model [20]. It is based on a statistical latent class model which is...uses a statistical foundation that is more accurate in finding hidden semantic relationships [20]. The model uses factor analysis of count data, number...principle of statistical infer- ence which asserts that all of the information in a sample is contained in the likelihood function [20]. The statistical
Paths to tobacco abstinence: A repeated-measures latent class analysis.

PubMed

McCarthy, Danielle E; Ebssa, Lemma; Witkiewitz, Katie; Shiffman, Saul

2015-08-01

Knowledge of smoking change processes may be enhanced by identifying pathways to stable abstinence. We sought to identify latent classes of smokers based on their day-to-day smoking status in the first weeks of a cessation attempt. We examined treatment effects on class membership and compared classes on baseline individual differences and 6-month abstinence rates. In this secondary analysis of a double-blind randomized placebo-controlled clinical trial (N = 1,433) of 5 smoking cessation pharmacotherapies (nicotine patch, nicotine lozenge, bupropion SR, patch and lozenge, or bupropion SR and lozenge), we conducted repeated-measures latent class analysis of daily smoking status (any smoking vs. none) for the first 27 days of a quit attempt. Treatment and covariate relations with latent class membership were examined. Distal outcome analysis compared confirmed 6-month abstinence rates among the latent classes. A 5-class solution was selected. Three-quarters of smokers were in stable smoking or abstinent classes, but 25% were in classes with unstable abstinence probabilities over time. Active treatment (compared to placebo), and particularly the patch and lozenge combination, promoted early quitting. Latent classes differed in 6-month abstinence rates and on several baseline variables, including nicotine dependence, quitting history, self-efficacy, sleep disturbance, and minority status. Repeated-measures latent class analysis identified latent classes of smoking change patterns affected by treatment, related to known risk factors, and predictive of distal outcomes. Tracking behavior early in a change attempt may identify prognostic patterns of change and facilitate adaptive treatment planning. (c) 2015 APA, all rights reserved).
Latent Class Subtyping of Attention-Deficit/Hyperactivity Disorder and Comorbid Conditions

ERIC Educational Resources Information Center

Acosta, Maria T.; Castellanos, F. Xavier; Bolton, Kelly L.; Balog, Joan Z.; Eagen, Patricia; Nee, Linda; Jones, Janet; Palacio, Luis; Sarampote, Christopher; Russell, Heather F.; Berg, Kate; Arcos-Burgos, Mauricio; Muenke, Maximilian

2008-01-01

The study attempts to carry out latent class analysis (LCA) in a sample of 1010 individuals, some with Attention-Deficit/Hyperactivity disorder (ADHD) and others normal. Results indicate that LCA can feasibly allow the combination of externalizing and internalizing symptoms for future tests regarding specific genetic risk factors.
Severity of mental illness as a result of multiple childhood adversities: US National Epidemiologic Survey.

PubMed

Curran, Emma; Adamson, Gary; Stringer, Maurice; Rosato, Michael; Leavey, Gerard

2016-05-01

To examine patterns of childhood adversity, their long-term consequences and the combined effect of different childhood adversity patterns as predictors of subsequent psychopathology. Secondary analysis of data from the US National Epidemiologic Survey on alcohol and related conditions. Using latent class analysis to identify childhood adversity profiles; and using multinomial logistic regression to validate and further explore these profiles with a range of associated demographic and household characteristics. Finally, confirmatory factor analysis substantiated initial latent class analysis findings by investigating a range of mental health diagnoses. Latent class analysis generated a three-class model of childhood adversity in which 60 % of participants were allocated to a low adversity class; 14 % to a global adversities class (reporting exposures for all the derived latent classes); and 26 % to a domestic emotional and physical abuse class (exposed to a range of childhood adversities). Confirmatory Factor analysis defined an internalising-externalising spectrum to represent lifetime reporting patterns of mental health disorders. Using logistic regression, both adversity groups showed specific gender and race/ethnicity differences, related family discord and increased psychopathology. We identified underlying patterns in the exposure to childhood adversity and associated mental health. These findings are informative in their description of the configuration of adversities, rather than focusing solely on the cumulative aspect of experience. Amelioration of longer-term negative consequences requires early identification of psychopathology risk factors that can inform protective and preventive interventions. This study highlights the utility of screening for childhood adversities when individuals present with symptoms of psychiatric disorders.
Race Differences in Patterns of Risky Behavior and Associated Risk Factors in Adolescence.

PubMed

Childs, Kristina K; Ray, James V

2017-05-01

Using data from the National Longitudinal Study of Adolescent Health (Add Health), this study expands on previous research by (a) examining differences across race in patterns or "subgroups" of adolescents based on nine self-reported behaviors (e.g., delinquency, substance use, risky sexual practices) and (b) comparing the risk factors (e.g., peer association, parenting, neighborhood cohesion), both within and across the race-specific subgroups, related to membership into the identified latent classes. The data used in this study include respondents aged 13 to 17 who participated in Waves 1 and 2 of the Add Health in-home interview. Latent class analysis (LCA) identified key differences in the number and characteristics of the latent classes across the racial subgroups. In addition, both similarities and differences in the risk factors for membership into the latent classes were identified across and within the race-specific subgroups. Implications for understanding risky behavior in adolescence, as well as directions for future research, are discussed.
Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

ERIC Educational Resources Information Center

Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

2012-01-01

In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…
Measuring the environmental awareness of young farmers

NASA Astrophysics Data System (ADS)

Kountios, G.; Ragkos, A.; Padadavid, G.; Hadjimitsis, D.

2017-09-01

Young farmers in Europe, especially the beneficiaries of Common Agricultural Policy (CAP) funding schemes, are considered as the ones who could ensure the sustainability of the European Model of Agriculture. Economic efficiency and competitiveness, aversion of depopulation of rural areas and environmental protection constitute some of the key objectives of the CAP and young farmers are expected to play a role to all of them. This study proposes a way of measuring the potential of young farmers to contribute to the latter objectives of the CAP by estimating their environmental attitudes. Data from a questionnaire survey of 492 Greek young farmers were used to design a latent construct measuring their environmental attitudes. The latent construct was designed by means of an Explanatory Factor Analysis (EFA) using the responses to a set of 12 Likert-scale items. The results the EFA yielded a latent construct with three factors related to "Environmental pollution and policies (EPP)", "Environmental factors and food quality (EFF)" and "Farming practices and the environment". These results were validated through a CFA where 8 items in total were categorized in the three factors (latent variables). The utilization of the latent construct for the effective implementation of CAP measures could ameliorate the relationships of agriculture and environment in general.
Latent Constructs in Psychosocial Factors Associated with Cardiovascular Disease: An Examination by Race and Sex

PubMed Central

Clark, Cari Jo; Henderson, Kimberly M.; de Leon, Carlos F. Mendes; Guo, Hongfei; Lunos, Scott; Evans, Denis A.; Everson-Rose, Susan A.

2012-01-01

This study examines race and sex differences in the latent structure of 10 psychosocial measures and the association of identified factors with self-reported history of coronary heart disease (CHD). Participants were 4,128 older adults from the Chicago Health and Aging Project. Exploratory factor analysis (EFA) with oblique geomin rotation was used to identify latent factors among the psychosocial measures. Multi-group comparisons of the EFA model were conducted using exploratory structural equation modeling to test for measurement invariance across race and sex subgroups. A factor-based scale score was created for invariant factor(s). Logistic regression was used to test the relationship between the factor score(s) and CHD adjusting for relevant confounders. Effect modification of the relationship by race–sex subgroup was tested. A two-factor model fit the data well (comparative fit index = 0.986; Tucker–Lewis index = 0.969; root mean square error of approximation = 0.039). Depressive symptoms, neuroticism, perceived stress, and low life satisfaction loaded on Factor I. Social engagement, spirituality, social networks, and extraversion loaded on Factor II. Only Factor I, re-named distress, showed measurement invariance across subgroups. Distress was associated with a 37% increased odds of self-reported CHD (odds ratio: 1.37; 95% confidence intervals: 1.25, 1.50; p-value < 0.0001). This effect did not differ by race or sex (interaction p-value = 0.43). This study identified two underlying latent constructs among a large range of psychosocial variables; only one, distress, was validly measured across race–sex subgroups. This construct was robustly related to prevalent CHD, highlighting the potential importance of latent constructs as predictors of cardiovascular disease. PMID:22347196
Assigning Cases to Groups Using Taxometric Results: An Empirical Comparison of Classification Techniques

ERIC Educational Resources Information Center

Ruscio, John

2009-01-01

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…
Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications

PubMed Central

Tao, Chenyang; Nichols, Thomas E.; Hua, Xue; Ching, Christopher R.K.; Rolls, Edmund T.; Thompson, Paul M.; Feng, Jianfeng

2017-01-01

We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches. PMID:27666385
Variation in working memory capacity, fluid intelligence, and episodic recall: a latent variable examination of differences in the dynamics of free recall.

PubMed

Unsworth, Nash

2009-09-01

A latent variable analysis was conducted to examine the nature of individual differences in the dynamics of free recall and cognitive abilities. Participants performed multiple measures of free recall, working memory capacity (WMC), and fluid intelligence (gF). For each free recall task, recall accuracy, recall latency, and number of intrusion errors were determined, and latent factors were derived for each. It was found that recall accuracy was negatively related to both recall latency and number of intrusions, and recall latency and number of intrusions were positively related. Furthermore, latent WMC and gF factors were positively related to recall accuracy, but negatively related to recall latency and number of intrusions. Finally, a cluster analysis revealed that subgroups of participants with deficits in focusing the search had deficits in recovering degraded representations or deficits in monitoring the products of retrieval. The results are consistent with the idea that variation in the dynamics of free recall, WMC, and gF are primarily due to differences in search set size, but differences in recovery and monitoring are also important.
The latent structure of the functional dyspepsia symptom complex: a taxometric analysis.

PubMed

Van Oudenhove, L; Jasper, F; Walentynowicz, M; Witthöft, M; Van den Bergh, O; Tack, J

2016-07-01

Rome III introduced a subdivision of functional dyspepsia (FD) into postprandial distress syndrome and epigastric pain syndrome, characterized by early satiation/postprandial fullness, and epigastric pain/burning, respectively. However, evidence on their degree of overlap is mixed. We aimed to investigate the latent structure of FD to test whether distinguishable symptom-based subgroups exist. Consecutive tertiary care Rome II FD patients completed the dyspepsia symptom severity scale. Confirmatory factor analysis (CFA) was used to compare the fit of a single factor model, a correlated three-factor model based on Rome III subgroups and a bifactor model consisting of a general FD factor and orthogonal subgroup factors. Taxometric analyses were subsequently used to investigate the latent structure of FD. Nine hundred and fifty-seven FD patients (71.1% women, age 41 ± 14.8) participated. In CFA, the bifactor model yielded a significantly better fit than the two other models (χ² difference tests both p < 0.001). All symptoms had significant loadings on both the general and the subgroup-specific factors (all p < 0.05). Somatization was associated with the general (r = 0.72, p < 0.01), but not the subgroup-specific factors (all r < 0.13, p > 0.05). Taxometric analyses supported a dimensional structure of FD (all CCFI<0.38). We found a dimensional rather than categorical latent structure of the FD symptom complex in tertiary care. A combination of a general dyspepsia symptom reporting factor, which was associated with somatization, and symptom-specific factors reflecting the Rome III subdivision fitted the data best. This has implications for classification, pathophysiology, and treatment of FD. © 2016 John Wiley & Sons Ltd.
Silent films and strange stories: theory of mind, gender, and social experiences in middle childhood.

PubMed

Devine, Rory T; Hughes, Claire

2013-01-01

In this study of two hundred and thirty 8- to 13-year-olds, a new "Silent Films" task is introduced, designed to address the dearth of research on theory of mind in older children by providing a film-based analogue of F. G. E. Happé's (1994) Strange Stories task. Confirmatory factor analysis showed that all items from both tasks loaded onto a single theory-of-mind latent factor. With effects of verbal ability and family affluence controlled, theory-of-mind latent factor scores increased significantly with age, indicating that mentalizing skills continue to develop through middle childhood. Girls outperformed boys on the theory-of-mind latent factor, and the correlates of individual differences in theory of mind were gender specific: Low scores were related to loneliness in girls and to peer rejection in boys. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Examining Factor Score Distributions to Determine the Nature of Latent Spaces

ERIC Educational Resources Information Center

Steinley, Douglas; McDonald, Roderick P.

2007-01-01

Similarities between latent class models with K classes and linear factor models with K-1 factors are investigated. Specifically, the mathematical equivalence between the covariance structure of the two models is discussed, and a Monte Carlo simulation is performed using generated data that represents both latent factors and latent classes with…
Psychometrican analysis and dimensional structure of the Brazilian version of melasma quality of life scale (MELASQoL-BP)*

PubMed Central

Maranzatto, Camila Fernandes Pollo; Miot, Hélio Amante; Miot, Luciane Donida Bartoli; Meneguin, Silmara

2016-01-01

Background Although asymptomatic, melasma inflicts significant impact on quality of life. MELASQoL is the main instrument used to assess quality of life associated with melasma, it has been validated in several languages, but its latent dimensional structure and psychometric properties haven´t been fully explored. Objectives To evaluate psychometric characteristics, information and dimensional structure of the Brazilian version of MELASQoL. Methods Survey with patients with facial melasma through socio-demographic questionnaire, DLQI-BRA, MASI and MELASQoL-BP, exploratory and confirmatory factor analysis, internal consistency of MELASQoL and latent dimensions (Cronbach's alpha). The informativeness of the model and items were investigated by the Rasch model (ordinal data). Results We evaluated 154 patients, 134 (87%) were female, mean age (± SD) of 39 (± 8) years, the onset of melasma at 27 (± 8) years, median (p25-p75) of MASI scores , DLQI and MELASQoL 8 (5-15) 2 (1-6) and 30 (17-44). The correlation (rho) of MELASQoL with DLQI and MASI were: 0.70 and 0.36. Exploratory factor analysis identified two latent dimensions: Q1-Q3 and Q4-Q10, which had significantly more adjusted factor structure than the one-dimensional model: Χ2 / gl = 2.03, CFI = 0.95, AGFI = 0.94, RMSEA = 0.08. Cronbach's coefficient for the one-dimensional model and the factors were: 0.95, 0.92 and 0.93. Rasch analysis demonstrated that the use of seven alternatives per item resulted in no increase in the model informativeness. Conclusions MELASQoL-BP showed good psychometric performance and a latent structure of two dimensions. We also identified an oversizing of item alternatives to characterize the aggregate information to each dimension. PMID:27579735
Data-driven subtypes of major depressive disorder: a systematic review

PubMed Central

2012-01-01

Background According to current classification systems, patients with major depressive disorder (MDD) may have very different combinations of symptoms. This symptomatic diversity hinders the progress of research into the causal mechanisms and treatment allocation. Theoretically founded subtypes of depression such as atypical, psychotic, and melancholic depression have limited clinical applicability. Data-driven analyses of symptom dimensions or subtypes of depression are scarce. In this systematic review, we examine the evidence for the existence of data-driven symptomatic subtypes of depression. Methods We undertook a systematic literature search of MEDLINE, PsycINFO and Embase in May 2012. We included studies analyzing the depression criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) of adults with MDD in latent variable analyses. Results In total, 1176 articles were retrieved, of which 20 satisfied the inclusion criteria. These reports described a total of 34 latent variable analyses: 6 confirmatory factor analyses, 6 exploratory factor analyses, 12 principal component analyses, and 10 latent class analyses. The latent class techniques distinguished 2 to 5 classes, which mainly reflected subgroups with different overall severity: 62 of 71 significant differences on symptom level were congruent with a latent class solution reflecting severity. The latent class techniques did not consistently identify specific symptom clusters. Latent factor techniques mostly found a factor explaining the variance in the symptoms depressed mood and interest loss (11 of 13 analyses), often complemented by psychomotor retardation or fatigue (8 of 11 analyses). However, differences in found factors and classes were substantial. Conclusions The studies performed to date do not provide conclusive evidence for the existence of depressive symptom dimensions or symptomatic subtypes. The wide diversity of identified factors and classes might result either from the absence of patterns to be found, or from the theoretical and modeling choices preceding analysis. PMID:23210727
Dissociative Experiences are Associated with Obsessive-Compulsive Symptoms in a Non-clinical Sample: A Latent Profile Analysis

PubMed Central

BOYSAN, Murat

2014-01-01

Introduction There has been a burgeoning literature considering the significant associations between obsessive-compulsive symptoms and dissociative experiences. In this study, the relationsips between dissociative symtomotology and dimensions of obsessive-compulsive symptoms were examined in homogeneous sub-groups obtained with latent class algorithm in an undergraduate Turkish sample. Method Latent profile analysis, a recently developed classification method based on latent class analysis, was applied to the Dissociative Experiences Scale (DES) item-response data from 2976 undergraduates. Differences in severity of obsessive-compulsive symptoms, anxiety and depression across groups were evaluated by running multinomial logistic regression analyses. Associations between latent class probabilities and psychological variables in terms of obsessive-compulsive sub-types, anxiety, and depression were assessed by computing Pearson’s product-moment correlation coefficients. Results The findings of the latent profile analysis supported further evidence for discontinuity model of dissociative experiences. The analysis empirically justified the distinction among three sub-groups based on the DES items. A marked proportion of the sample (42%) was assigned to the high dissociative class. In the further analyses, all sub-types of obsessive-compulsive symptoms significantly differed across latent classes. Regarding the relationships between obsessive-compulsive symptoms and dissociative symptomatology, low dissociation appeared to be a buffering factor dealing with obsessive-compulsive symptoms; whereas high dissociation appeared to be significantly associated with high levels of obsessive-compulsive symptoms. Conclusion It is concluded that the concept of dissociation can be best understood in a typological approach that dissociative symptomatology not only exacerbates obsessive-compulsive symptoms but also serves as an adaptive coping mechanism. PMID:28360635
Dissociative Experiences are Associated with Obsessive-Compulsive Symptoms in a Non-clinical Sample: A Latent Profile Analysis.

PubMed

Boysan, Murat

2014-09-01

There has been a burgeoning literature considering the significant associations between obsessive-compulsive symptoms and dissociative experiences. In this study, the relationsips between dissociative symtomotology and dimensions of obsessive-compulsive symptoms were examined in homogeneous sub-groups obtained with latent class algorithm in an undergraduate Turkish sample. Latent profile analysis, a recently developed classification method based on latent class analysis, was applied to the Dissociative Experiences Scale (DES) item-response data from 2976 undergraduates. Differences in severity of obsessive-compulsive symptoms, anxiety and depression across groups were evaluated by running multinomial logistic regression analyses. Associations between latent class probabilities and psychological variables in terms of obsessive-compulsive sub-types, anxiety, and depression were assessed by computing Pearson's product-moment correlation coefficients. The findings of the latent profile analysis supported further evidence for discontinuity model of dissociative experiences. The analysis empirically justified the distinction among three sub-groups based on the DES items. A marked proportion of the sample (42%) was assigned to the high dissociative class. In the further analyses, all sub-types of obsessive-compulsive symptoms significantly differed across latent classes. Regarding the relationships between obsessive-compulsive symptoms and dissociative symptomatology, low dissociation appeared to be a buffering factor dealing with obsessive-compulsive symptoms; whereas high dissociation appeared to be significantly associated with high levels of obsessive-compulsive symptoms. It is concluded that the concept of dissociation can be best understood in a typological approach that dissociative symptomatology not only exacerbates obsessive-compulsive symptoms but also serves as an adaptive coping mechanism.
Clustering of modifiable biobehavioral risk factors for chronic disease in US adults: a latent class analysis.

PubMed

Leventhal, Adam M; Huh, Jimi; Dunton, Genevieve F

2014-11-01

Examining the co-occurrence patterns of modifiable biobehavioral risk factors for deadly chronic diseases (e.g. cancer, cardiovascular disease, diabetes) can elucidate the etiology of risk factors and guide disease-prevention programming. The aims of this study were to (1) identify latent classes based on the clustering of five key biobehavioral risk factors among US adults who reported at least one risk factor and (2) explore the demographic correlates of the identified latent classes. Participants were respondents of the National Epidemiologic Survey of Alcohol and Related Conditions (2004-2005) with at least one of the following disease risk factors in the past year (N = 22,789), which were also the latent class indicators: (1) alcohol abuse/dependence, (2) drug abuse/dependence, (3) nicotine dependence, (4) obesity, and (5) physical inactivity. Housing sample units were selected to match the US National Census in location and demographic characteristics, with young adults oversampled. Participants were administered surveys by trained interviewers. Five latent classes were yielded: 'obese, active non-substance abusers' (23%); 'nicotine-dependent, active, and non-obese' (19%); 'active, non-obese alcohol abusers' (6%); 'inactive, non-substance abusers' (50%); and 'active, polysubstance abusers' (3.7%). Four classes were characterized by a 100% likelihood of having one risk factor coupled with a low or moderate likelihood of having the other four risk factors. The five classes exhibited unique demographic profiles. Risk factors may cluster together in a non-monotonic fashion, with the majority of the at-risk population of US adults expected to have a high likelihood of endorsing only one of these five risk factors. © Royal Society for Public Health 2013.
Evaluating measurement models in clinical research: covariance structure analysis of latent variable models of self-conception.

PubMed

Hoyle, R H

1991-02-01

Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.
What to do When Scalar Invariance Fails: The Extended Alignment Method for Multi-Group Factor Analysis Comparison of Latent Means Across Many Groups.

PubMed

Marsh, Herbert W; Guo, Jiesi; Parker, Philip D; Nagengast, Benjamin; Asparouhov, Tihomir; Muthén, Bengt; Dicke, Theresa

2017-01-12

Scalar invariance is an unachievable ideal that in practice can only be approximated; often using potentially questionable approaches such as partial invariance based on a stepwise selection of parameter estimates with large modification indices. Study 1 demonstrates an extension of the power and flexibility of the alignment approach for comparing latent factor means in large-scale studies (30 OECD countries, 8 factors, 44 items, N = 249,840), for which scalar invariance is typically not supported in the traditional confirmatory factor analysis approach to measurement invariance (CFA-MI). Importantly, we introduce an alignment-within-CFA (AwC) approach, transforming alignment from a largely exploratory tool into a confirmatory tool, and enabling analyses that previously have not been possible with alignment (testing the invariance of uniquenesses and factor variances/covariances; multiple-group MIMIC models; contrasts on latent means) and structural equation models more generally. Specifically, it also allowed a comparison of gender differences in a 30-country MIMIC AwC (i.e., a SEM with gender as a covariate) and a 60-group AwC CFA (i.e., 30 countries × 2 genders) analysis. Study 2, a simulation study following up issues raised in Study 1, showed that latent means were more accurately estimated with alignment than with the scalar CFA-MI, and particularly with partial invariance scalar models based on the heavily criticized stepwise selection strategy. In summary, alignment augmented by AwC provides applied researchers from diverse disciplines considerable flexibility to address substantively important issues when the traditional CFA-MI scalar model does not fit the data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Analysis of the Empathic Concern Subscale of the Emotional Response Questionnaire in a Study Evaluating the Impact of a 3D Cultural Simulation.

PubMed

Everson, Naleya; Levett-Jones, Tracy; Pitt, Victoria; Lapkin, Samuel; Van Der Riet, Pamela; Rossiter, Rachel; Jones, Donovan; Gilligan, Conor; Courtney Pratt, Helen

2018-04-25

Abstract Background Empathic concern has been found to decline in health professional students. Few effective educational programs and a lack of validated scales are reported. Previous analysis of the Empathic Concern scale of the Emotional Response Questionnaire has reported both one and two latent constructs. Aim To evaluate the impact of simulation on nursing students' empathic concern and test the psychometric properties of the Empathic Concern scale. Methods The study used a one group pre-test post-test design with a convenience sample of 460 nursing students. Empathic concern was measured pre-post simulation with the Empathic Concern scale. Factor Analysis was undertaken to investigate the structure of the scale. Results There was a statistically significant increase in Empathic Concern scores between pre-simulation 5.57 (SD = 1.04) and post-simulation 6.10 (SD = 0.95). Factor analysis of the Empathic Concern scale identified one latent dimension. Conclusion Immersive simulation may promote empathic concern. The Empathic Concern scale measured a single latent construct in this cohort.
The Structure of Student Satisfaction with College Services: A Latent Class Model

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph

2011-01-01

Latent Class Analysis (LCA) was used to identify distinct groups of Community college students based on their self-ratings of satisfaction with student service programs. The programs were counseling, financial aid, health center, student programs and student government. The best fitting model to describe the data was a two Discrete-Factor model…
Interactions between lower urinary tract symptoms and cardiovascular risk factors determine distinct patterns of erectile dysfunction: a latent class analysis.

PubMed

Barbosa, João A B A; Muracca, Eduardo; Nakano, Élcio; Assalin, Adriana R; Cordeiro, Paulo; Paranhos, Mario; Cury, José; Srougi, Miguel; Antunes, Alberto A

2013-12-01

An epidemiological association between lower urinary tract symptoms and erectile dysfunction is well established. However, interactions among multiple risk factors and the role of each in pathological mechanisms are not fully elucidated We enrolled 898 men undergoing prostate cancer screening for evaluation with the International Prostate Symptom Score (I-PSS) and simplified International Index of Erectile Function-5 (IIEF-5) questionnaires. Age, race, hypertension, diabetes, dyslipidemia, metabolic syndrome, cardiovascular disease, serum hormones and anthropometric parameters were also evaluated. Risk factors for erectile dysfunction were identified by logistic regression. The 333 men with at least mild to moderate erectile dysfunction (IIEF 16 or less) were included in a latent class model to identify relationships across erectile dysfunction risk factors. Age, hypertension, diabetes, lower urinary tract symptoms and cardiovascular event were independent predictors of erectile dysfunction (p<0.05). We identified 3 latent classes of patients with erectile dysfunction (R2 entropy=0.82). Latent class 1 had younger men at low cardiovascular risk and a moderate/high prevalence of lower urinary tract symptoms. Latent class 2 had the oldest patients at moderate cardiovascular risk with an increased prevalence of lower urinary tract symptoms. Latent class 3 had men of intermediate age with the highest prevalence of cardiovascular risk factors and lower urinary tract symptoms. Erectile dysfunction severity and lower urinary tract symptoms increased from latent class 1 to 3. Risk factor interactions determined different severities of lower urinary tract symptoms and erectile dysfunction. The effect of lower urinary tract symptoms and cardiovascular risk outweighed that of age. While in the youngest patients lower urinary tract symptoms acted as a single risk factor for erectile dysfunction, the contribution of vascular disease resulted in significantly more severe dysfunction. Applying a risk factor interaction model to prospective trials could reveal distinct classes of drug responses and help define optimal treatment strategies for specific groups. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Characterization of dissolved organic matter in Dongjianghu Lake by UV-visible absorption spectroscopy with multivariate analysis.

PubMed

Zhu, Yanzhong; Song, Yonghui; Yu, Huibin; Liu, Ruixia; Liu, Lusan; Lv, Chunjian

2017-08-08

UV-visible absorption spectroscopy coupled with principal component analysis (PCA) and hierarchical cluster analysis (HCA) was applied to characterize spectroscopic components, detect latent factors, and investigate spatial variations of dissolved organic matter (DOM) in a large-scale lake. Twelve surface water samples were collected from Dongjianghu Lake in China. DOM contained lignin and quinine moieties, carboxylic acid, microbial products, and aromatic and alkyl groups, which in the northern part of the lake was largely different from the southern part. Fifteen spectroscopic indices were deduced from the absorption spectra to indicate molecular weight or humification degree of DOM. The northern part of the lake presented the smaller molecular weight or the lower humification degree of DOM than the southern part. E 2/4 , E 3/4 , E 2/3 , and S 2 were latent factors of characterizing the molecular weight of DOM, while E 2/5 , E 3/5 , E 2/6 , E 4/5 , E 3/6 , and A 2/1 were latent factors of evaluating the humification degree of DOM. The UV-visible absorption spectroscopy combined with PCA and HCA may not only characterize DOM fractions of lakes, but may be transferred to other types of waterscape.
Accounting for standard errors of vision-specific latent trait in regression models.

PubMed

Wong, Wan Ling; Li, Xiang; Li, Jialiang; Wong, Tien Yin; Cheng, Ching-Yu; Lamoureux, Ecosse L

2014-07-11

To demonstrate the effectiveness of Hierarchical Bayesian (HB) approach in a modeling framework for association effects that accounts for SEs of vision-specific latent traits assessed using Rasch analysis. A systematic literature review was conducted in four major ophthalmic journals to evaluate Rasch analysis performed on vision-specific instruments. The HB approach was used to synthesize the Rasch model and multiple linear regression model for the assessment of the association effects related to vision-specific latent traits. The effectiveness of this novel HB one-stage "joint-analysis" approach allows all model parameters to be estimated simultaneously and was compared with the frequently used two-stage "separate-analysis" approach in our simulation study (Rasch analysis followed by traditional statistical analyses without adjustment for SE of latent trait). Sixty-six reviewed articles performed evaluation and validation of vision-specific instruments using Rasch analysis, and 86.4% (n = 57) performed further statistical analyses on the Rasch-scaled data using traditional statistical methods; none took into consideration SEs of the estimated Rasch-scaled scores. The two models on real data differed for effect size estimations and the identification of "independent risk factors." Simulation results showed that our proposed HB one-stage "joint-analysis" approach produces greater accuracy (average of 5-fold decrease in bias) with comparable power and precision in estimation of associations when compared with the frequently used two-stage "separate-analysis" procedure despite accounting for greater uncertainty due to the latent trait. Patient-reported data, using Rasch analysis techniques, do not take into account the SE of latent trait in association analyses. The HB one-stage "joint-analysis" is a better approach, producing accurate effect size estimations and information about the independent association of exposure variables with vision-specific latent traits. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.
Characteristics of cyclist crashes in Italy using latent class analysis and association rule mining

PubMed Central

De Angelis, Marco; Marín Puchades, Víctor; Fraboni, Federico; Pietrantoni, Luca

2017-01-01

The factors associated with severity of the bicycle crashes may differ across different bicycle crash patterns. Therefore, it is important to identify distinct bicycle crash patterns with homogeneous attributes. The current study aimed at identifying subgroups of bicycle crashes in Italy and analyzing separately the different bicycle crash types. The present study focused on bicycle crashes that occurred in Italy during the period between 2011 and 2013. We analyzed categorical indicators corresponding to the characteristics of infrastructure (road type, road signage, and location type), road user (i.e., opponent vehicle and cyclist’s maneuver, type of collision, age and gender of the cyclist), vehicle (type of opponent vehicle), and the environmental and time period variables (time of the day, day of the week, season, pavement condition, and weather). To identify homogenous subgroups of bicycle crashes, we used latent class analysis. Using latent class analysis, the bicycle crash data set was segmented into 19 classes, which represents 19 different bicycle crash types. Logistic regression analysis was used to identify the association between class membership and severity of the bicycle crashes. Finally, association rules were conducted for each of the latent classes to uncover the factors associated with an increased likelihood of severity. Association rules highlighted different crash characteristics associated with an increased likelihood of severity for each of the 19 bicycle crash types. PMID:28158296
Interexaminer variation of minutia markup on latent fingerprints.

PubMed

Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn

2016-07-01

Latent print examiners often differ in the number of minutiae they mark during analysis of a latent, and also during comparison of a latent with an exemplar. Differences in minutia counts understate interexaminer variability: examiners' markups may have similar minutia counts but differ greatly in which specific minutiae were marked. We assessed variability in minutia markup among 170 volunteer latent print examiners. Each provided detailed markup documenting their examinations of 22 latent-exemplar pairs of prints randomly assigned from a pool of 320 pairs. An average of 12 examiners marked each latent. The primary factors associated with minutia reproducibility were clarity, which regions of the prints examiners chose to mark, and agreement on value or comparison determinations. In clear areas (where the examiner was "certain of the location, presence, and absence of all minutiae"), median reproducibility was 82%; in unclear areas, median reproducibility was 46%. Differing interpretations regarding which regions should be marked (e.g., when there is ambiguity in the continuity of a print) contributed to variability in minutia markup: especially in unclear areas, marked minutiae were often far from the nearest minutia marked by a majority of examiners. Low reproducibility was also associated with differences in value or comparison determinations. Lack of standardization in minutia markup and unfamiliarity with test procedures presumably contribute to the variability we observed. We have identified factors accounting for interexaminer variability; implementing standards for detailed markup as part of documentation and focusing future training efforts on these factors may help to facilitate transparency and reduce subjectivity in the examination process. Published by Elsevier Ireland Ltd.
Predicting Viral Infection From High-Dimensional Biomarker Trajectories

PubMed Central

Chen, Minhua; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S.; Lucas, Joseph; Dunson, David; Carin, Lawrence

2013-01-01

There is often interest in predicting an individual’s latent health status based on high-dimensional biomarkers that vary over time. Motivated by time-course gene expression array data that we have collected in two influenza challenge studies performed with healthy human volunteers, we develop a novel time-aligned Bayesian dynamic factor analysis methodology. The time course trajectories in the gene expressions are related to a relatively low-dimensional vector of latent factors, which vary dynamically starting at the latent initiation time of infection. Using a nonparametric cure rate model for the latent initiation times, we allow selection of the genes in the viral response pathway, variability among individuals in infection times, and a subset of individuals who are not infected. As we demonstrate using held-out data, this statistical framework allows accurate predictions of infected individuals in advance of the development of clinical symptoms, without labeled data and even when the number of biomarkers vastly exceeds the number of individuals under study. Biological interpretation of several of the inferred pathways (factors) is provided. PMID:23704802
A systematic literature review of PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders: DSM-IV to DSM-5.

PubMed

Armour, Cherie; Műllerová, Jana; Elhai, Jon D

2016-03-01

The factor structure of posttraumatic stress disorder (PTSD) has been widely researched, but consensus regarding the exact number and nature of factors is yet to be reached. The aim of the current study was to systematically review the extant literature on PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders (DSM) in order to identify the best-fitting model. One hundred and twelve research papers published after 1994 using confirmatory factor analysis and DSM-based measures of PTSD were included in the review. In the DSM-IV literature, four-factor models received substantial support, but the five-factor Dysphoric arousal model demonstrated the best fit, regardless of gender, measurement instrument or trauma type. The recently proposed DSM-5 PTSD model was found to be a good representation of PTSD's latent structure, but studies analysing the six- and seven-factor models suggest that the DSM-5 PTSD factor structure may need further alterations. Copyright © 2015 Elsevier Ltd. All rights reserved.
Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling.

PubMed

Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry

2013-06-01

The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Analyzing the Validity of the Adult-Adolescent Parenting Inventory for Low-Income Populations

ERIC Educational Resources Information Center

Lawson, Michael A.; Alameda-Lawson, Tania; Byrnes, Edward

2017-01-01

Objectives: The purpose of this study was to examine the construct and predictive validity of the Adult-Adolescent Parenting Inventory (AAPI-2). Methods: The validity of the AAPI-2 was evaluated using multiple statistical methods, including exploratory factor analysis, confirmatory factor analysis, and latent class analysis. These analyses were…
Connections between Graphical Gaussian Models and Factor Analysis

ERIC Educational Resources Information Center

Salgueiro, M. Fatima; Smith, Peter W. F.; McDonald, John W.

2010-01-01

Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations…

Comparison of Suicide Attempters and Decedents in the U.S. Army: A Latent Class Analysis.

PubMed

Skopp, Nancy A; Smolenski, Derek J; Sheppard, Sean C; Bush, Nigel E; Luxton, David D

2016-08-01

A clearer understanding of risk factors for suicidal behavior among soldiers is of principal importance to military suicide prevention. It is unclear whether soldiers who attempt suicide and those who die by suicide have different patterns of risk factors. As such, preventive efforts aimed toward reducing suicide attempts and suicides, respectively, may require different strategies. We conducted a latent class analysis (LCA) to examine classes of risk factors among suicide attempters (n = 1,433) and decedents (n = 424). Both groups were represented by three classes: (1) External/Antisocial Risk Factors, (2) Mental Health Risk Factors, and (3) No Pattern. These findings support the conceptualization that military suicide attempters and decedents represent a single population. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
The Recoverability of P-Technique Factor Analysis

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

2009-01-01

It seems that just when we are about to lay P-technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables--dynamic factor models--it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even…
Community Violence, Protective Factors, and Adolescent Mental Health: A Profile Analysis

ERIC Educational Resources Information Center

Copeland-Linder, Nikeea; Lambert, Sharon F.; Ialongo, Nicholas S.

2010-01-01

This study examined interrelationships among community violence exposure, protective factors, and mental health in a sample of urban, predominantly African American adolescents (N = 504). Latent Profile Analysis was conducted to identify profiles of adolescents based on a combination of community violence exposure, self-worth, parental monitoring,…
Dynamic Factor Analysis of Nonstationary Multivariate Time Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; And Others

1992-01-01

The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)
Effects of additional data on Bayesian clustering.

PubMed

Yamazaki, Keisuke

2017-10-01

Hierarchical probabilistic models, such as mixture models, are used for cluster analysis. These models have two types of variables: observable and latent. In cluster analysis, the latent variable is estimated, and it is expected that additional information will improve the accuracy of the estimation of the latent variable. Many proposed learning methods are able to use additional data; these include semi-supervised learning and transfer learning. However, from a statistical point of view, a complex probabilistic model that encompasses both the initial and additional data might be less accurate due to having a higher-dimensional parameter. The present paper presents a theoretical analysis of the accuracy of such a model and clarifies which factor has the greatest effect on its accuracy, the advantages of obtaining additional data, and the disadvantages of increasing the complexity. Copyright © 2017 Elsevier Ltd. All rights reserved.
The Latent Structures of the Learning and Study Strategies Inventory (LASSI): A Comparative Analysis.

ERIC Educational Resources Information Center

Obiekwe, Jerry C.

The first purpose of this study was to analyze the results of the confirmatory factor analyses, via EQS, with regard to the latent structures of the Learning and Study Strategies Inventory (LASSI) (C. Weinstein, D. Palmer, and A. Schulte, 1987) as proposed by S. Olejnik and S. Nist (1992), A. Olivarez and M. Tallent-Runnels (1994), B. Olaussen and…
Configurations of Common Childhood Psychosocial Risk Factors

ERIC Educational Resources Information Center

Copeland, William; Shanahan, Lilly; Costello, E. Jane; Angold, Adrian

2009-01-01

Background: Co-occurrence of psychosocial risk factors is commonplace, but little is known about psychiatrically-predictive configurations of psychosocial risk factors. Methods: Latent class analysis (LCA) was applied to 17 putative psychosocial risk factors in a representative population sample of 920 children ages 9 to 17. The resultant class…
Causal Indicators Can Help to Interpret Factors

ERIC Educational Resources Information Center

Bentler, Peter M.

2016-01-01

The latent factor in a causal indicator model is no more than the latent factor of the factor part of the model. However, if the causal indicator variables are well-understood and help to improve the prediction of individuals' factor scores, they can help to interpret the meaning of the latent factor. Aguirre-Urreta, Rönkkö, and Marakas (2016)…
Refining the tobacco dependence phenotype using the Wisconsin Inventory of Smoking Dependence Motives (WISDM)

PubMed Central

Piper, Megan E.; Bolt, Daniel M.; Kim, Su-Young; Japuntich, Sandra J.; Smith, Stevens S.; Niederdeppe, Jeff; Cannon, Dale S.; Baker, Timothy B.

2008-01-01

The construct of tobacco dependence is important from both scientific and public health perspectives, but it is poorly understood. The current research integrates person-centered analyses (e.g., latent profile analysis) and variable-centered analyses (e.g., exploratory factor analysis) to understand better the latent structure of dependence and to guide distillation of the phenotype. Using data from four samples of smokers (including treatment and non-treatment samples), latent profiles were derived using the Wisconsin Inventory of Smoking Dependence Motives (WISDM) subscale scores. Across all four samples, results revealed a unique latent profile that had relative elevations on four dependence motive subscales (Automaticity, Craving, Loss of Control, and Tolerance). Variable-centered analyses supported the uniqueness of these four subscales both as measures of a common factor distinct from that underlying the other nine subscales, and as the strongest predictors of relapse, withdrawal and other dependence criteria. Conversely, the remaining nine motives carried little unique predictive validity regarding dependence. Applications of a factor mixture model further support the presence of a unique class of smokers in relation to a common factor underlying the four subscales. The results illustrate how person-centered analyses may be useful as a supplement to variable-centered analyses for uncovering variables that are necessary and/or sufficient predictors of disorder criteria, as they may uncover small segments of a population in which the variables are uniquely distributed. The results also suggest that severe dependence is associated with a pattern of smoking that is heavy, pervasive, automatic and relatively unresponsive to instrumental contingencies. PMID:19025223
Validating the European Health Literacy Survey Questionnaire in people with type 2 diabetes: Latent trait analyses applying multidimensional Rasch modelling and confirmatory factor analysis.

PubMed

Finbråten, Hanne Søberg; Pettersen, Kjell Sverre; Wilde-Larsson, Bodil; Nordström, Gun; Trollvik, Anne; Guttersrud, Øystein

2017-11-01

To validate the European Health Literacy Survey Questionnaire (HLS-EU-Q47) in people with type 2 diabetes mellitus. The HLS-EU-Q47 latent variable is outlined in a framework with four cognitive domains integrated in three health domains, implying 12 theoretically defined subscales. Valid and reliable health literacy measurers are crucial to effectively adapt health communication and education to individuals and groups of patients. Cross-sectional study applying confirmatory latent trait analyses. Using a paper-and-pencil self-administered approach, 388 adults responded in March 2015. The data were analysed using the Rasch methodology and confirmatory factor analysis. Response violation (response dependency) and trait violation (multidimensionality) of local independence were identified. Fitting the "multidimensional random coefficients multinomial logit" model, 1-, 3- and 12-dimensional Rasch models were applied and compared. Poor model fit and differential item functioning were present in some items, and several subscales suffered from poor targeting and low reliability. Despite multidimensional data, we did not observe any unordered response categories. Interpreting the domains as distinct but related latent dimensions, the data fit a 12-dimensional Rasch model and a 12-factor confirmatory factor model best. Therefore, the analyses did not support the estimation of one overall "health literacy score." To support the plausibility of claims based on the HLS-EU score(s), we suggest: removing the health care aspect to reduce the magnitude of multidimensionality; rejecting redundant items to avoid response dependency; adding "harder" items and applying a six-point rating scale to improve subscale targeting and reliability; and revising items to improve model fit and avoid bias owing to person factors. © 2017 John Wiley & Sons Ltd.
Rotation Criteria and Hypothesis Testing for Exploratory Factor Analysis: Implications for Factor Pattern Loadings and Interfactor Correlations

ERIC Educational Resources Information Center

Schmitt, Thomas A.; Sass, Daniel A.

2011-01-01

Exploratory factor analysis (EFA) has long been used in the social sciences to depict the relationships between variables/items and latent traits. Researchers face many choices when using EFA, including the choice of rotation criterion, which can be difficult given that few research articles have discussed and/or demonstrated their differences.…
Exploring the Latent Structure of the Luria Model for the KABC-II at School Age: Further Insights from Confirmatory Factor Analysis

ERIC Educational Resources Information Center

McGill, Ryan J.

2017-01-01

The present study examined the factor structure of the Luria interpretive model for the Kaufman Assessment Battery for Children-Second Edition (KABC-II) with normative sample participants aged 7-18 (N = 2,025) using confirmatory factor analysis with maximum-likelihood estimation. For the eight subtest Luria configuration, an alternative…
Multivariate analysis of fears in dental phobic patients according to a reduced FSS-II scale.

PubMed

Hakeberg, M; Gustafsson, J E; Berggren, U; Carlsson, S G

1995-10-01

This study analyzed and assessed dimensions of a questionnaire developed to measure general fears and phobias. A previous factor analysis among 109 dental phobics had revealed a five-factor structure with 22 items and an explained total variance of 54%. The present study analyzed the same material using a multivariate statistical procedure (LISREL) to reveal structural latent variables. The LISREL analysis, based on the correlation matrix, yielded a chi-square of 216.6 with 195 degrees of freedom (P = 0.138) and showed a model with seven latent variables. One was a general fear factor correlated to all 22 items. The other six factors concerned "Illness & Death" (5 items), "Failures & Embarrassment" (5 items), "Social situations" (5 items), "Physical injuries" (4 items), "Animals & Natural phenomena" (4 items). One item (opposite sex) was included in both "Failures & Embarrassment" and "Social situations". The last factor, "Social interaction", combined all the items in "Failures & Embarrassment" and "Social situations" (9 items). In conclusion, this multivariate statistical analysis (LISREL) revealed and confirmed a factor structure similar to our previous study, but added two important dimensions not shown with a traditional factor analysis. This reduced FSS-II version measures general fears and phobias and may be used on a routine clinical basis as well as in dental phobia research.
Friendship Group Composition and Juvenile Institutional Misconduct.

PubMed

Reid, Shannon E

2017-02-01

The present study examines both the patterns of friendship networks and how these network characteristics relate to the risk factors of institutional misconduct for incarcerated youth. Using friendship networks collected from males incarcerated with California's Division of Juvenile Justice (DJJ), latent profile analysis was utilized to create homogeneous groups of friendship patterns based on alter attributes and network structure. The incarcerated youth provided 144 egocentric networks reporting 558 social network relationships. Latent profile analysis identified three network profiles: expected group (67%), new breed group (20%), and model citizen group (13%). The three network profiles were integrated into a multiple group analysis framework to examine the relative influence of individual-level risk factors on their rate of institutional misconduct. The analysis finds variation in predictors of institutional misconduct across profile types. These findings suggest that the close friendships of incarcerated youth are patterned across the individual characteristics of the youth's friends and that the friendship network can act as a moderator for individual risk factors for institutional misconduct.
Measurement Invariance and Latent Mean Differences in the Reynolds Intellectual Assessment Scales (RIAS): Does the German Version of the RIAS Allow a Valid Assessment of Individuals with a Migration Background?

PubMed Central

Gygi, Jasmin T.; Fux, Elodie; Grob, Alexander; Hagmann-von Arx, Priska

2016-01-01

This study examined measurement invariance and latent mean differences in the German version of the Reynolds Intellectual Assessment Scales (RIAS) for 316 individuals with a migration background (defined as speaking German as a second language) and 316 sex- and age-matched natives. The RIAS measures general intelligence (single-factor structure) and its two components, verbal and nonverbal intelligence (two-factor structure). Results of a multi-group confirmatory factor analysis showed scalar invariance for the two-factor and partial scalar invariance for the single-factor structure. We conclude that the two-factor structure of the RIAS is comparable across groups. Hence, verbal and nonverbal intelligence but not general intelligence should be considered when comparing RIAS test results of individuals with and without a migration background. Further, latent mean differences especially on the verbal, but also on the nonverbal intelligence index indicate language barriers for individuals with a migration background, as subtests corresponding to verbal intelligence require higher skills in German language. Moreover, cultural, environmental, and social factors that have to be taken into account when assessing individuals with a migration background are discussed. PMID:27846270
Semiparametric Time-to-Event Modeling in the Presence of a Latent Progression Event

PubMed Central

Rice, John D.; Tsodikov, Alex

2017-01-01

Summary In cancer research, interest frequently centers on factors influencing a latent event that must precede a terminal event. In practice it is often impossible to observe the latent event precisely, making inference about this process difficult. To address this problem, we propose a joint model for the unobserved time to the latent and terminal events, with the two events linked by the baseline hazard. Covariates enter the model parametrically as linear combinations that multiply, respectively, the hazard for the latent event and the hazard for the terminal event conditional on the latent one. We derive the partial likelihood estimators for this problem assuming the latent event is observed, and propose a profile likelihood–based method for estimation when the latent event is unobserved. The baseline hazard in this case is estimated nonparametrically using the EM algorithm, which allows for closed-form Breslow-type estimators at each iteration, bringing improved computational efficiency and stability compared with maximizing the marginal likelihood directly. We present simulation studies to illustrate the finite-sample properties of the method; its use in practice is demonstrated in the analysis of a prostate cancer data set. PMID:27556886
Semiparametric time-to-event modeling in the presence of a latent progression event.

PubMed

Rice, John D; Tsodikov, Alex

2017-06-01

In cancer research, interest frequently centers on factors influencing a latent event that must precede a terminal event. In practice it is often impossible to observe the latent event precisely, making inference about this process difficult. To address this problem, we propose a joint model for the unobserved time to the latent and terminal events, with the two events linked by the baseline hazard. Covariates enter the model parametrically as linear combinations that multiply, respectively, the hazard for the latent event and the hazard for the terminal event conditional on the latent one. We derive the partial likelihood estimators for this problem assuming the latent event is observed, and propose a profile likelihood-based method for estimation when the latent event is unobserved. The baseline hazard in this case is estimated nonparametrically using the EM algorithm, which allows for closed-form Breslow-type estimators at each iteration, bringing improved computational efficiency and stability compared with maximizing the marginal likelihood directly. We present simulation studies to illustrate the finite-sample properties of the method; its use in practice is demonstrated in the analysis of a prostate cancer data set. © 2016, The International Biometric Society.
Environmental, morphological, and productive characterization of Sardinian goats and use of latent explanatory factors for population analysis.

PubMed

Vacca, G M; Paschino, P; Dettori, M L; Bergamaschi, M; Cipolat-Gotet, C; Bittante, G; Pazzola, M

2016-09-01

Dairy goat farming is practiced worldwide, within a range of different farming systems. Here we investigated the effects of environmental factors and morphology on milk traits of the Sardinian goat population. Sardinian goats are currently reared in Sardinia (Italy) in a low-input context, similar to many goat farming systems, especially in developing countries. Milk and morphological traits from 1,050 Sardinian goats from 42 farms were recorded. We observed a high variability regarding morphological traits, such as coat color, ear length and direction, horn presence, and udder shape. Such variability derived partly from the unplanned repeated crossbreeding of the native Sardinian goats with exotic breeds, especially Maltese goats. The farms located in the mountains were characterized by the traditional farming system and the lowest percentage of crossbred goats. Explanatory factors analysis was used to summarize the interrelated measured milk variables. The explanatory factor related to fat, protein, and energy content of milk (the "Quality" latent variable) explained about 30% of the variance of the whole data set of measured milk traits followed by the "Hygiene" (19%), "Production" (19%), and "Acidity" (11%) factors. The "Quality" and "Hygiene" factors were not affected by any of the farm classification items, whereas "Production" and "Acidity" were affected only by altitude and size of herds, respectively, indicating the adaptation of the local goat population to different environmental conditions. The use of latent explanatory factor analysis allowed us to clearly explain the large variability of milk traits, revealing that the Sardinian goat population cannot be divided into subpopulations based on milk attitude The factors, properly integrated with genetic data, may be useful tools in future selection programs.
The Peer Interaction in Primary School Questionnaire: Testing for Measurement Equivalence and Latent Mean Differences in Bullying between Gender in Egypt, Saudi Arabia and the USA

ERIC Educational Resources Information Center

Hussein, Mohamed Habashy

2010-01-01

The Peer Interaction in Primary School Questionnaire (PIPSQ) was developed to assess individuals' levels of bullying and victimization. This study used the approach of latent means analysis (LMA) within the framework of structural equation modeling (SEM) to explore the factor structure and gender differences associated with the PIPSQ in a sample…
Parent and Child Personality Traits and Children's Externalizing Problem Behavior from Age 4 to 9 Years: A Cohort-Sequential Latent Growth Curve Analysis

ERIC Educational Resources Information Center

Prinzie, P.; Onghena, P.; Hellinckx, W.

2005-01-01

Cohort-sequential latent growth modeling was used to analyze longitudinal data for children's externalizing behavior from four overlapping age cohorts (4, 5, 6, and 7 years at first assessment) measured at three annual time points. The data included mother and father ratings on the Child Behavior Checklist and the Five-Factor Personality Inventory…

The Influence of Static and Dynamic Intrapersonal Factors on Longitudinal Patterns of Peer Victimization through Mid-adolescence: a Latent Transition Analysis.

PubMed

Haltigan, John D; Vaillancourt, Tracy

2018-01-01

Using 6 cycles (grade 5 through grade 10) of data obtained from a large prospective sample of Canadian school children (N = 700; 52.6% girls), we replicated previous findings concerning the empirical definition of peer victimization (i.e., being bullied) and examined static and dynamic intrapersonal factors associated with its emergence and experiential continuity through mid-adolescence. Latent class analyses consistently revealed a low victimization and an elevated victimization class across time, supporting previous work suggesting peer victimization was defined by degree rather than by type (e.g., physical). Using latent transition analyses (LTA), we found that child sex, parent-perceived pubertal development, and internalizing symptoms influenced the probability of transitioning from the low to the elevated victimization class across time. Higher-order extensions within the LTA modeling framework revealed a lasting effect of grade 5 victimization status on grade 10 victimization status and a large effect of chronic victimization on later parent-reported youth internalizing symptoms (net of prior parent-reported internalizing symptoms) in later adolescence (grade 11). Implications of the current findings for the experience of peer victimization, as well as the application of latent transition analysis as a useful approach for peer victimization research, are discussed.
Understanding the Support Needs of People with Intellectual and Related Developmental Disabilities through Cluster Analysis and Factor Analysis of Statewide Data

ERIC Educational Resources Information Center

Viriyangkura, Yuwadee

2014-01-01

Through a secondary analysis of statewide data from Colorado, people with intellectual and related developmental disabilities (ID/DD) were classified into five clusters based on their support needs characteristics using cluster analysis techniques. Prior latent factor models of support needs in the field of ID/DD were examined to investigate the…
Revealing unobserved factors underlying cortical activity with a rectified latent variable model applied to neural population recordings.

PubMed

Whiteway, Matthew R; Butts, Daniel A

2017-03-01

The activity of sensory cortical neurons is not only driven by external stimuli but also shaped by other sources of input to the cortex. Unlike external stimuli, these other sources of input are challenging to experimentally control, or even observe, and as a result contribute to variability of neural responses to sensory stimuli. However, such sources of input are likely not "noise" and may play an integral role in sensory cortex function. Here we introduce the rectified latent variable model (RLVM) in order to identify these sources of input using simultaneously recorded cortical neuron populations. The RLVM is novel in that it employs nonnegative (rectified) latent variables and is much less restrictive in the mathematical constraints on solutions because of the use of an autoencoder neural network to initialize model parameters. We show that the RLVM outperforms principal component analysis, factor analysis, and independent component analysis, using simulated data across a range of conditions. We then apply this model to two-photon imaging of hundreds of simultaneously recorded neurons in mouse primary somatosensory cortex during a tactile discrimination task. Across many experiments, the RLVM identifies latent variables related to both the tactile stimulation as well as nonstimulus aspects of the behavioral task, with a majority of activity explained by the latter. These results suggest that properly identifying such latent variables is necessary for a full understanding of sensory cortical function and demonstrate novel methods for leveraging large population recordings to this end. NEW & NOTEWORTHY The rapid development of neural recording technologies presents new opportunities for understanding patterns of activity across neural populations. Here we show how a latent variable model with appropriate nonlinear form can be used to identify sources of input to a neural population and infer their time courses. Furthermore, we demonstrate how these sources are related to behavioral contexts outside of direct experimental control. Copyright © 2017 the American Physiological Society.
An Item Response Theory Analysis of DSM–IV Diagnostic Criteria for Personality Disorders: Findings From the National Epidemiologic Survey on Alcohol and Related Conditions

PubMed Central

Harford, Thomas C.; Chen, Chiung M.; Saha, Tulshi D.; Smith, Sharon M.; Hasin, Deborah S.; Grant, Bridget F.

2013-01-01

The purpose of this study was to evaluate the psychometric properties of DSM–IV symptom criteria for assessing personality disorders (PDs) in a national population and to compare variations in proposed symptom coding for social and/or occupational dysfunction. Data were obtained from a total sample of 34,653 respondents from Waves 1 and 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). For each personality disorder, confirmatory factor analysis (CFA) established a 1-factor latent factor structure for the respective symptom criteria. A 2-parameter item response theory (IRT) model was applied to the symptom criteria for each PD to assess the probabilities of symptom item endorsements across different values of the underlying trait (latent factor). Findings were compared with a separate IRT model using an alternative coding of symptom criteria that requires distress/impairment to be related to each criterion. The CFAs yielded a good fit for a single underlying latent dimension for each PD. Findings from the IRT indicated that DSM–IV PD symptom criteria are clustered in the moderate to severe range of the underlying latent dimension for each PD and are peaked, indicating high measurement precision only within a narrow range of the underlying trait and lower measurement precision at lower and higher levels of severity. Compared with the NESARC symptom coding, the IRT results for the alternative symptom coding are shifted toward the more severe range of the latent trait but generally have lower measurement precision for each PD. The IRT findings provide support for a reliable assessment of each PD for both NESARC and alternative coding for distress/impairment. The use of symptom dysfunction for each criterion, however, raises a number of issues and implications for the DSM-5 revision currently proposed for Axis II disorders (American Psychiatric Association, 2010). PMID:22449066
Primary Energy Efficiency Analysis of Different Separate Sensible and Latent Cooling Techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abdelaziz, Omar

2015-01-01

Separate Sensible and Latent cooling (SSLC) has been discussed in open literature as means to improve air conditioning system efficiency. The main benefit of SSLC is that it enables heat source optimization for the different forms of loads, sensible vs. latent, and as such maximizes the cycle efficiency. In this paper I use a thermodynamic analysis tool in order to analyse the performance of various SSLC technologies including: multi-evaporators two stage compression system, vapour compression system with heat activated desiccant dehumidification, and integrated vapour compression with desiccant dehumidification. A primary coefficient of performance is defined and used to judge themore » performance of the different SSLC technologies at the design conditions. Results showed the trade-off in performance for different sensible heat factor and regeneration temperatures.« less
The use of fault reporting of medical equipment to identify latent design flaws.

PubMed

Flewwelling, C J; Easty, A C; Vicente, K J; Cafazzo, J A

2014-10-01

Poor device design that fails to adequately account for user needs, cognition, and behavior is often responsible for use errors resulting in adverse events. This poor device design is also often latent, and could be responsible for "No Fault Found" (NFF) reporting, in which medical devices sent for repair by clinical users are found to be operating as intended. Unresolved NFF reports may contribute to incident under reporting, clinical user frustration, and biomedical engineering technologist inefficacy. This study uses human factors engineering methods to investigate the relationship between NFF reporting frequency and device usability. An analysis of medical equipment maintenance data was conducted to identify devices with a high NFF reporting frequency. Subsequently, semi-structured interviews and heuristic evaluations were performed in order to identify potential usability issues. Finally, usability testing was conducted in order to validate that latent usability related design faults result in a higher frequency of NFF reporting. The analysis of medical equipment maintenance data identified six devices with a high NFF reporting frequency. Semi-structured interviews, heuristic evaluations and usability testing revealed that usability issues caused a significant portion of the NFF reports. Other factors suspected to contribute to increased NFF reporting include accessory issues, intermittent faults and environmental issues. Usability testing conducted on three of the devices revealed 23 latent usability related design faults. These findings demonstrate that latent usability related design faults manifest themselves as an increase in NFF reporting and that devices containing usability related design faults can be identified through an analysis of medical equipment maintenance data. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Subgroups of Dutch homeless young adults based on risk- and protective factors for quality of life: Results of a latent class analysis.

PubMed

Altena, Astrid M; Beijersbergen, Mariëlle D; Vermunt, Jeroen K; Wolf, Judith R L M

2018-04-17

It is important to gain more insight into specific subgroups of homeless young adults (HYA) to enable the development of tailored interventions that adequately meet their diverse needs and to improve their quality of life. Within a heterogeneous sample of HYA, we investigated whether subgroups are distinguishable based on risk- and protective factors for quality of life. In addition, differences between subgroups were examined regarding the socio-demographic characteristics, the use of cognitive coping strategies and quality of life. A total of 393 HYA using shelter facilities in the Netherlands were approached to participate, between December 2011 and March 2013. Structured face-to-face interviews were administered approximately 2 weeks after shelter admission by trained research assistants. A latent class analysis was conducted to empirically distinguish 251 HYA in subgroups based on common risk factors (former abuse, victimisation, psychological symptoms and substance use) and protective factors (resilience, family and social support and perceived health status). Additional analysis of variance and chi-square tests were used to compare subgroups on socio-demographic characteristics, the use of cognitive coping strategies and quality of life. The latent class analysis yielded four highly interpretable subgroups: the at-risk subgroup, the high-risk and least protected subgroup, the low-risk subgroup and the higher functioning and protected subgroup. Subgroups of HYA with lower scores in risk factors showed higher scores in protective factors, the adaptive cognitive coping strategies and quality of life. Our findings confirm the need for targeted and tailored interventions for specific subgroups of HYA. Social workers need to be attentive to the pattern of risk- and protective factors in each individual to determine which risk factors are prominent and need to be targeted and which protective factors need to be enhanced to improve the quality of life of HYA. © 2018 John Wiley & Sons Ltd.
Pathological grooming: Evidence for a single factor behind trichotillomania, skin picking and nail biting

PubMed Central

Hende, Borbála; Urbán, Róbert; Demetrovics, Zsolt

2017-01-01

Although trichotillomania (TTM), skin picking (SP), and nail biting (NB) have been receiving growing scientific attention, the question as to whether these disorders can be regarded as separate entities or they are different manifestations of the same underlying tendency is unclear. Data were collected online in a community survey, yielding a sample of 2705 participants (66% women, mean age: 29.1, SD: 8.6). Hierarchical factor analysis was used to identify a common latent factor and the multiple indicators and multiple causes (MIMIC) modelling was applied to test the predictive effect of borderline personality disorder symptoms, impulsivity, distress and self-esteem on pathological grooming. Pearson correlation coefficients between TTM, SP and NB were between 0.13 and 0.29 (p < 0.01). The model yielded an excellent fit to the data (CFI = 0.992, TLI = 0.991, χ2 = 696.65, p < 0.001, df = 222, RMSEA = 0.030, Cfit of RMSEA = 1.000), supporting the existence of a latent factor. The MIMIC model indicated an adequate fit (CFI = 0.993, TLI = 0.992, χ2 = 655.8, p < 0.001, df = 307, RMSEA = 0.25, CI: 0.022–0.028, pclose = 1.000). TTM, SP and NB each were loaded significantly on the latent factor, indicating the presence of a general grooming factor. Impulsivity, psychiatric distress and contingent self-esteem had significant predictive effects, whereas borderline personality disorder had a nonsignificant predictive effect on the latent factor. We found evidence that the category of pathological grooming is meaningful and encompasses three symptom manifestations: trichotillomania, skin picking and nail biting. This latent underlying factor is not better explained by indicators of psychopathology, which supports the notion that the urge to self-groom, rather than general psychiatric distress, impulsivity, self-esteem or borderline symptomatology, is what drives individual grooming behaviours. PMID:28902896
Ethnic differences in longitudinal latent verbal profiles in the millennium cohort study.

PubMed

Zilanawala, Afshin; Kelly, Yvonne; Sacker, Amanda

2016-12-01

Development of verbal skills during early childhood and school age years is consequential for children's educational achievement and adult outcomes. We examine ethnic differences in longitudinal latent verbal profiles and assess the contribution of family process and family resource factors to observed differences. Using data from the UK Millennium Cohort Study and the latent profile analysis, we estimate longitudinal latent verbal profiles using verbal skills measured 4 times from age 3-11 years. We investigate the odds of verbal profiles by ethnicity (reported in infancy), and the extent observed differences are mediated by the home learning environment, family routines, and psychosocial environment (measured at age 3). Indian children were twice as likely (OR = 2.14, CI: 1.37-3.33) to be in the high achieving profile, compared to White children. Socioeconomic markers attenuated this advantage to nonsignificance. Pakistani and Bangladeshi children were significantly more likely to be in the low performing group (OR = 2.23, CI: 1.61-3.11; OR = 3.37, CI: 2.20-5.17, respectively). Socioeconomic and psychosocial factors had the strongest mediating influence on the association between lower achieving profiles and Pakistani children, whereas for Bangladeshi children, there was mediation by the home learning environment, family routines, and psychosocial factors. Family process and resource factors explain ethnic differences in longitudinal latent verbal profiles. Family resources explain verbal advantages for Indian children, whereas a range of home environment and socioeconomic factors explain disparities for Pakistani and Bangladeshi children. Future policy initiatives focused on reducing ethnic disparities in children's development should consider supporting and enhancing family resources and processes. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association.
Ethnic differences in longitudinal latent verbal profiles in the millennium cohort study*

PubMed Central

Kelly, Yvonne; Sacker, Amanda

2016-01-01

Background: Development of verbal skills during early childhood and school age years is consequential for children’s educational achievement and adult outcomes. We examine ethnic differences in longitudinal latent verbal profiles and assess the contribution of family process and family resource factors to observed differences. Methods: Using data from the UK Millennium Cohort Study and the latent profile analysis, we estimate longitudinal latent verbal profiles using verbal skills measured 4 times from age 3–11 years. We investigate the odds of verbal profiles by ethnicity (reported in infancy), and the extent observed differences are mediated by the home learning environment, family routines, and psychosocial environment (measured at age 3). Results: Indian children were twice as likely (OR = 2.14, CI: 1.37–3.33) to be in the high achieving profile, compared to White children. Socioeconomic markers attenuated this advantage to nonsignificance. Pakistani and Bangladeshi children were significantly more likely to be in the low performing group (OR = 2.23, CI: 1.61–3.11; OR = 3.37, CI: 2.20–5.17, respectively). Socioeconomic and psychosocial factors had the strongest mediating influence on the association between lower achieving profiles and Pakistani children, whereas for Bangladeshi children, there was mediation by the home learning environment, family routines, and psychosocial factors. Conclusion: Family process and resource factors explain ethnic differences in longitudinal latent verbal profiles. Family resources explain verbal advantages for Indian children, whereas a range of home environment and socioeconomic factors explain disparities for Pakistani and Bangladeshi children. Future policy initiatives focused on reducing ethnic disparities in children’s development should consider supporting and enhancing family resources and processes. PMID:27999155
Latent Factor Structure of the Das-Naglieri Cognitive Assessment System: A Confirmatory Factor Analysis in a Chinese Setting

ERIC Educational Resources Information Center

Deng, Ci-ping; Liu, Ming; Wei, Wei; Chan, Raymond C. K.; Das, J. P.

2011-01-01

This study aims to measure the psychometric properties of the Das-Naglieri Cognitive Assessment System (D-N CAS) and to determine its clinical utility in a Chinese context. Confirmatory factor analysis (CFA) was conducted to examine the construct validity of the Chinese version of the D-N CAS among a group of 567, normally developed children.…
Do gamblers eat more salt? Testing a latent trait model of covariance in consumption

PubMed Central

Goodwin, Belinda C.; Browne, Matthew; Rockloff, Matthew; Donaldson, Phillip

2015-01-01

A diverse class of stimuli, including certain foods, substances, media, and economic behaviours, may be described as ‘reward-oriented’ in that they provide immediate reinforcement with little initial investment. Neurophysiological and personality concepts, including dopaminergic dysfunction, reward sensitivity and rash impulsivity, each predict the existence of a latent behavioural trait that leads to increased consumption of all stimuli in this class. Whilst bivariate relationships (co-morbidities) are often reported in the literature, to our knowledge, a multivariate investigation of this possible trait has not been done. We surveyed 1,194 participants (550 male) on their typical weekly consumption of 11 types of reward-oriented stimuli, including fast food, salt, caffeine, television, gambling products, and illicit drugs. Confirmatory factor analysis was used to compare models in a 3×3 structure, based on the definition of a single latent factor (none, fixed loadings, or estimated loadings), and assumed residual covariance structure (none, a-priori / literature based, or post-hoc / data-driven). The inclusion of a single latent behavioural ‘consumption’ factor significantly improved model fit in all cases. Also confirming theoretical predictions, estimated factor loadings on reward-oriented indicators were uniformly positive, regardless of assumptions regarding residual covariances. Additionally, the latent trait was found to be negatively correlated with the non-reward-oriented indicators of fruit and vegetable consumption. The findings support the notion of a single behavioural trait leading to increased consumption of reward-oriented stimuli across multiple modalities. We discuss implications regarding the concentration of negative lifestyle-related health behaviours. PMID:26551907
Do gamblers eat more salt? Testing a latent trait model of covariance in consumption.

PubMed

Goodwin, Belinda C; Browne, Matthew; Rockloff, Matthew; Donaldson, Phillip

2015-09-01

A diverse class of stimuli, including certain foods, substances, media, and economic behaviours, may be described as 'reward-oriented' in that they provide immediate reinforcement with little initial investment. Neurophysiological and personality concepts, including dopaminergic dysfunction, reward sensitivity and rash impulsivity, each predict the existence of a latent behavioural trait that leads to increased consumption of all stimuli in this class. Whilst bivariate relationships (co-morbidities) are often reported in the literature, to our knowledge, a multivariate investigation of this possible trait has not been done. We surveyed 1,194 participants (550 male) on their typical weekly consumption of 11 types of reward-oriented stimuli, including fast food, salt, caffeine, television, gambling products, and illicit drugs. Confirmatory factor analysis was used to compare models in a 3×3 structure, based on the definition of a single latent factor (none, fixed loadings, or estimated loadings), and assumed residual covariance structure (none, a-priori / literature based, or post-hoc / data-driven). The inclusion of a single latent behavioural 'consumption' factor significantly improved model fit in all cases. Also confirming theoretical predictions, estimated factor loadings on reward-oriented indicators were uniformly positive, regardless of assumptions regarding residual covariances. Additionally, the latent trait was found to be negatively correlated with the non-reward-oriented indicators of fruit and vegetable consumption. The findings support the notion of a single behavioural trait leading to increased consumption of reward-oriented stimuli across multiple modalities. We discuss implications regarding the concentration of negative lifestyle-related health behaviours.
Psychometric analysis of the Swedish version of the General Medical Council's multi source feedback questionnaires.

PubMed

Olsson, Jan-Eric; Wallentin, Fan Yang; Toth-Pal, Eva; Ekblad, Solvig; Bertilson, Bo Christer

2017-07-10

To determine the internal consistency and the underlying components of our translated and adapted Swedish version of the General Medical Council's multisource feedback questionnaires (GMC questionnaires) for physicians and to confirm which aspects of good medical practice the latent variable structure reflected. From October 2015 to March 2016, residents in family medicine in Sweden were invited to participate in the study and to use the Swedish version to perform self-evaluations and acquire feedback from both their patients and colleagues. The validation focused on internal consistency and construct validity. Main outcome measures were Cronbach's alpha coefficients, Principal Component Analysis, and Confirmatory Factor Analysis indices. A total of 752 completed questionnaires from patients, colleagues, and residents were analysed. Of these, 213 comprised resident self-evaluations, 336 were feedback from residents' patients, and 203 were feedback from residents' colleagues. Cronbach's alpha coefficients of the scores were 0.88 from patients, 0.93 from colleagues, and 0.84 in the self-evaluations. The Confirmatory Factor Analysis validated two models that fit the data reasonably well and reflected important aspects of good medical practice. The first model had two latent factors for patient-related items concerning empathy and consultation management, and the second model had five latent factors for colleague-related items, including knowledge and skills, attitude and approach, reflection and development, teaching, and trust. The current Swedish version seems to be a reliable and valid tool for formative assessment for resident physicians and their supervisors. This needs to be verified in larger samples.
Psychometric analysis of the Swedish version of the General Medical Council's multi source feedback questionnaires

PubMed Central

Wallentin, Fan Yang; Toth-Pal, Eva; Ekblad, Solvig; Bertilson, Bo Christer

2017-01-01

Objectives To determine the internal consistency and the underlying components of our translated and adapted Swedish version of the General Medical Council's multisource feedback questionnaires (GMC questionnaires) for physicians and to confirm which aspects of good medical practice the latent variable structure reflected. Methods From October 2015 to March 2016, residents in family medicine in Sweden were invited to participate in the study and to use the Swedish version to perform self-evaluations and acquire feedback from both their patients and colleagues. The validation focused on internal consistency and construct validity. Main outcome measures were Cronbach’s alpha coefficients, Principal Component Analysis, and Confirmatory Factor Analysis indices. Results A total of 752 completed questionnaires from patients, colleagues, and residents were analysed. Of these, 213 comprised resident self-evaluations, 336 were feedback from residents’ patients, and 203 were feedback from residents’ colleagues. Cronbach’s alpha coefficients of the scores were 0.88 from patients, 0.93 from colleagues, and 0.84 in the self-evaluations. The Confirmatory Factor Analysis validated two models that fit the data reasonably well and reflected important aspects of good medical practice. The first model had two latent factors for patient-related items concerning empathy and consultation management, and the second model had five latent factors for colleague-related items, including knowledge and skills, attitude and approach, reflection and development, teaching, and trust. Conclusions The current Swedish version seems to be a reliable and valid tool for formative assessment for resident physicians and their supervisors. This needs to be verified in larger samples. PMID:28704204
Medical University admission test: a confirmatory factor analysis of the results.

PubMed

Luschin-Ebengreuth, Marion; Dimai, Hans P; Ithaler, Daniel; Neges, Heide M; Reibnegger, Gilbert

2016-05-01

The Graz Admission Test has been applied since the academic year 2006/2007. The validity of the Test was demonstrated by a significant improvement of study success and a significant reduction of dropout rate. The purpose of this study was a detailed analysis of the internal correlation structure of the various components of the Graz Admission Test. In particular, the question investigated was whether or not the various test parts constitute a suitable construct which might be designated as "Basic Knowledge in Natural Science." This study is an observational investigation, analyzing the results of the Graz Admission Test for the study of human medicine and dentistry. A total of 4741 applicants were included in the analysis. Principal component factor analysis (PCFA) as well as techniques from structural equation modeling, specifically confirmatory factor analysis (CFA), were employed to detect potential underlying latent variables governing the behavior of the measured variables. PCFA showed good clustering of the science test parts, including also text comprehension. A putative latent variable "Basic Knowledge in Natural Science," investigated by CFA, was indeed shown to govern the response behavior of the applicants in biology, chemistry, physics, and mathematics as well as text comprehension. The analysis of the correlation structure of the various test parts confirmed that the science test parts together with text comprehension constitute a satisfactory instrument for measuring a latent construct variable "Basic Knowledge in Natural Science." The present results suggest the fundamental importance of basic science knowledge for results obtained in the framework of the admission process for medical universities.
Relationships among Behavioral Profiles, Reading Performance, and Disability Labels: A Latent Class Analysis of Students in the ED, LD, and OHI Special Education Categories

ERIC Educational Resources Information Center

Weingarten, Zachary

2018-01-01

The aim of this study was to explore the variation in student behavior across the ED, LD, and OHI disability categories and to examine demographic, behavioral, and academic factors that may place students at risk for negative outcomes. This study used teachers' rating of students' in-class behavior to identify latent classes of students in the ED,…
Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations

ERIC Educational Resources Information Center

Can, Seda; van de Schoot, Rens; Hox, Joop

2015-01-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation…
Return on Investment Analysis for the Almond Board of California

DTIC Science & Technology

2004-06-01

general approach for the analysis is first to identify relevant factors concerning consumer behavior using exploratory factor analysis (EFA) and...That completed the intermediate stage of the conceptual model below, referring to the latent drivers of consumer behavior that affect the almond... consumer behavior remains a challenge that will have to be continuously addressed by the ABC management. Finally, to improve the methodology for
The Depression Anxiety Stress Scales (DASS): normative data and latent structure in a large non-clinical sample.

PubMed

Crawford, John R; Henry, Julie D

2003-06-01

To provide UK normative data for the Depression Anxiety and Stress Scale (DASS) and test its convergent, discriminant and construct validity. Cross-sectional, correlational and confirmatory factor analysis (CFA). The DASS was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,771) in terms of demographic variables. Competing models of the latent structure of the DASS were derived from theoretical and empirical sources and evaluated using confirmatory factor analysis. Correlational analysis was used to determine the influence of demographic variables on DASS scores. The convergent and discriminant validity of the measure was examined through correlating the measure with two other measures of depression and anxiety (the HADS and the sAD), and a measure of positive and negative affectivity (the PANAS). The best fitting model (CFI =.93) of the latent structure of the DASS consisted of three correlated factors corresponding to the depression, anxiety and stress scales with correlated error permitted between items comprising the DASS subscales. Demographic variables had only very modest influences on DASS scores. The reliability of the DASS was excellent, and the measure possessed adequate convergent and discriminant validity Conclusions: The DASS is a reliable and valid measure of the constructs it was intended to assess. The utility of this measure for UK clinicians is enhanced by the provision of large sample normative data.

Bayesian Nonparametric Ordination for the Analysis of Microbial Communities.

PubMed

Ren, Boyu; Bacallado, Sergio; Favaro, Stefano; Holmes, Susan; Trippa, Lorenzo

2017-01-01

Human microbiome studies use sequencing technologies to measure the abundance of bacterial species or Operational Taxonomic Units (OTUs) in samples of biological material. Typically the data are organized in contingency tables with OTU counts across heterogeneous biological samples. In the microbial ecology community, ordination methods are frequently used to investigate latent factors or clusters that capture and describe variations of OTU counts across biological samples. It remains important to evaluate how uncertainty in estimates of each biological sample's microbial distribution propagates to ordination analyses, including visualization of clusters and projections of biological samples on low dimensional spaces. We propose a Bayesian analysis for dependent distributions to endow frequently used ordinations with estimates of uncertainty. A Bayesian nonparametric prior for dependent normalized random measures is constructed, which is marginally equivalent to the normalized generalized Gamma process, a well-known prior for nonparametric analyses. In our prior, the dependence and similarity between microbial distributions is represented by latent factors that concentrate in a low dimensional space. We use a shrinkage prior to tune the dimensionality of the latent factors. The resulting posterior samples of model parameters can be used to evaluate uncertainty in analyses routinely applied in microbiome studies. Specifically, by combining them with multivariate data analysis techniques we can visualize credible regions in ecological ordination plots. The characteristics of the proposed model are illustrated through a simulation study and applications in two microbiome datasets.
Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples.

PubMed

MacLeod, Melissa A; Tremblay, Paul F; Graham, Kathryn; Bernards, Sharon; Rehm, Jürgen; Wells, Samantha

2016-12-01

The 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a brief measurement tool used cross-culturally to capture the multi-dimensional nature of disablement through six domains, including: understanding and interacting with the world; moving and getting around; self-care; getting on with people; life activities; and participation in society. Previous psychometric research supports that the WHODAS 2.0 functions as a general factor of disablement. In a pooled dataset from community samples of adults (N = 447) we used confirmatory factor analysis to confirm a one-factor structure. Latent class analysis was used to identify subgroups of individuals based on their patterns of responses. We identified four distinct classes, or patterns of disablement: (1) pervasive disability; (2) physical disability; (3) emotional, cognitive, or interpersonal disability; (4) no/low disability. Convergent validity of the latent class subgroups was found with respect to socio-demographic characteristics, number of days affected by disabilities, stress, mental health, and substance use. These classes offer a simple and meaningful way to classify people with disabilities based on the 12-item WHODAS 2.0. Focusing on individuals with a high probability of being in the first three classes may help guide interventions. Copyright © 2016 John Wiley & Sons, Ltd.
Factor analysis of the Foreign Language Classroom Anxiety Scale in Korean learners of English as a foreign language.

PubMed

Park, Gi-Pyo

2014-08-01

This study examined the latent constructs of the Foreign Language Classroom Anxiety Scale (FLCAS) using two different groups of Korean English as a foreign language (EFL) university students. Maximum likelihood exploratory factor analysis with direct oblimin rotation was performed among the first group of 217 participants and produced two meaningful latent components in the FLCAS. The two components of the FLCAS were closely examined among the second group of 244 participants to find the extent to which the two components of the FLCAS fit the data. The model fit indexes showed that the two-factor model in general adequately fit the data. Findings of this study were discussed with the focus on the two components of the FLCAS, followed by future study areas to be undertaken to shed further light on the role of foreign language anxiety in L2 acquisition.
Measuring psychosocial environments using individual responses: an application of multilevel factor analysis to examining students in schools.

PubMed

Dunn, Erin C; Masyn, Katherine E; Jones, Stephanie M; Subramanian, S V; Koenen, Karestan C

2015-07-01

Interest in understanding how psychosocial environments shape youth outcomes has grown considerably. School environments are of particular interest to prevention scientists as many prevention interventions are school-based. Therefore, effective conceptualization and operationalization of the school environment is critical. This paper presents an illustration of an emerging analytic method called multilevel factor analysis (MLFA) that provides an alternative strategy to conceptualize, measure, and model environments. MLFA decomposes the total sample variance-covariance matrix for variables measured at the individual level into within-cluster (e.g., student level) and between-cluster (e.g., school level) matrices and simultaneously models potentially distinct latent factor structures at each level. Using data from 79,362 students from 126 schools in the National Longitudinal Study of Adolescent to Adult Health (formerly known as the National Longitudinal Study of Adolescent Health), we use MLFA to show how 20 items capturing student self-reported behaviors and emotions provide information about both students (within level) and their school environment (between level). We identified four latent factors at the within level: (1) school adjustment, (2) externalizing problems, (3) internalizing problems, and (4) self-esteem. Three factors were identified at the between level: (1) collective school adjustment, (2) psychosocial environment, and (3) collective self-esteem. The finding of different and substantively distinct latent factor structures at each level emphasizes the need for prevention theory and practice to separately consider and measure constructs at each level of analysis. The MLFA method can be applied to other nested relationships, such as youth in neighborhoods, and extended to a multilevel structural equation model to better understand associations between environments and individual outcomes and therefore how to best implement preventive interventions.
The Four-Factor Model of Depressive Symptoms in Dementia Caregivers: A Structural Equation Model of Ethnic Differences

PubMed Central

Roth, David L.; Ackerman, Michelle L.; Okonkwo, Ozioma C.; Burgio, Louis D.

2008-01-01

Previous studies have suggested that 4 latent constructs (depressed affect, well-being, interpersonal problems, somatic symptoms) underlie the item responses on the Center for Epidemiological Studies Depression (CES-D) Scale. This instrument has been widely used in dementia caregiving research, but the fit of this multifactor model and the explanatory contributions of multifactor models have not been sufficiently examined for caregiving samples. The authors subjected CES-D data (N = 1,183) from the initial Resources for Enhancing Alzheimer’s Caregiver Health Study to confirmatory factor analysis methods and found that the 4-factor model provided excellent fit to the observed data. Invariance analyses suggested only minimal item-loading differences across race subgroups and supported the validity of race comparisons on the latent factors. Significant race differences were found on 3 of the 4 latent factors both before and after controlling for demographic covariates. African Americans reported less depressed affect and better well-being than White caregivers, who reported better well-being and fewer interpersonal problems than Hispanic caregivers. These findings clarify and extend previous studies of race differences in depression among diverse samples of dementia caregivers. PMID:18808246
Stability of alcohol use and teen dating violence for female youth: A latent transition analysis.

PubMed

Choi, Hye Jeong; Elmquist, JoAnna; Shorey, Ryan C; Rothman, Emily F; Stuart, Gregory L; Temple, Jeff R

2017-01-01

Alcohol use is one of the most widely accepted and studied risk factors for teen dating violence (TDV). Too little research has explored longitudinally if it is true that an adolescent's alcohol use and TDV involvement simultaneously occur. In the current study, we examined whether there were latent status based on past-year TDV and alcohol use and whether female adolescents changed their statuses of TDV and alcohol use over time. The sample consisted of 583 female youths in seven public high schools in Texas. Three waves of longitudinal data collected from 2011 to 2013 were utilised in this study. Participants completed self-report assessments of alcohol use (past-year alcohol use, number of drinks in the past month and episodic heavy drinking within the past month) and psychological and physical TDV victimisation and perpetration. Latent transition analysis was used to examine if the latent status based on TDV and alcohol use changed over time. Five separate latent statuses were identified: (i) no violence, no alcohol; (ii) alcohol; (iii) psychological violence, no alcohol; (iv) psychological violence, alcohol; and (v) physical and psychological violence, alcohol. Latent transition analysis indicated that adolescents generally remained in the same subgroup across time. This study provides evidence on the co-occurrence of alcohol use and teen dating violence, and whether teens' status based on dating violence and alcohol use are stable over time. Findings from the current study highlight the importance of targeting both TDV and substance use in intervention and prevention programs. [Choi HJ, Elmquist J, Shorey RC, Rothman EF, Stuart GL,Temple JR. Stability of alcohol use and teen dating violence for female youth: Alatent transition analysis. Drug Alcohol Rev 2017;36:80-87]. © 2017 Australasian Professional Society on Alcohol and other Drugs.
Psychological Factors Predict Local and Referred Experimental Muscle Pain: A Cluster Analysis in Healthy Adults

PubMed Central

Lee, Jennifer E.; Watson, David; Frey-Law, Laura A.

2012-01-01

Background Recent studies suggest an underlying three- or four-factor structure explains the conceptual overlap and distinctiveness of several negative emotionality and pain-related constructs. However, the validity of these latent factors for predicting pain has not been examined. Methods A cohort of 189 (99F; 90M) healthy volunteers completed eight self-report negative emotionality and pain-related measures (Eysenck Personality Questionnaire-Revised; Positive and Negative Affect Schedule; State-Trait Anxiety Inventory; Pain Catastrophizing Scale; Fear of Pain Questionnaire; Somatosensory Amplification Scale; Anxiety Sensitivity Index; Whiteley Index). Using principal axis factoring, three primary latent factors were extracted: General Distress; Catastrophic Thinking; and Pain-Related Fear. Using these factors, individuals clustered into three subgroups of high, moderate, and low negative emotionality responses. Experimental pain was induced via intramuscular acidic infusion into the anterior tibialis muscle, producing local (infusion site) and/or referred (anterior ankle) pain and hyperalgesia. Results Pain outcomes differed between clusters (multivariate analysis of variance and multinomial regression), with individuals in the highest negative emotionality cluster reporting the greatest local pain (p = 0.05), mechanical hyperalgesia (pressure pain thresholds; p = 0.009) and greater odds (2.21 OR) of experiencing referred pain compared to the lowest negative emotionality cluster. Conclusion Our results provide support for three latent psychological factors explaining the majority of the variance between several pain-related psychological measures, and that individuals in the high negative emotionality subgroup are at increased risk for (1) acute local muscle pain; (2) local hyperalgesia; and (3) referred pain using a standardized nociceptive input. PMID:23165778
Transdiagnostic Factors and Mediation of the Relationship Between Perceived Racial Discrimination and Mental Disorders.

PubMed

Rodriguez-Seijas, Craig; Stohl, Malki; Hasin, Deborah S; Eaton, Nicholas R

2015-07-01

Multivariable comorbidity research indicates that many common mental disorders are manifestations of 2 latent transdiagnostic factors, internalizing and externalizing. Environmental stressors are known to increase the risk for experiencing particular mental disorders, but their relationships with transdiagnostic disorder constructs are unknown. The present study investigated one such stressor, perceived racial discrimination, which is robustly associated with a variety of mental disorders. To examine the direct and indirect associations between perceived racial discrimination and common forms of psychopathology. Quantitative analysis of 12 common diagnoses that were previously assessed in a nationally representative sample (N = 5191) of African American and Afro-Caribbean adults in the United States, taken from the National Survey of American Life, and used to test the possibility that transdiagnostic factors mediate the effects of discrimination on disorders. The data were obtained from February 2001 to March 2003. Latent variable measurement models, including factor analysis, and indirect effect models were used in the study. Mental health diagnoses from reliable and valid structured interviews and perceived race-based discrimination. While perceived discrimination was positively associated with all examined forms of psychopathology and substance use disorders, latent variable indirect effects modeling revealed that almost all of these associations were significantly mediated by the transdiagnostic factors. For social anxiety disorder and attention-deficit/hyperactivity disorder, complete mediation was found. The pathways linking perceived discrimination to psychiatric disorders were not direct but indirect (via transdiagnostic factors). Therefore, perceived discrimination may be associated with risk for myriad psychiatric disorders due to its association with transdiagnostic factors.
Mexican American Adolescents' Profiles of Risk and Mental Health: A Person-Centered Longitudinal Approach

ERIC Educational Resources Information Center

Zeiders, Katharine H.; Roosa, Mark W.; Knight, George P.; Gonzales, Nancy A.

2013-01-01

Although Mexican American adolescents experience multiple risk factors in their daily lives, most research examines the influences of risk factors on adjustment independently, ignoring the additive and interactive effects of multiple risk factors. Guided by a person-centered perspective and utilizing latent profile analysis, this study identified…
Gender Differences in Risk/Protection Profiles for Low Academic Performance

ERIC Educational Resources Information Center

Whitney, Stephen D.; Renner, Lynette M.; Herrenkohl, Todd I.

2010-01-01

Using holistic-interactionistic theory, the simultaneous nature of risk and protection factors for both males and females (age 6-11 in Wave 1) is examined using latent profile analysis (LPA). Risk/protection classes are estimated using multiple risk factor variables (e.g., physical child abuse) and multiple protective factors (e.g.,…
The mechanisms mediating the effects of poverty on children's intellectual development.

PubMed

Guo, G; Harris, K M

2000-11-01

Although adverse consequences of poverty for children are documented widely, little is understood about the mechanisms through which the effects of poverty disadvantage young children. In this analysis we investigate multiple mechanisms through which poverty affects a child's intellectual development. Using data from the NLSY and structural equation models, we have constructed five latent factors (cognitive stimulation, parenting style, physical environment, child's ill health at birth, and ill health in childhood) and have allowed these factors, along with child care, to mediate the effects of poverty and other exogenous variables. We produce two main findings. First, the influence of family poverty on children's intellectual development is mediated completely by the intervening mechanisms measured by our latent factors. Second, our analysis points to cognitive stimulation in the home, and (to a lesser extent) to parenting style, physical environment of the home, and poor child health at birth, as mediating factors that are affected by lack of income and that influence children's intellectual development.
Refreshing the Aged Latent Fingerprints with Ionizing Radiation Prior to the Cyanoacrylate Fuming Procedure: A Preliminary Study.

PubMed

Ristova, Mimoza M; Radiceska, Pavlina; Bozinov, Igorco; Barandovski, Lambe

2016-05-01

One of the crucial factors determining the cyanoacrylate deposit quality over latent fingerprints appeared to be the extent of the humidity. This work focuses on the enhancement/refreshment of age-degraded latent fingerprints by irradiating the samples with UV, X-ray, or thermal neutrons prior to the cyanoacrylate (CA) fuming. Age degradation of latent fingerprints deposited on glass surfaces was examined through the decrease in the number of characteristic minutiae counts over time. A term "critical day" was introduced for the time at which the average number of identifiable minutiae definitions drops to one-half. Fingerprints older than their "critical day" were exposed to either UV, X-ray, or thermal neutrons. Identical reference samples were kept unexposed. All samples, both reference and irradiated, were developed during a single CA fuming procedure. Comparative latent fingerprint analysis showed that exposure to ionizing radiation enhances the CA fuming, yielding a 20-30% increase in average minutiae count. © 2015 American Academy of Forensic Sciences.
The development of the Problematic Online Gaming Questionnaire (POGQ).

PubMed

Demetrovics, Zsolt; Urbán, Róbert; Nagygyörgy, Katalin; Farkas, Judit; Griffiths, Mark D; Pápay, Orsolya; Kökönyei, Gyöngyi; Felvinczi, Katalin; Oláh, Attila

2012-01-01

Online gaming has become increasingly popular. However, this has led to concerns that these games might induce serious problems and/or lead to dependence for a minority of players. The aim of this study was to uncover and operationalize the components of problematic online gaming. A total of 3415 gamers (90% males; mean age 21 years), were recruited through online gaming websites. A combined method of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was applied. Latent profile analysis was applied to identify persons at-risk. EFA revealed a six-factor structure in the background of problematic online gaming that was also confirmed by a CFA. For the assessment of the identified six dimensions--preoccupation, overuse, immersion, social isolation, interpersonal conflicts, and withdrawal--the 18-item Problematic Online Gaming Questionnaire (POGQ) proved to be exceedingly suitable. Based on the latent profile analysis, 3.4% of the gamer population was considered to be at high risk, while another 15.2% was moderately problematic. The POGQ seems to be an adequate measurement tool for the differentiated assessment of gaming related problems on six subscales.
Are Exaggerated Health Complaints Continuous or Categorical? A Taxometric Analysis of the Health Problem Overstatement Scale

ERIC Educational Resources Information Center

Walters, Glenn D.; Berry, David T. R.; Lanyon, Richard I.; Murphy, Michael P.

2009-01-01

A taxometric analysis of 3 factor scales extracted from the Health Problem Overstatement (HPO) scale of the Psychological Screening Inventory (PSI; R. I. Lanyon, 1970, 1978) was performed on the data from 1,240 forensic and psychiatric patients. Mean above minus below a cut, maximum covariance, and latent-mode factor analyses produced results…
An Assessment of Character and Leadership Development Latent Factor Structures through Confirmatory Factor, Item Response Theory, and Latent Class Analyses

ERIC Educational Resources Information Center

Higginbotham, David L.

2013-01-01

This study leveraged the complementary nature of confirmatory factor (CFA), item response theory (IRT), and latent class (LCA) analyses to strengthen the rigor and sophistication of evaluation of two new measures of the Air Force Academy's "leader of character" definition--the Character Mosaic Virtues (CMV) and the Leadership Mosaic…
FACTOR ANALYTIC MODELS OF CLUSTERED MULTIVARIATE DATA WITH INFORMATIVE CENSORING

EPA Science Inventory

This paper describes a general class of factor analytic models for the analysis of clustered multivariate data in the presence of informative missingness. We assume that there are distinct sets of cluster-level latent variables related to the primary outcomes and to the censorin...
Psychological Processes Mediate the Impact of Familial Risk, Social Circumstances and Life Events on Mental Health

PubMed Central

Kinderman, Peter; Schwannauer, Matthias; Pontin, Eleanor; Tai, Sara

2013-01-01

Background Despite widespread acceptance of the ‘biopsychosocial model’, the aetiology of mental health problems has provoked debate amongst researchers and practitioners for decades. The role of psychological factors in the development of mental health problems remains particularly contentious, and to date there has not been a large enough dataset to conduct the necessary multivariate analysis of whether psychological factors influence, or are influenced by, mental health. This study reports on the first empirical, multivariate, test of the relationships between the key elements of the biospychosocial model of mental ill-health. Methods and Findings Participants were 32,827 (age 18–85 years) self-selected respondents from the general population who completed an open-access online battery of questionnaires hosted by the BBC. An initial confirmatory factor analysis was performed to assess the adequacy of the proposed factor structure and the relationships between latent and measured variables. The predictive path model was then tested whereby the latent variables of psychological processes were positioned as mediating between the causal latent variables (biological, social and circumstantial) and the outcome latent variables of mental health problems and well-being. This revealed an excellent fit to the data, S-B χ2 (3199, N = 23,397) = 126654·8, p<·001; RCFI = ·97; RMSEA = ·04 (·038–·039). As hypothesised, a family history of mental health difficulties, social deprivation, and traumatic or abusive life-experiences all strongly predicted higher levels of anxiety and depression. However, these relationships were strongly mediated by psychological processes; specifically lack of adaptive coping, rumination and self-blame. Conclusion These results support a significant revision of the biopsychosocial model, as psychological processes determine the causal impact of biological, social, and circumstantial risk factors on mental health. This has clear implications for policy, education and clinical practice as psychological processes such as rumination and self-blame are amenable to evidence-based psychological therapies. PMID:24146890
Psychological processes mediate the impact of familial risk, social circumstances and life events on mental health.

PubMed

Kinderman, Peter; Schwannauer, Matthias; Pontin, Eleanor; Tai, Sara

2013-01-01

Despite widespread acceptance of the 'biopsychosocial model', the aetiology of mental health problems has provoked debate amongst researchers and practitioners for decades. The role of psychological factors in the development of mental health problems remains particularly contentious, and to date there has not been a large enough dataset to conduct the necessary multivariate analysis of whether psychological factors influence, or are influenced by, mental health. This study reports on the first empirical, multivariate, test of the relationships between the key elements of the biospychosocial model of mental ill-health. Participants were 32,827 (age 18-85 years) self-selected respondents from the general population who completed an open-access online battery of questionnaires hosted by the BBC. An initial confirmatory factor analysis was performed to assess the adequacy of the proposed factor structure and the relationships between latent and measured variables. The predictive path model was then tested whereby the latent variables of psychological processes were positioned as mediating between the causal latent variables (biological, social and circumstantial) and the outcome latent variables of mental health problems and well-being. This revealed an excellent fit to the data, S-B χ(2) (3199, N = 23,397) = 126654.8, p<.001; RCFI = .97; RMSEA = .04 (.038-.039). As hypothesised, a family history of mental health difficulties, social deprivation, and traumatic or abusive life-experiences all strongly predicted higher levels of anxiety and depression. However, these relationships were strongly mediated by psychological processes; specifically lack of adaptive coping, rumination and self-blame. These results support a significant revision of the biopsychosocial model, as psychological processes determine the causal impact of biological, social, and circumstantial risk factors on mental health. This has clear implications for policy, education and clinical practice as psychological processes such as rumination and self-blame are amenable to evidence-based psychological therapies.
The Coach-Athlete Relationship Questionnaire (CART-Q): development and initial validation.

PubMed

Jowett, Sophia; Ntoumanis, Nikos

2004-08-01

The purpose of the present study was to develop and validate a self-report instrument that measures the nature of the coach-athlete relationship. Jowett et al.'s (Jowett & Meek, 2000; Jowett, in press) qualitative case studies and relevant literature were used to generate items for an instrument that measures affective, cognitive, and behavioral aspects of the coach-athlete relationship. Two studies were carried out in an attempt to assess content, predictive, and construct validity, as well as internal consistency, of the Coach-Athlete Relationship Questionnaire (CART-Q), using two independent British samples. Principal component analysis and confirmatory factor analysis were used to reduce the number of items, identify principal components, and confirm the latent structure of the CART-Q. Results supported the multidimensional nature of the coach-athlete relationship. The latent structure of the CART-Q was underlined by the latent variables of coaches' and athletes' Closeness (emotions), Commitment (cognitions), and Complementarity (behaviors).
Aggressiveness as a latent personality trait of domestic dogs: Testing local independence and measurement invariance.

PubMed

Goold, Conor; Newberry, Ruth C

2017-01-01

Studies of animal personality attempt to uncover underlying or "latent" personality traits that explain broad patterns of behaviour, often by applying latent variable statistical models (e.g., factor analysis) to multivariate data sets. Two integral, but infrequently confirmed, assumptions of latent variable models in animal personality are: i) behavioural variables are independent (i.e., uncorrelated) conditional on the latent personality traits they reflect (local independence), and ii) personality traits are associated with behavioural variables in the same way across individuals or groups of individuals (measurement invariance). We tested these assumptions using observations of aggression in four age classes (4-10 months, 10 months-3 years, 3-6 years, over 6 years) of male and female shelter dogs (N = 4,743) in 11 different contexts. A structural equation model supported the hypothesis of two positively correlated personality traits underlying aggression across contexts: aggressiveness towards people and aggressiveness towards dogs (comparative fit index: 0.96; Tucker-Lewis index: 0.95; root mean square error of approximation: 0.03). Aggression across contexts was moderately repeatable (towards people: intraclass correlation coefficient (ICC) = 0.479; towards dogs: ICC = 0.303). However, certain contexts related to aggressiveness towards people (but not dogs) shared significant residual relationships unaccounted for by latent levels of aggressiveness. Furthermore, aggressiveness towards people and dogs in different contexts interacted with sex and age. Thus, sex and age differences in displays of aggression were not simple functions of underlying aggressiveness. Our results illustrate that the robustness of traits in latent variable models must be critically assessed before making conclusions about the effects of, or factors influencing, animal personality. Our findings are of concern because inaccurate "aggressive personality" trait attributions can be costly to dogs, recipients of aggression and society in general.

Changes to the Student Loan Experience: Psychological Predictors and Outcomes

ERIC Educational Resources Information Center

Mueller, Thomas

2014-01-01

This study builds on the work of scholars who have explored psychological perceptions of the student loan experience. Survey analysis ("N" = 175) revealed a multidimensional model was developed through factor analysis and testing, which revealed four latent variables: "Duress," "Mandatory," "Financial," and…
Aberrant intracellular localization of Varicella-Zoster virus regulatory proteins during latency

PubMed Central

Lungu, Octavian; Panagiotidis, Christos A.; Annunziato, Paula W.; Gershon, Anne A.; Silverstein, Saul J.

1998-01-01

Varicella-Zoster virus (VZV) is a herpesvirus that becomes latent in sensory neurons after primary infection (chickenpox) and subsequently may reactivate to cause zoster. The mechanism by which this virus maintains latency, and the factors involved, are poorly understood. Here we demonstrate, by immunohistochemical analysis of ganglia obtained at autopsy from seropositive patients without clinical symptoms of VZV infection that viral regulatory proteins are present in latently infected neurons. These proteins, which localize to the nucleus of cells during lytic infection, predominantly are detected in the cytoplasm of latently infected neurons. The restriction of regulatory proteins from the nucleus of latently infected neurons might interrupt the cascade of virus gene expression that leads to a productive infection. Our findings raise the possibility that VZV has developed a novel mechanism for maintenance of latency that contrasts with the transcriptional repression that is associated with latency of herpes simplex virus, the prototypic alpha herpesvirus. PMID:9618542
Constraints of recreational sport participation: measurement invariance and latent mean differences across sex and physical activity status.

PubMed

Liu, Jing Dong; Chung, Pak Kwong; Chen, Wing Ping

2014-10-01

The purpose of the current study was to (a) examine the measurement invariance of the Constraint Scale of Sport Participation across sex and physical activity status among the undergraduate students (N = 630) in Hong Kong and (b) compare the latent mean differences across groups. Measurement invariance of the Constraint Scale of Sport Participation across sex of and physical activity status of the participants was examined first. With receiving support on the measurement invariance across groups, latent mean differences of the scores across groups were examined. Multi-group confirmatory factor analysis revealed that the configural, metric, scalar, and structural invariance of the scale was supported across groups. The results of latent mean differences suggested that the women reported significantly higher constraints on time, partner, psychology, knowledge, and interest than the men. The physically inactive participants reported significantly higher scores on all constraints except for accessibility than the physically active participants.
A Semi-parametric Multivariate Gap-filling Model for Eddy Covariance Latent Heat Flux

NASA Astrophysics Data System (ADS)

Li, M.; Chen, Y.

2010-12-01

Quantitative descriptions of latent heat fluxes are important to study the water and energy exchanges between terrestrial ecosystems and the atmosphere. The eddy covariance approaches have been recognized as the most reliable technique for measuring surface fluxes over time scales ranging from hours to years. However, unfavorable micrometeorological conditions, instrument failures, and applicable measurement limitations may cause inevitable flux gaps in time series data. Development and application of suitable gap-filling techniques are crucial to estimate long term fluxes. In this study, a semi-parametric multivariate gap-filling model was developed to fill latent heat flux gaps for eddy covariance measurements. Our approach combines the advantages of a multivariate statistical analysis (principal component analysis, PCA) and a nonlinear interpolation technique (K-nearest-neighbors, KNN). The PCA method was first used to resolve the multicollinearity relationships among various hydrometeorological factors, such as radiation, soil moisture deficit, LAI, and wind speed. The KNN method was then applied as a nonlinear interpolation tool to estimate the flux gaps as the weighted sum latent heat fluxes with the K-nearest distances in the PCs’ domain. Two years, 2008 and 2009, of eddy covariance and hydrometeorological data from a subtropical mixed evergreen forest (the Lien-Hua-Chih Site) were collected to calibrate and validate the proposed approach with artificial gaps after standard QC/QA procedures. The optimal K values and weighting factors were determined by the maximum likelihood test. The results of gap-filled latent heat fluxes conclude that developed model successful preserving energy balances of daily, monthly, and yearly time scales. Annual amounts of evapotranspiration from this study forest were 747 mm and 708 mm for 2008 and 2009, respectively. Nocturnal evapotranspiration was estimated with filled gaps and results are comparable with other studies. Seasonal and daily variability of latent heat fluxes were also discussed.
PTSD's latent structure in Malaysian tsunami victims: assessing the newly proposed Dysphoric Arousal model.

PubMed

Armour, Cherie; Raudzah Ghazali, Siti; Elklit, Ask

2013-03-30

The underlying latent structure of Posttraumatic Stress Disorder (PTSD) is widely researched. However, despite a plethora of factor analytic studies, no single model has consistently been shown as superior to alternative models. The two most often supported models are the Emotional Numbing and the Dysphoria models. However, a recently proposed five-factor Dysphoric Arousal model has been gathering support over and above existing models. Data for the current study were gathered from Malaysian Tsunami survivors (N=250). Three competing models (Emotional Numbing/Dysphoria/Dysphoric Arousal) were specified and estimated using Confirmatory Factor Analysis (CFA). The Dysphoria model provided superior fit to the data compared to the Emotional Numbing model. However, using chi-square difference tests, the Dysphoric Arousal model showed a superior fit compared to both the Emotional Numbing and Dysphoria models. In conclusion, the current results suggest that the Dysphoric Arousal model better represents PTSD's latent structure and that items measuring sleeping difficulties, irritability/anger and concentration difficulties form a separate, unique PTSD factor. These results are discussed in relation to the role of Hyperarousal in PTSD's on-going symptom maintenance and in relation to the DSM-5. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Verbal Neuropsychological Functions in Aphasia: An Integrative Model

ERIC Educational Resources Information Center

Vigliecca, Nora Silvana; Báez, Sandra

2015-01-01

A theoretical framework which considers the verbal functions of the brain under a multivariate and comprehensive cognitive model was statistically analyzed. A confirmatory factor analysis was performed to verify whether some recognized aphasia constructs can be hierarchically integrated as latent factors from a homogenously verbal test. The Brief…
Latent Factors in Student-Teacher Interaction Factor Analysis

ERIC Educational Resources Information Center

Le, Thu; Bolt, Daniel; Camburn, Eric; Goff, Peter; Rohe, Karl

2017-01-01

Classroom interactions between students and teachers form a two-way or dyadic network. Measurements such as days absent, test scores, student ratings, or student grades can indicate the "quality" of the interaction. Together with the underlying bipartite graph, these values create a valued student-teacher dyadic interaction network. To…
How to Inspect Fruit

ERIC Educational Resources Information Center

Hamaker, Ellen L.

2007-01-01

Nesselroade, Gerstof, Hardy, and Ram point out that the concept of invariance as it is used in factor analytic practice differs from that employed in psychological theory. Although substantive interests often center on a lawfulness in the relationships among abstract constructs (i.e., latent variables), the focus in factor analysis has primarily…
Differences in environmental preferences towards cycling for transport among adults: a latent class analysis.

PubMed

Mertens, Lieze; Van Cauwenberg, Jelle; Ghekiere, Ariane; De Bourdeaudhuij, Ilse; Deforche, Benedicte; Van de Weghe, Nico; Van Dyck, Delfien

2016-08-12

Increasing cycling for transport can contribute to improve public health among adults. Micro-environmental factors (i.e. small-scaled street-setting features) may play an important role in affecting the street's appeal to cycle for transport. Understanding about the interplay between individuals and their physical environment is important to establish tailored environmental interventions. Therefore, the current study aimed to examine whether specific subgroups exist based on similarities in micro-environmental preferences to cycle for transport. Responses of 1950 middle-aged adults (45-65 years) on a series of choice tasks depicting potential cycling routes with manipulated photographs yielded three subgroups with different micro-environmental preferences using latent class analysis. Although latent class analysis revealed three different subgroups in the middle-aged adult population based on their environmental preferences, results indicated that cycle path type (i.e. a good separated cycle path) is the most important environmental factor for all participants and certainly for individuals who did not cycle for transport. Furthermore, only negligible differences were found between the importances of the other micro-environmental factors (i.e. traffic density, evenness of the cycle path, maintenance, vegetation and speed limits) regarding the two at risk subgroups and that providing a speed bump obviously has the least impact on the street's appeal to cycle for transport. Results from the current study indicate that only negligible differences were found between the three subgroups. Therefore, it might be suggested that tailored environmental interventions are not required in this research context.
Latent profiles of family background, personality and mental health factors and their association with behavioural addictions and substance use disorders in young Swiss men.

PubMed

Marmet, Simon; Studer, Joseph; Rougemont-Bücking, Ansgar; Gmel, Gerhard

2018-05-04

Recent theories suggest that behavioural addictions and substance use disorders may be the result of the same underlying vulnerability. The present study investigates profiles of family background, personality and mental health factors and their associations with seven behavioural addictions (to the internet, gaming, smartphones, internet sex, gambling, exercise and work) and three substance use disorder scales (for alcohol, cannabis and tobacco). The sample consisted of 5287 young Swiss men (mean age = 25.42) from the Cohort Study on Substance Use Risk Factors (C-SURF). A latent profile analysis was performed on family background, personality and mental health factors. The derived profiles were compared with regards to means and prevalence rates of the behavioural addiction and substance use disorder scales. Seven latent profiles were identified, ranging from profiles with a positive family background, favourable personality patterns and low values on mental health scales to profiles with a negative family background, unfavourable personality pattern and high values on mental health scales. Addiction scale means, corresponding prevalence rates and the number of concurrent addictions were highest in profiles with high values on mental health scales and a personality pattern dominated by neuroticism. Overall, behavioural addictions and substance use disorders showed similar patterns across latent profiles. Patterns of family background, personality and mental health factors were associated with different levels of vulnerability to addictions. Behavioural addictions and substance use disorders may thus be the result of the same underlying vulnerabilities. Copyright © 2018 Elsevier Masson SAS. All rights reserved.
Adolescent emotionality and effortful control: Core latent constructs and links to psychopathology and functioning

PubMed Central

Snyder, Hannah R.; Gulley, Lauren D.; Bijttebier, Patricia; Hartman, Catharina A.; Oldehinkel, Albertine J.; Mezulis, Amy; Young, Jami F.; Hankin, Benjamin L.

2015-01-01

Temperament is associated with important outcomes in adolescence, including academic and interpersonal functioning and psychopathology. Rothbart’s temperament model is among the most well-studied and supported approaches to adolescent temperament, and contains three main components: positive emotionality (PE), negative emotionality (NE), and effortful control (EC). However, the latent factor structure of Rothbart’s temperament measure for adolescents, the Early Adolescent Temperament Questionnaire Revised (EATQ-R, Ellis & Rothbart, 2001) has not been definitively established. To address this problem and investigate links between adolescent temperament and functioning, we used confirmatory factor analysis to examine the latent constructs of the EATQ-R in a large combined sample. For EC and NE, bifactor models consisting of a common factor plus specific factors for some sub-facets of each component fit best, providing a more nuanced understanding of these temperament dimensions. The nature of the PE construct in the EATQ-R is less clear. Models replicated in a hold-out dataset. The common components of high NE and low EC where broadly associated with increased psychopathology symptoms, and poor interpersonal and school functioning, while specific components of NE were further associated with corresponding specific components of psychopathology. Further questioning the construct validity of PE as measured by the EATQ-R, PE factors did not correlate with construct validity measures in a way consistent with theories of PE. Bringing consistency to the way the EATQ-R is modeled and using purer latent variables has the potential to advance the field in understanding links between dimensions of temperament and important outcomes of adolescent development. PMID:26011660
Adolescent emotionality and effortful control: Core latent constructs and links to psychopathology and functioning.

PubMed

Snyder, Hannah R; Gulley, Lauren D; Bijttebier, Patricia; Hartman, Catharina A; Oldehinkel, Albertine J; Mezulis, Amy; Young, Jami F; Hankin, Benjamin L

2015-12-01

Temperament is associated with important outcomes in adolescence, including academic and interpersonal functioning and psychopathology. Rothbart's temperament model is among the most well-studied and supported approaches to adolescent temperament, and contains 3 main components: positive emotionality (PE), negative emotionality (NE), and effortful control (EC). However, the latent factor structure of Rothbart's temperament measure for adolescents, the Early Adolescent Temperament Questionnaire Revised (EATQ-R; Ellis & Rothbart, 2001) has not been definitively established. To address this problem and investigate links between adolescent temperament and functioning, we used confirmatory factor analysis to examine the latent constructs of the EATQ-R in a large combined sample. For EC and NE, bifactor models consisting of a common factor plus specific factors for some subfacets of each component fit best, providing a more nuanced understanding of these temperament dimensions. The nature of the PE construct in the EATQ-R is less clear. Models replicated in a hold-out dataset. The common components of high NE and low EC where broadly associated with increased psychopathology symptoms, and poor interpersonal and school functioning, while specific components of NE were further associated with corresponding specific components of psychopathology. Further questioning the construct validity of PE as measured by the EATQ-R, PE factors did not correlate with construct validity measures in a way consistent with theories of PE. Bringing consistency to the way the EATQ-R is modeled and using purer latent variables has the potential to advance the field in understanding links between dimensions of temperament and important outcomes of adolescent development. (c) 2015 APA, all rights reserved).
Integrated systems biology analysis of KSHV latent infection reveals viral induction and reliance on peroxisome mediated lipid metabolism

PubMed Central

Sychev, Zoi E.; Hu, Alex; Lagunoff, Michael

2017-01-01

Kaposi’s Sarcoma associated Herpesvirus (KSHV), an oncogenic, human gamma-herpesvirus, is the etiological agent of Kaposi’s Sarcoma the most common tumor of AIDS patients world-wide. KSHV is predominantly latent in the main KS tumor cell, the spindle cell, a cell of endothelial origin. KSHV modulates numerous host cell-signaling pathways to activate endothelial cells including major metabolic pathways involved in lipid metabolism. To identify the underlying cellular mechanisms of KSHV alteration of host signaling and endothelial cell activation, we identified changes in the host proteome, phosphoproteome and transcriptome landscape following KSHV infection of endothelial cells. A Steiner forest algorithm was used to integrate the global data sets and, together with transcriptome based predicted transcription factor activity, cellular networks altered by latent KSHV were predicted. Several interesting pathways were identified, including peroxisome biogenesis. To validate the predictions, we showed that KSHV latent infection increases the number of peroxisomes per cell. Additionally, proteins involved in peroxisomal lipid metabolism of very long chain fatty acids, including ABCD3 and ACOX1, are required for the survival of latently infected cells. In summary, novel cellular pathways altered during herpesvirus latency that could not be predicted by a single systems biology platform, were identified by integrated proteomics and transcriptomics data analysis and when correlated with our metabolomics data revealed that peroxisome lipid metabolism is essential for KSHV latent infection of endothelial cells. PMID:28257516
Exploratory factor analysis of pathway copy number data with an application towards the integration with gene expression data.

PubMed

van Wieringen, Wessel N; van de Wiel, Mark A

2011-05-01

Realizing that genes often operate together, studies into the molecular biology of cancer shift focus from individual genes to pathways. In order to understand the regulatory mechanisms of a pathway, one must study its genes at all molecular levels. To facilitate such study at the genomic level, we developed exploratory factor analysis for the characterization of the variability of a pathway's copy number data. A latent variable model that describes the call probability data of a pathway is introduced and fitted with an EM algorithm. In two breast cancer data sets, it is shown that the first two latent variables of GO nodes, which inherit a clear interpretation from the call probabilities, are often related to the proportion of aberrations and a contrast of the probabilities of a loss and of a gain. Linking the latent variables to the node's gene expression data suggests that they capture the "global" effect of genomic aberrations on these transcript levels. In all, the proposed method provides an possibly insightful characterization of pathway copy number data, which may be fruitfully exploited to study the interaction between the pathway's DNA copy number aberrations and data from other molecular levels like gene expression.
Cognitive issues in fingerprint analysis: inter- and intra-expert consistency and the effect of a 'target' comparison.

PubMed

Dror, Itiel E; Champod, Christophe; Langenburg, Glenn; Charlton, David; Hunt, Heloise; Rosenthal, Robert

2011-05-20

Deciding whether two fingerprint marks originate from the same source requires examination and comparison of their features. Many cognitive factors play a major role in such information processing. In this paper we examined the consistency (both between- and within-experts) in the analysis of latent marks, and whether the presence of a 'target' comparison print affects this analysis. Our findings showed that the context of a comparison print affected analysis of the latent mark, possibly influencing allocation of attention, visual search, and threshold for determining a 'signal'. We also found that even without the context of the comparison print there was still a lack of consistency in analysing latent marks. Not only was this reflected by inconsistency between different experts, but the same experts at different times were inconsistent with their own analysis. However, the characterization of these inconsistencies depends on the standard and definition of what constitutes inconsistent. Furthermore, these effects were not uniform; the lack of consistency varied across fingerprints and experts. We propose solutions to mediate variability in the analysis of friction ridge skin. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Development of an Individualism-Collectivism Scale revisited: a Korean sample.

PubMed

Kim, Kitae; Cho, Bongsoon

2011-04-01

A 13-item Individualism-Collectivism scale comprising source of identity, goal priority, mode of social relation, and norm acceptance is presented. A validation of this scale was conducted using a survey of 773 Korean employees. An exploratory factor analysis and a second-order confirmatory factor analysis supported the measure as having theoretical face validity and acceptable internal consistency reliability. Among the four facets, goal priority most strongly predicted the general Individualism-Collectivism latent factor.
Assessing the fit of the Dysphoric Arousal model across two nationally representative epidemiological surveys: The Australian NSMHWB and the United States NESARC.

PubMed

Armour, Cherie; Carragher, Natacha; Elhai, Jon D

2013-01-01

Since the initial inclusion of PTSD in the DSM nomenclature, PTSD symptomatology has been distributed across three symptom clusters. However, a wealth of empirical research has concluded that PTSD's latent structure is best represented by one of two four-factor models: Numbing or Dysphoria. Recently, a newly proposed five-factor Dysphoric Arousal model, which separates the DSM-IV's Arousal cluster into two factors of Anxious Arousal and Dysphoric Arousal, has gathered support across a variety of trauma samples. To date, the Dysphoric Arousal model has not been assessed using nationally representative epidemiological data. We employed confirmatory factor analysis to examine PTSD's latent structure in two independent population based surveys from American (NESARC) and Australia (NSWHWB). We specified and estimated the Numbing model, the Dysphoria model, and the Dysphoric Arousal model in both samples. Results revealed that the Dysphoric Arousal model provided superior fit to the data compared to the alternative models. In conclusion, these findings suggest that items D1-D3 (sleeping difficulties; irritability; concentration difficulties) represent a separate, fifth factor within PTSD's latent structure using nationally representative epidemiological data in addition to single trauma specific samples. Copyright © 2012 Elsevier Ltd. All rights reserved.
The measurement of "eating-disorder-thoughts" and "eating-disorder-behaviors": Implications for assessment and detection of eating disorders in epidemiological studies.

PubMed

Miller, Jessie L; Vaillancourt, Tracy; Hanna, Steven E

2009-04-01

To test a theoretically driven second-order factor model of eating disorders, with eating-disordered thoughts and eating-disordered behaviors representing the higher order factors, we conducted a confirmatory factor analysis using a female university student sample (N=1816). The 'Thought' latent construct was comprised of indicators representing fear of fat and dissatisfaction with body shape/weight and the latent construct 'Behavior' was comprised of indicators representing binging, purging and restricting. From the thought and behavior latent factors, composite groups were created by varying the level of thoughts and behaviors (high, moderate, and few/or none). We examined the independent contributions of thoughts and behaviors on a measure of psychopathology (depression). A second-order model of "eating disorder thoughts" and "eating disorder behaviors" was supported by the data, based on model fit, factor loadings, and model parsimony. Mean scores on depression were clinically significant for groups engaged in any level of eating disorder behavior whereas thoughts contributed to risk for depression only at the extreme end. Because of the disproportionate representation of eating disorder thoughts (high) and eating disorder behaviors (low) in non-clinical populations, the measurement and detection of eating disorders may be enhanced by measuring thoughts separate from behaviors.
Molecular Basis of Latency in Pathogenic Human Viruses

NASA Astrophysics Data System (ADS)

Garcia-Blanco, Mariano A.; Cullen, Bryan R.

1991-11-01

Several human viruses are able to latently infect specific target cell populations in vivo. Analysis of the replication cycles of herpes simplex virus, Epstein-Barr virus, and human immunodeficiency virus suggests that the latent infections established by these human pathogens primarily result from a lack of host factors critical for the expression of viral early gene products. The subsequent activation of specific cellular transcription factors in response to extracellular stimuli can induce the expression of these viral regulatory proteins and lead to a burst of lytic viral replication. Latency in these eukaryotic viruses therefore contrasts with latency in bacteriophage, which is maintained primarily by the expression of virally encoded repressors of lytic replication.
Classifying Patients with Chronic Pelvic Pain into Levels of Biopsychosocial Dysfunction Using Latent Class Modeling of Patient Reported Outcome Measures

PubMed Central

Fenton, Bradford W.; Grey, Scott F.; Tossone, Krystel; McCarroll, Michele; Von Gruenigen, Vivian E.

2015-01-01

Chronic pelvic pain affects multiple aspects of a patient's physical, social, and emotional functioning. Latent class analysis (LCA) of Patient Reported Outcome Measures Information System (PROMIS) domains has the potential to improve clinical insight into these patients' pain. Based on the 11 PROMIS domains applied to n=613 patients referred for evaluation in a chronic pelvic pain specialty center, exploratory factor analysis (EFA) was used to identify unidimensional superdomains. Latent profile analysis (LPA) was performed to identify the number of homogeneous classes present and to further define the pain classification system. The EFA combined the 11 PROMIS domains into four unidimensional superdomains of biopsychosocial dysfunction: Pain, Negative Affect, Fatigue, and Social Function. Based on multiple fit criteria, a latent class model revealed four distinct classes of CPP: No dysfunction (3.2%); Low Dysfunction (17.8%); Moderate Dysfunction (53.2%); and High Dysfunction (25.8%). This study is the first description of a novel approach to the complex disease process such as chronic pelvic pain and was validated by demographic, medical, and psychosocial variables. In addition to an essentially normal class, three classes of increasing biopsychosocial dysfunction were identified. The LCA approach has the potential for application to other complex multifactorial disease processes. PMID:26355825

The Dynamics of Internalizing and Externalizing Comorbidity Across the Early School Years

PubMed Central

Willner, Cynthia J.; Gatzke-Kopp, Lisa M.; Bray, Bethany C.

2017-01-01

High rates of comorbidity are observed between internalizing and externalizing problems, yet the developmental dynamics of comorbid symptom presentations are not yet well understood. This study explored the developmental course of latent profiles of internalizing and externalizing symptoms across kindergarten, 1st, and 2nd grade. The sample consisted of 336 children from an urban, low-income community, selected based on relatively high (61%) or low (39%) aggressive/oppositional behavior problems at school entry (64% male; 70% African American, 20% Hispanic). Teachers reported on children’s symptoms in each year. An exploratory latent profile analysis of children’s scores on aggression/oppositionality, hyperactivity/inattention, anxiety, and social withdrawal symptom factors revealed 4 latent symptom profiles: comorbid (48% of the sample in each year), internalizing (19–23%), externalizing (21–22%), and well-adjusted (7–11%). The developmental course of these symptom profiles was examined using a latent transition analysis, which revealed remarkably high continuity in the comorbid symptom profile (89% from one year to the next) and moderately high continuity in both the internalizing and externalizing profiles (80% and 71%, respectively). Internalizing children had a 20% probability of remitting to the well-adjusted profile by the following year, whereas externalizing children had a 25% probability of transitioning to the comorbid profile. These results are consistent with the hypothesis that a common vulnerability factor contributes to developmentally stable internalizing-externalizing comorbidity, while also suggesting that some children with externalizing symptoms are at risk for subsequently accumulating internalizing symptoms. PMID:27739391
Exploring the application of latent class cluster analysis for investigating pedestrian crash injury severities in Switzerland.

PubMed

Sasidharan, Lekshmi; Wu, Kun-Feng; Menendez, Monica

2015-12-01

One of the major challenges in traffic safety analyses is the heterogeneous nature of safety data, due to the sundry factors involved in it. This heterogeneity often leads to difficulties in interpreting results and conclusions due to unrevealed relationships. Understanding the underlying relationship between injury severities and influential factors is critical for the selection of appropriate safety countermeasures. A method commonly employed to address systematic heterogeneity is to focus on any subgroup of data based on the research purpose. However, this need not ensure homogeneity in the data. In this paper, latent class cluster analysis is applied to identify homogenous subgroups for a specific crash type-pedestrian crashes. The manuscript employs data from police reported pedestrian (2009-2012) crashes in Switzerland. The analyses demonstrate that dividing pedestrian severity data into seven clusters helps in reducing the systematic heterogeneity of the data and to understand the hidden relationships between crash severity levels and socio-demographic, environmental, vehicle, temporal, traffic factors, and main reason for the crash. The pedestrian crash injury severity models were developed for the whole data and individual clusters, and were compared using receiver operating characteristics curve, for which results favored clustering. Overall, the study suggests that latent class clustered regression approach is suitable for reducing heterogeneity and revealing important hidden relationships in traffic safety analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.
Development of a new multidimensional individual and interpersonal resilience measure for older adults.

PubMed

Martin, A'verria Sirkin; Distelberg, Brian; Palmer, Barton W; Jeste, Dilip V

2015-01-01

Develop an empirically grounded measure that can be used to assess family and individual resilience in a population of older adults (aged 50-99). Cross-sectional, self-report data from 1006 older adults were analyzed in two steps. The total sample was split into two subsamples and the first step identified the underlying latent structure through principal component exploratory factor analysis (EFA). The second step utilized the second half of the sample to validate the derived latent structure through confirmatory factor analysis (CFA). EFA produced an eight-factor structure that appeared clinically relevant for measuring the multidimensional nature of resilience. Factors included self-efficacy, access to social support network, optimism, perceived economic and social resources, spirituality and religiosity, relational accord, emotional expression and communication, and emotional regulation. CFA confirmed the eight-factor structure previously achieved with covariance between each of the factors. Based on these analyses we developed the multidimensional individual and interpersonal resilience measure, a broad assessment of resilience for older adults. This study highlights the multidimensional nature of resilience and introduces an individual and interpersonal resilience measure developed for older adults which is grounded in the individual and family resilience literature.
Development of a New Multidimensional Individual and Interpersonal Resilience Measure for Older Adults

PubMed Central

Martin, A’verria Sirkin; Distelberg, Brian; Palmer, Barton W.; Jeste, Dilip V.

2015-01-01

Objectives Develop an empirically grounded measure that can be used to assess family and individual resilience in a population of older adults (aged 50-99). Methods Cross-sectional, self-report data from 1,006 older adults were analyzed in two steps. The total sample was split into two sub-samples and the first step identified the underlying latent structure through principal component Exploratory Factor Analysis (EFA). The second step utilized the second half of the sample to validate the derived latent structure through Confirmatory Factor Analysis (CFA). Results EFA produced an eight-factor structure that appeared clinically relevant for measuring the multidimensional nature of resilience. Factors included self-efficacy, access to social support network, optimism, perceived economic and social resources, spirituality and religiosity, relational accord, emotional expression and communication, and emotional regulation. CFA confirmed the eight-factor structure previously achieved with covariance between each of the factors. Based on these analyses we developed the Multidimensional Individual and Interpersonal Resilience Measure (MIIRM), a broad assessment of resilience for older adults. Conclusion This study highlights the multidimensional nature of resilience and introduces an individual and interpersonal resilience measure developed for older adults which is grounded in the individual and family resilience literature. PMID:24787701
The Relations Among Inhibition and Interference Control Functions: A Latent-Variable Analysis

ERIC Educational Resources Information Center

Friedman, Naomi P.; Miyake, Akira

2004-01-01

This study used data from 220 adults to examine the relations among 3 inhibition-related functions. Confirmatory factor analysis suggested that Prepotent Response Inhibition and Resistance to Distractor Interference were closely related, but both were unrelated to Resistance to Proactive Interference. Structural equation modeling, which combined…
The Development of the Problematic Online Gaming Questionnaire (POGQ)

PubMed Central

Demetrovics, Zsolt; Urbán, Róbert; Nagygyörgy, Katalin; Farkas, Judit; Griffiths, Mark D.; Pápay, Orsolya; Kökönyei, Gyöngyi; Felvinczi, Katalin; Oláh, Attila

2012-01-01

Background Online gaming has become increasingly popular. However, this has led to concerns that these games might induce serious problems and/or lead to dependence for a minority of players. Aim: The aim of this study was to uncover and operationalize the components of problematic online gaming. Methods A total of 3415 gamers (90% males; mean age 21 years), were recruited through online gaming websites. A combined method of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was applied. Latent profile analysis was applied to identify persons at-risk. Results EFA revealed a six-factor structure in the background of problematic online gaming that was also confirmed by a CFA. For the assessment of the identified six dimensions – preoccupation, overuse, immersion, social isolation, interpersonal conflicts, and withdrawal – the 18-item Problematic Online Gaming Questionnaire (POGQ) proved to be exceedingly suitable. Based on the latent profile analysis, 3.4% of the gamer population was considered to be at high risk, while another 15.2% was moderately problematic. Conclusions The POGQ seems to be an adequate measurement tool for the differentiated assessment of gaming related problems on six subscales. PMID:22590541
Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564
Young Children's Psychological Selves: Convergence with Maternal Reports of Child Personality

ERIC Educational Resources Information Center

Brown, Geoffrey L.; Mangelsdorf, Sarah C.; Agathen, Jean M.; Ho, Moon-Ho

2008-01-01

The present research examined five-year-old children's psychological self-concepts. Non-linear factor analysis was used to model the latent structure of the children's self-view questionnaire (CSVQ; Eder, 1990), a measure of children's self-concepts. The coherence and reliability of the emerging factor structure indicated that young children are…
Trajectories of Developmental Functioning among Children of Adolescent Mothers: Factors Associated with Risk for Delay

ERIC Educational Resources Information Center

Jahromi, Laudan B.; Umaña-Taylor, Adriana J.; Updegraff, Kimberly A.; Zeiders, Katharine H.

2016-01-01

Children of adolescent mothers are at risk for developmental delays. Less is known about the heterogeneity in these children's developmental trajectories, and factors associated with different patterns of development. This longitudinal study used latent class growth analysis (LCGA) to identify distinct trajectories in children of Mexican-origin…
Assessing Measurement Invariance of the Children's Depression Inventory in Chinese and Italian Primary School Student Samples

ERIC Educational Resources Information Center

Wu, Wenfeng; Lu, Yongbiao; Tan, Furong; Yao, Shuqiao; Steca, Patrizia; Abela, John R. Z.; Hankin, Benjamin L.

2012-01-01

This study tested the measurement invariance of Children's Depression Inventory (CDI) and compared its factorial variance/covariance and latent means among Chinese and Italian children. Multigroup confirmatory factor analysis of the original five factors identified by Kovacs revealed that full measurement invariance did not hold. Further analysis…
Latent Transition Analysis with a Mixture Item Response Theory Measurement Model

ERIC Educational Resources Information Center

Cho, Sun-Joo; Cohen, Allan S.; Kim, Seock-Ho; Bottge, Brian

2010-01-01

A latent transition analysis (LTA) model was described with a mixture Rasch model (MRM) as the measurement model. Unlike the LTA, which was developed with a latent class measurement model, the LTA-MRM permits within-class variability on the latent variable, making it more useful for measuring treatment effects within latent classes. A simulation…
Exploration and confirmation of the latent variable structure of the Jefferson scale of empathy

PubMed Central

LaNoue, Marianna

2014-01-01

Objectives: To reaffirm the underlying components of the JSE by using exploratory factor analysis (EFA), and to confirm its latent variable structure by using confirmatory factor analysis (CFA). Methods Research participants included 2,612 medical students who entered Jefferson Medical College between 2002 and 2012. This sample was divided into two groups: Matriculants between 2002 and 2007 (n=1,380) and between 2008 and 2012 (n=1,232). Data for 2002-2007 matriculants were subjected to EFA (principal component factor extraction), and data for matriculants of 2008-2012 were used for CFA (structural equation modeling, and root mean square error for approximation). Results The EFA resulted in three factors: “perspective-taking,” “compassionate care” and “walking in patient’s shoes” replicating the 3-factor model reported in most of the previous studies. The CFA showed that the 3-factor model was an acceptable fit, thus confirming the latent variable structure emerged in the EFA. Corrected item-total score correlations for the total sample were all positive and statistically significant, ranging from 0.13 to 0.61 with a median of 0.44 (p<0.01). The item discrimination effect size indices (contrasting item mean scores for the top-third versus bottom-third JSE scorers) ranged from 0.50 to 1.4 indicating that the differences in item mean scores between top and bottom scorers on the JSE were of practical importance. Cronbach’s alpha coefficient of the JSE for the total sample was 0.80, ranging from 0.75 to 0.84 for matriculatnts of different years. Conclusions Findings provided further support for underlying constructs of the JSE, adding to its credibility. PMID:25341215
Assessing the heterogeneity of aggressive behavior traits: exploratory and confirmatory analyses of the reactive and instrumental aggression Personality Assessment Inventory (PAI) scales.

PubMed

Antonius, Daniel; Sinclair, Samuel Justin; Shiva, Andrew A; Messinger, Julie W; Maile, Jordan; Siefert, Caleb J; Belfi, Brian; Malaspina, Dolores; Blais, Mark A

2013-01-01

The heterogeneity of violent behavior is often overlooked in risk assessment despite its importance in the management and treatment of psychiatric and forensic patients. In this study, items from the Personality Assessment Inventory (PAI) were first evaluated and rated by experts in terms of how well they assessed personality features associated with reactive and instrumental aggression. Exploratory principal component analyses (PCA) were then conducted on select items using a sample of psychiatric and forensic inpatients (n = 479) to examine the latent structure and construct validity of these reactive and instrumental aggression factors. Finally, a confirmatory factor analysis (CFA) was conducted on a separate sample of psychiatric inpatients (n = 503) to evaluate whether these factors yielded acceptable model fit. Overall, the exploratory and confirmatory analyses supported the existence of two latent PAI factor structures, which delineate personality traits related to reactive and instrumental aggression.
Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2015-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.
Test-retest reliability of the underlying latent factor structure of alcohol subjective response.

PubMed

Lutz, Joseph A; Childs, Emma

2017-04-01

Alcohol subjective experiences are multi-dimensional and demonstrate wide inter-individual variability. Recent efforts have sought to establish a clearer understanding of subjective alcohol responses by identifying core constructs derived from multiple measurement instruments. The aim of this study was to evaluate the temporal stability of this approach to conceptualizing alcohol subjective experiences across successive alcohol administrations in the same individuals. Healthy moderate alcohol drinkers (n = 104) completed six experimental sessions each, three with alcohol (0.8 g/kg), and three with a non-alcoholic control beverage. Participants reported subjective mood and drug effects using standardized questionnaires before and at repeated times after beverage consumption. We explored the underlying latent structure of subjective responses for all alcohol administrations using exploratory factor analysis and then tested measurement invariance over the three successive administrations using multi-group confirmatory factor analyses. Exploratory factor analyses on responses to alcohol across all administrations yielded four factors representing "Positive mood," "Sedation," "Stimulation/Euphoria," and "Drug effects and Urges." A confirmatory factor analysis on the separate administrations indicated acceptable configural and metric invariance and moderate scalar invariance. In this study, we demonstrate temporal stability of the underlying constructs of subjective alcohol responses derived from factor analysis. These findings strengthen the utility of this approach to conceptualizing subjective alcohol responses especially for use in prospective and longitudinal alcohol challenge studies relating subjective response to alcohol use disorder risk.
Confirmatory factor analysis reveals a latent cognitive structure common to bipolar disorder, schizophrenia, and normal controls.

PubMed

Schretlen, David J; Peña, Javier; Aretouli, Eleni; Orue, Izaskun; Cascella, Nicola G; Pearlson, Godfrey D; Ojeda, Natalia

2013-06-01

We sought to determine whether a single hypothesized latent factor structure would characterize cognitive functioning in three distinct groups. We assessed 576 adults (340 community controls, 126 adults with bipolar disorder, and 110 adults with schizophrenia) using 15 measures derived from nine cognitive tests. Confirmatory factor analysis (CFA) was conducted to examine the fit of a hypothesized six-factor model. The hypothesized factors included attention, psychomotor speed, verbal memory, visual memory, ideational fluency, and executive functioning. The six-factor model provided an excellent fit for all three groups [for community controls, root mean square error of approximation (RMSEA) <0.048 and comparative fit index (CFI) = 0.99; for adults with bipolar disorder, RMSEA = 0.071 and CFI = 0.99; and for adults with schizophrenia, RMSEA = 0.06 and CFI = 0.98]. Alternate models that combined fluency with processing speed or verbal and visual memory reduced the goodness of fit. Multi-group CFA results supported factor invariance across the three groups. Confirmatory factor analysis supported a single six-factor structure of cognitive functioning among patients with schizophrenia or bipolar disorder and community controls. While the three groups clearly differ in level of performance, they share a common underlying architecture of information processing abilities. These cognitive factors could provide useful targets for clinical trials of treatments that aim to enhance information processing in persons with neurological and neuropsychiatric disorders. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Anxiety, bulimia, drug and alcohol addiction, depression, and schizophrenia: what do you think about their aetiology, dangerousness, social distance, and treatment? A latent class analysis approach.

PubMed

Mannarini, Stefania; Boffo, Marilisa

2015-01-01

Mental illness stigma is a serious societal problem and a critical impediment to treatment seeking for mentally ill people. To improve the understanding of mental illness stigma, this study focuses on the simultaneous analysis of people's aetiological beliefs, attitudes (i.e. perceived dangerousness and social distance), and recommended treatments related to several mental disorders by devising an over-arching latent structure that could explain the relations among these variables. Three hundred and sixty university students randomly received an unlabelled vignette depicting one of six mental disorders to be evaluated on the four variables on a Likert-type scale. A one-factor Latent Class Analysis (LCA) model was hypothesized, which comprised the four manifest variables as indicators and the mental disorder as external variable. The main findings were the following: (a) a one-factor LCA model was retrieved; (b) alcohol and drug addictions are the most strongly stigmatized; (c) a realistic opinion about the causes and treatment of schizophrenia, anxiety, bulimia, and depression was associated to lower prejudicial attitudes and social rejection. Beyond the general appraisal of mental illness an individual might have, the results generally point to the acknowledgement of the specific features of different diagnostic categories. The implications of the present results are discussed in the framework of a better understanding of mental illness stigma.
Symptoms of prolonged grief and posttraumatic stress following loss: A latent class analysis.

PubMed

Maccallum, Fiona; Bryant, Richard A

2018-04-01

Individuals vary in how they respond to bereavement. Those who experience poor bereavement outcomes often report symptoms from more than one diagnostic category. This study sought to identify groups of individuals who share similar patterns of prolonged grief disorder and posttraumatic stress disorder symptoms to determine whether these profiles are differentially related to negative appraisals thought to contribute to prolonged grief disorder and posttraumatic stress disorder symptomatology. Participants were 185 bereaved adults. Latent class analysis was used to identify subgroups of individuals who showed similar patterns of co-occurrence of prolonged grief disorder and posttraumatic stress disorder symptoms. Multinomial regression was used to examine the extent to which appraisal domains and sociodemographic and loss factors predicted class membership. Latent class analysis revealed three classes of participants: a low symptom group, a high prolonged grief disorder symptom group, and a high prolonged grief disorder and posttraumatic stress disorder symptom group. Membership of the prolonged grief disorder group and prolonged grief disorder and posttraumatic stress disorder group was predicted by higher mean negative self-related appraisals. Demographic and loss-related factors did not predict group membership. These findings have implications for understanding co-occurrence of prolonged grief disorder and posttraumatic stress disorder symptoms following bereavement. Findings are consistent with theoretical models highlighting the importance of negative self-related beliefs in prolonged grief disorder.
Predictors of Patterns of Alcohol-Related Blackouts Over Time in Youth From the Collaborative Study of the Genetics of Alcoholism: The Roles of Genetics and Cannabis

PubMed Central

Schuckit, Marc A.; Smith, Tom L.; Shafir, Alexandra; Clausen, Peyton; Danko, George; Gonçalves, Priscila Dib; Anthenelli, Robert M.; Chan, Grace; Kuperman, Samuel; Hesselbrock, Michie; Hesselbrock, Victor; Kramer, John; Bucholz, Kathleen K.

2017-01-01

Objective: Alcohol-related blackouts (ARBs) are anterograde amnesias related to heavy alcohol intake seen in about 50% of drinkers. Although a major determinant of ARBs relates to blood alcohol concentrations, additional contributions come from genetic vulnerabilities and possible impacts of cannabis use disorders (CUDs). We evaluated relationships of genetics and cannabis use to latent class trajectories of ARBs in 829 subjects from the Collaborative Study of the Genetics of Alcoholism (COGA). Method: The number of ARBs experienced every 2 years from subjects with average ages of 18 to 25 were entered into a latent class growth analysis in Mplus, and resulting class membership was evaluated in light of baseline characteristics, including CUDs. Correlations of number of ARBs across assessments were also compared for sibling pairs versus unrelated subjects. Results: Latent class growth analysis identified ARB-based Classes 1 (consistent low = 42.5%), 2 (moderate low = 28.3%), 3 (moderate high = 22.9%), and 4 (consistent high = 6.3%). A multinomial logistic regression analysis within latent class growth analysis revealed that baseline CUDs related most closely to Classes 3 and 4. The number of ARBs across time correlated .23 for sibling pairs and -.10 for unrelated subjects. Conclusions: Baseline CUDs related to the most severe latent ARB course over time, even when considered along with other trajectory predictors, including baseline alcohol use disorders and maximum number of drinks. Data indicated significant roles for genetic factors for alcohol use disorder patterns over time. Future research is needed to improve understanding of how cannabis adds to the ARB risk and to find genes that contribute to risks for ARBs among drinkers. PMID:27936363
Substance Use Patterns Among Adolescents in Europe: A Latent Class Analysis.

PubMed

Göbel, Kristin; Scheithauer, Herbert; Bräker, Astrid-Britta; Jonkman, Harrie; Soellner, Renate

2016-07-28

Several researchers have investigated substance use patterns using a latent class analysis; however, hardly no studies exist on substance use patterns across countries. Adolescent substance use patterns, demographic factors, and international differences in the prevalence of substance use patterns were explored. Data from 25 European countries were used to identify patterns of adolescent (12-16 years, 50.6% female) substance use (N = 33,566). Latent class analysis revealed four substance use classes: nonusers (68%), low-alcohol users (recent use of beer, wine, and alcopops; 16.1%), alcohol users (recent use of alcohol and lifetime use of marijuana; 11.2%), and polysubstance users (recent use of alcohol, marijuana, and other illicit drugs; 4.7%). Results support a general pattern of adolescent substance use across all countries; however, the prevalence rates of use patterns vary for each country. The present research provides insight into substance use patterns across Europe by using a large international adolescent sample, multidimensional indicators and a variety of substances. Substance use patterns are helpful when targeting policy and prevention strategies.

Discordant inflammation and pain in early and established rheumatoid arthritis: Latent Class Analysis of Early Rheumatoid Arthritis Network and British Society for Rheumatology Biologics Register data.

PubMed

McWilliams, Daniel F; Ferguson, Eamonn; Young, Adam; Kiely, Patrick D W; Walsh, David A

2016-12-13

Rheumatoid arthritis (RA) disease activity is often measured using the 28-joint Disease Activity Score (DAS28). We aimed to identify and independently verify subgroups of people with RA that may be discordant with respect to self-reported and objective disease state, with potentially different clinical needs. Data were derived from three cohorts: (1) the Early Rheumatoid Arthritis Network (ERAN) and the British Society for Rheumatology Biologics Register (BSRBR), (2) those commencing tumour necrosis factor (TNF)-α inhibitors and (3) those using non-biologic drugs. In latent class analysis, we used variables related to pain, central pain mechanisms or inflammation (pain, vitality, mental health, erythrocyte sedimentation rate, swollen joint count, tender joint count, visual analogue scale of general health). Clinically relevant outcomes were examined. Five, four and four latent classes were found in the ERAN, BSRBR TNF inhibitor and non-biologic cohorts, respectively. The proportions of people assigned with >80% probability into latent classes were 76%, 58% and 72% in the ERAN, TNF inhibitor and non-biologic cohorts, respectively. The latent classes displayed either concordance between measures indicative of mild, moderate or severe disease activity; discordantly worse patient-reported measures despite less markedly elevated inflammation; or discordantly less severe patient-reported measures despite elevated inflammation. Latent classes with discordantly worse patient-reported measures represented 12%, 40% and 21% of the ERAN, TNF inhibitor and non-biologic cohorts, respectively; contained more females; and showed worse function. In those latent classes with worse scores at baseline, DAS28 and function improved over 1 year (p < 0.001 for all comparisons), and scores differed less at follow-up than at baseline. Discordant latent classes can be identified in people with RA, and these findings are robust across three cohorts with varying disease duration and activity. These findings could be used to identify a sizeable subgroup of people with RA who might gain added benefit from pain management strategies.
Clustering, hierarchical organization, and the topography of abstract and concrete nouns.

PubMed

Troche, Joshua; Crutch, Sebastian; Reilly, Jamie

2014-01-01

The empirical study of language has historically relied heavily upon concrete word stimuli. By definition, concrete words evoke salient perceptual associations that fit well within feature-based, sensorimotor models of word meaning. In contrast, many theorists argue that abstract words are "disembodied" in that their meaning is mediated through language. We investigated word meaning as distributed in multidimensional space using hierarchical cluster analysis. Participants (N = 365) rated target words (n = 400 English nouns) across 12 cognitive dimensions (e.g., polarity, ease of teaching, emotional valence). Factor reduction revealed three latent factors, corresponding roughly to perceptual salience, affective association, and magnitude. We plotted the original 400 words for the three latent factors. Abstract and concrete words showed overlap in their topography but also differentiated themselves in semantic space. This topographic approach to word meaning offers a unique perspective to word concreteness.
High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

PubMed Central

Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike

2010-01-01

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139
Postneedling soreness after deep dry needling of a latent myofascial trigger point in the upper trapezius muscle: Characteristics, sex differences and associated factors.

PubMed

Martín-Pintado-Zugasti, Aitor; Rodríguez-Fernández, Ángel Luis; Fernandez-Carnero, Josue

2016-04-27

Postneedling soreness is considered the most frequent secondary effect associated to dry needling. A detailed description of postneedling soreness characteristics has not been previously reported. (1) to assess the intensity and duration of postneedling soreness and tenderness after deep dry needling of a trapezius latent myofascial trigger point (MTrP), (2) to evaluate the possible differences in postneedling soreness between sexes and (3) to analyze the influence on postneedling soreness of factors involved in the dry needling process. Sixty healthy subjects (30 men, 30 women) with latent MTrPs in the upper trapezius muscle received a dry needling intervention in the MTrP. Pain and pressure pain threshold (PPT) were assessed during a 72 hours follow-up period. Repeated measures analysis of covariance showed a significant effect for time in pain and in PPT. An interaction between sex and time in pain was obtained: women exhibited higher intensity in postneedling pain than men. The pain during needling and the number of needle insertions significantly correlated with postneedling soreness. Soreness and hyperalgesia are present in all subjects after dry needling of a latent MTrP in the upper trapezius muscle. Women exhibited higher intensity of postneedling soreness than men.
Aggressiveness as a latent personality trait of domestic dogs: Testing local independence and measurement invariance

PubMed Central

2017-01-01

Studies of animal personality attempt to uncover underlying or “latent” personality traits that explain broad patterns of behaviour, often by applying latent variable statistical models (e.g., factor analysis) to multivariate data sets. Two integral, but infrequently confirmed, assumptions of latent variable models in animal personality are: i) behavioural variables are independent (i.e., uncorrelated) conditional on the latent personality traits they reflect (local independence), and ii) personality traits are associated with behavioural variables in the same way across individuals or groups of individuals (measurement invariance). We tested these assumptions using observations of aggression in four age classes (4–10 months, 10 months–3 years, 3–6 years, over 6 years) of male and female shelter dogs (N = 4,743) in 11 different contexts. A structural equation model supported the hypothesis of two positively correlated personality traits underlying aggression across contexts: aggressiveness towards people and aggressiveness towards dogs (comparative fit index: 0.96; Tucker-Lewis index: 0.95; root mean square error of approximation: 0.03). Aggression across contexts was moderately repeatable (towards people: intraclass correlation coefficient (ICC) = 0.479; towards dogs: ICC = 0.303). However, certain contexts related to aggressiveness towards people (but not dogs) shared significant residual relationships unaccounted for by latent levels of aggressiveness. Furthermore, aggressiveness towards people and dogs in different contexts interacted with sex and age. Thus, sex and age differences in displays of aggression were not simple functions of underlying aggressiveness. Our results illustrate that the robustness of traits in latent variable models must be critically assessed before making conclusions about the effects of, or factors influencing, animal personality. Our findings are of concern because inaccurate “aggressive personality” trait attributions can be costly to dogs, recipients of aggression and society in general. PMID:28854267
Development of lifetime comorbidity in the WHO World Mental Health (WMH) Surveys

PubMed Central

Kessler, Ronald C.; Ormel, Johan; Petukhova, Maria; McLaughlin, Katie A.; Green, Jennifer Greif; Russo, Leo J.; Stein, Dan J.; Zaslavsky, Alan M; Aguilar-Gaxiola, Sergio; Alonso, Jordi; Andrade, Laura; Benjet, Corina; de Girolamo, Giovanni; de Graaf, Ron; Demyttenaere, Koen; Fayyad, John; Haro, Josep Maria; Hu, Chi yi; Karam, Aimee; Lee, Sing; Lepine, Jean-Pierre; Matchsinger, Herbert; Mihaescu-Pintia, Constanta; Posada-Villa, Jose; Sagar, Rajesh; Üstün, T. Bedirhan

2010-01-01

CONTEXT Although numerous studies have examined the role of latent variables in the structure of comorbidity among mental disorders, none has examined their role in the development of comorbidity. OBJECTIVE To study the role of latent variables in the development of comorbidity among 18 lifetime DSM-IV disorders in the WHO World Mental Health (WMH) surveys. SETTING/PARTICIPANTS Nationally or regionally representative community surveys in 14 countries with a total of 21,229 respondents. MAIN OUTCOME MEASURES First onset of 18 lifetime DSM-IV anxiety, mood, behavior, and substance disorders assessed retrospectively in the WHO Composite International Diagnostic Interview (CIDI). RESULTS Separate internalizing (anxiety and mood disorders) and externalizing (behavior and substance disorders) factors were found in exploratory factor analysis of lifetime disorders. Consistently significant positive time-lagged associations were found in survival analyses for virtually all temporally primary lifetime disorders predicting subsequent onset of other disorders. Within-domain (i.e., internalizing or externalizing) associations were generally stronger than between-domain associations. The vast majority of time-lagged associations were explained by a model that assumed the existence of mediating latent internalizing and externalizing variables. Specific phobia and obsessive-compulsive disorder (internalizing) and hyperactivity disorder and oppositional-defiant disorder (externalizing) were the most important predictors. A small number of residual associations remained significant after controlling the latent variables. CONCLUSIONS The good fit of the latent variable model suggests that common causal pathways account for most of the comorbidity among the disorders considered here. These common pathways should be the focus of future research on the development of comorbidity, although several important pair-wise associations that cannot be accounted for by latent variables also exist that warrant further focused study. PMID:21199968
Immunohistochemical detection of active transforming growth factor-beta in situ using engineered tissue

NASA Technical Reports Server (NTRS)

Barcellos-Hoff, M. H.; Ehrhart, E. J.; Kalia, M.; Jirtle, R.; Flanders, K.; Tsang, M. L.; Chatterjee, A. (Principal Investigator)

1995-01-01

The biological activity of transforming growth factor-beta 1 (TGF-beta) is governed by dissociation from its latent complex. Immunohistochemical discrimination of active and latent TGF-beta could provide insight into TGF-beta activation in physiological and pathological processes. However, evaluation of immunoreactivity specificity in situ has been hindered by the lack of tissue in which TGF-beta status is known. To provide in situ analysis of antibodies to differentiate between these functional forms, we used xenografts of human tumor cells modified by transfection to overexpress latent TGF-beta or constitutively active TGF-beta. This comparison revealed that, whereas most antibodies did not differentiate between TGF-beta activation status, the immunoreactivity of some antibodies was activation dependent. Two widely used peptide antibodies to the amino-terminus of TGF-beta, LC(1-30) and CC(1-30) showed marked preferential immunoreactivity with active TGF-beta versus latent TGF-beta in cryosections. However, in formalin-fixed, paraffin-embedded tissue, discrimination of active TGF-beta by CC(1-30) was lost and immunoreactivity was distinctly extracellular, as previously reported for this antibody. Similar processing-dependent extracellular localization was found with a neutralizing antibody raised to recombinant TGF-beta. Antigen retrieval recovered cell-associated immunoreactivity of both antibodies. Two antibodies to peptides 78-109 showed mild to moderate preferential immunoreactivity with active TGF-beta only in paraffin sections. LC(1-30) was the only antibody tested that discriminated active from latent TGF-beta in both frozen and paraffin-embedded tissue. Thus, in situ discrimination of active versus latent TGF-beta depends on both the antibody and tissue preparation. We propose that tissues engineered to express a specific form of a given protein provide a physiological setting in which to evaluate antibody reactivity with specific functional forms of a protein.
Using a latent variable model with non-constant factor loadings to examine PM2.5 constituents related to secondary inorganic aerosols.

PubMed

Zhang, Zhenzhen; O'Neill, Marie S; Sánchez, Brisa N

2016-04-01

Factor analysis is a commonly used method of modelling correlated multivariate exposure data. Typically, the measurement model is assumed to have constant factor loadings. However, from our preliminary analyses of the Environmental Protection Agency's (EPA's) PM 2.5 fine speciation data, we have observed that the factor loadings for four constituents change considerably in stratified analyses. Since invariance of factor loadings is a prerequisite for valid comparison of the underlying latent variables, we propose a factor model that includes non-constant factor loadings that change over time and space using P-spline penalized with the generalized cross-validation (GCV) criterion. The model is implemented using the Expectation-Maximization (EM) algorithm and we select the multiple spline smoothing parameters by minimizing the GCV criterion with Newton's method during each iteration of the EM algorithm. The algorithm is applied to a one-factor model that includes four constituents. Through bootstrap confidence bands, we find that the factor loading for total nitrate changes across seasons and geographic regions.
Trait Sources of Spirituality Scale: Assessing Trait Spirituality More Inclusively

ERIC Educational Resources Information Center

Westbrook, Charles J.; Davis, Don E.; McElroy, Stacey E.; Brubaker, Kacy; Choe, Elise; Karaga, Sara; Dooley, Matt; O'Bryant, Brittany L.; Van Tongeren, Daryl R.; Hook, Joshua

2018-01-01

We develop the Trait Sources of Spirituality Scale (TSSS), which assesses experiences of closeness to the sacred, within and outside a religious tradition. After using factor analysis to finalize the scale, we examine evidence of construct validity, including latent profile analysis that reveals 5 patterns of how spirituality is experienced.
The Latent Structure of Memory: A Confirmatory Factor-Analytic Study of Memory Distinctions.

ERIC Educational Resources Information Center

Herrman, Douglas J.; Schooler, Carmi; Caplan, Leslie J.; Lipman, Paula Darby; Grafman, Jordan; Schoenbach, Carrie; Schwab, Karen; Johnson, Marnie L.

2001-01-01

Used confirmatory factor analysis to study the nature of memory distinctions underlying the performance of two samples of Vietnam veterans. One sample (n=96) had received head injuries resulting in relatively small lesions; the other (n=85) had not. A four-component model with verbal-episodic, visual-episodic, semantic, and short-term memory…
Relating Factor Models for Longitudinal Data to Quasi-Simplex and NARMA Models

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

2005-01-01

In this article we show the one-factor model can be rewritten as a quasi-simplex model. Using this result along with addition theorems from time series analysis, we describe a common general model, the nonstationary autoregressive moving average (NARMA) model, that includes as a special case, any latent variable model with continuous indicators…
Interaction of Dopamine Transporter (DAT1) Genotype and Maltreatment for ADHD: A Latent Class Analysis

ERIC Educational Resources Information Center

Li, James J.; Lee, Steve S.

2012-01-01

Background: Although the association of the dopamine transporter (DAT1) gene and attention-deficit/hyperactivity disorder (ADHD) has been widely studied, far less is known about its potential interaction with environmental risk factors. Given that maltreatment is a replicated risk factor for ADHD, we explored the interaction between DAT1 and…
ADHD and Method Variance: A Latent Variable Approach Applied to a Nationally Representative Sample of College Freshmen

ERIC Educational Resources Information Center

Konold, Timothy R.; Glutting, Joseph J.

2008-01-01

This study employed a correlated trait-correlated method application of confirmatory factor analysis to disentangle trait and method variance from measures of attention-deficit/hyperactivity disorder obtained at the college level. The two trait factors were "Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition" ("DSM-IV")…
Specificity of disgust domains in the prediction of contamination anxiety and avoidance: a multimodal examination.

PubMed

Olatunji, Bunmi O; Ebesutani, Chad; Haidt, Jonathan; Sawchuk, Craig N

2014-07-01

Although core, animal-reminder, and contamination disgust are viewed as distinct "types" of disgust vulnerabilities, the extent to which individual differences in the three disgust domains uniquely predict contamination-related anxiety and avoidance remains unclear. Three studies were conducted to fill this important gap in the literature. Study 1 was conducted to first determine if the three types of disgust could be replicated in a larger and more heterogeneous sample. Confirmatory factor analysis revealed that a bifactor model consisting of a "general disgust" dimension and the three distinct disgust dimensions yielded a better fit than a one-factor model. Structural equation modeling in Study 2 showed that while latent core, animal-reminder, and contamination disgust factors each uniquely predicted a latent "contamination anxiety" factor above and beyond general disgust, only animal-reminder uniquely predicted a latent "non-contamination anxiety" factor above and beyond general disgust. However, Study 3 found that only contamination disgust uniquely predicted behavioral avoidance in a public restroom where contamination concerns are salient. These findings suggest that although the three disgust domains are associated with contamination anxiety and avoidance, individual differences in contamination disgust sensitivity appear to be most uniquely predictive of contamination-related distress. The implications of these findings for the development and maintenance of anxiety-related disorders marked by excessive contamination concerns are discussed. Copyright © 2014. Published by Elsevier Ltd.
A Note on Cluster Effects in Latent Class Analysis

ERIC Educational Resources Information Center

Kaplan, David; Keller, Bryan

2011-01-01

This article examines the effects of clustering in latent class analysis. A comprehensive simulation study is conducted, which begins by specifying a true multilevel latent class model with varying within- and between-cluster sample sizes, varying latent class proportions, and varying intraclass correlations. These models are then estimated under…
Who Should Be Targeted for the Prevention of Birth Defects? A Latent Class Analysis Based on a Large, Population-Based, Cross-Sectional Study in Shaanxi Province, Western China.

PubMed

Zhu, Zhonghai; Cheng, Yue; Yang, Wenfang; Li, Danyang; Yang, Xue; Liu, Danli; Zhang, Min; Yan, Hong; Zeng, Lingxia

2016-01-01

The wide range and complex combinations of factors that cause birth defects impede the development of primary prevention strategies targeted at high-risk subpopulations. Latent class analysis (LCA) was conducted to identify mutually exclusive profiles of factors associated with birth defects among women between 15 and 49 years of age using data from a large, population-based, cross-sectional study conducted in Shaanxi Province, western China, between August and October, 2013. The odds ratios (ORs) and 95% confidence intervals (CIs) of associated factors and the latent profiles of indicators of birth defects and congenital heart defects were computed using a logistic regression model. Five discrete subpopulations of participants were identified as follows: No folic acid supplementation in the periconceptional period (reference class, 21.37%); low maternal education level + unhealthy lifestyle (class 2, 39.75%); low maternal education level + unhealthy lifestyle + disease (class 3, 23.71%); unhealthy maternal lifestyle + advanced age (class 4, 4.71%); and multi-risk factor exposure (class 5, 10.45%). Compared with the reference subgroup, the other subgroups consistently had a significantly increased risk of birth defects (ORs and 95% CIs: class 2, 1.75 and 1.21-2.54; class 3, 3.13 and 2.17-4.52; class 4, 5.02 and 3.20-7.88; and class 5, 12.25 and 8.61-17.42, respectively). For congenital heart defects, the ORs and 95% CIs were all higher, and the magnitude of OR differences ranged from 1.59 to 16.15. A comprehensive intervention strategy targeting maternal exposure to multiple risk factors is expected to show the strongest results in preventing birth defects.
The influence of mindfulness, self-compassion, psychological flexibility, and posttraumatic stress disorder on disability and quality of life over time in war veterans.

PubMed

Meyer, Eric C; Frankfurt, Sheila B; Kimbrel, Nathan A; DeBeer, Bryann B; Gulliver, Suzy B; Morrisette, Sandra B

2018-07-01

Posttraumatic stress disorder (PTSD) strongly predicts greater disability and lower quality of life (QOL). Mindfulness-based and other third-wave behavior therapy interventions improve well-being by enhancing mindfulness, self-compassion, and psychological flexibility. We hypothesized that these mechanisms of therapeutic change would comprise a single latent factor that would predict disability and QOL after accounting for PTSD symptom severity. Iraq and Afghanistan war veterans (N = 117) completed a study of predictors of successful reintegration. Principal axis factor analysis tested whether mindfulness, self-compassion, and psychological flexibility comprised a single latent factor. Hierarchical regression tested whether this factor predicted disability and QOL 1 year later. Mindfulness, self-compassion, and psychological flexibility comprised a single factor that predicted disability and QOL after accounting for PTSD symptom severity. PTSD symptoms remained a significant predictor of disability but not QOL. Targeting these mechanisms may help veterans achieve functional recovery, even in the presence of PTSD symptoms. © 2018 Wiley Periodicals, Inc.
Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.
Testing for measurement invariance and latent mean differences across methods: interesting incremental information from multitrait-multimethod studies

PubMed Central

Geiser, Christian; Burns, G. Leonard; Servera, Mateu

2014-01-01

Models of confirmatory factor analysis (CFA) are frequently applied to examine the convergent validity of scores obtained from multiple raters or methods in so-called multitrait-multimethod (MTMM) investigations. We show that interesting incremental information about method effects can be gained from including mean structures and tests of MI across methods in MTMM models. We present a modeling framework for testing MI in the first step of a CFA-MTMM analysis. We also discuss the relevance of MI in the context of four more complex CFA-MTMM models with method factors. We focus on three recently developed multiple-indicator CFA-MTMM models for structurally different methods [the correlated traits-correlated (methods – 1), latent difference, and latent means models; Geiser et al., 2014a; Pohl and Steyer, 2010; Pohl et al., 2008] and one model for interchangeable methods (Eid et al., 2008). We demonstrate that some of these models require or imply MI by definition for a proper interpretation of trait or method factors, whereas others do not, and explain why MI may or may not be required in each model. We show that in the model for interchangeable methods, testing for MI is critical for determining whether methods can truly be seen as interchangeable. We illustrate the theoretical issues in an empirical application to an MTMM study of attention deficit and hyperactivity disorder (ADHD) with mother, father, and teacher ratings as methods. PMID:25400603
Reactivation of Latent HIV-1 Expression by Engineered TALE Transcription Factors.

PubMed

Perdigão, Pedro; Gaj, Thomas; Santa-Marta, Mariana; Barbas, Carlos F; Goncalves, Joao

2016-01-01

The presence of replication-competent HIV-1 -which resides mainly in resting CD4+ T cells--is a major hurdle to its eradication. While pharmacological approaches have been useful for inducing the expression of this latent population of virus, they have been unable to purge HIV-1 from all its reservoirs. Additionally, many of these strategies have been associated with adverse effects, underscoring the need for alternative approaches capable of reactivating viral expression. Here we show that engineered transcriptional modulators based on customizable transcription activator-like effector (TALE) proteins can induce gene expression from the HIV-1 long terminal repeat promoter, and that combinations of TALE transcription factors can synergistically reactivate latent viral expression in cell line models of HIV-1 latency. We further show that complementing TALE transcription factors with Vorinostat, a histone deacetylase inhibitor, enhances HIV-1 expression in latency models. Collectively, these findings demonstrate that TALE transcription factors are a potentially effective alternative to current pharmacological routes for reactivating latent virus and that combining synthetic transcriptional activators with histone deacetylase inhibitors could lead to the development of improved therapies for latent HIV-1 infection.

The household-based socio-economic deprivation index in Setiu Wetlands, Malaysia

NASA Astrophysics Data System (ADS)

Zakaria, Syerrina; May, Chin Sin; Rahman, Nuzlinda Abdul

2017-08-01

Deprivation index usually used in public health study. At the same time, deprivation index can also use to measure the level of deprivation in an area or a village. These indices are also referred as the index of inequalities or disadvantage. Even though, there are many indices that have been built before. But it is believed to be less appropriate to use the existing indices to be applied in other countries or areas which had different socio-economic conditions and different geographical characteristics. The objective of this study is to construct the index based on the socio-economic factors in Setiu Wetlands (Jajaran Merang, Jajaran Setiu and Jajaran Kuala Besut) in Terengganu Malaysia which is defined as weighted household-based socioeconomic deprivation index. This study has employed the variables based on income level, education level and employment rate obtained from questionnaire which are acquired from 64 villages included 1024 respondents. The factor analysis is used to extract the latent variables or observed variables into smaller amount of components or factors. By using factor analysis, one factor is extracted from 3 latent variables. This factor known as socioeconomic deprivation index. Based on the result, the areas with a lower index values until high index values were identified.
The Shame and Guilt Scales of the Test of Self-Conscious Affect-Adolescent (TOSCA-A): Factor Structure, Concurrent and Discriminant Validity, and Measurement and Structural Invariance Across Ratings of Males and Females.

PubMed

Watson, Shaun; Gomez, Rapson; Gullone, Eleonora

2017-06-01

This study examined various psychometric properties of the items comprising the shame and guilt scales of the Test of Self-Conscious Affect-Adolescent. A total of 563 adolescents (321 females and 242 males) completed these scales, and also measures of depression and empathy. Confirmatory factor analysis provided support for an oblique two-factor model, with the originally proposed shame and guilt items comprising shame and guilt factors, respectively. Also, shame correlated with depression positively and had no relation with empathy. Guilt correlated with depression negatively and with empathy positively. Thus, there was support for the convergent and discriminant validity of the shame and guilt factors. Multiple-group confirmatory factor analysis comparing females and males, based on the chi-square difference test, supported full metric invariance, the intercept invariance of 26 of the 30 shame and guilt items, and higher latent mean scores among females for both shame and guilt. Comparisons based on the difference in root mean squared error of approximation values supported full measurement invariance and no gender difference for latent mean scores. The psychometric and practical implications of the findings are discussed.
Detecting Mixtures from Structural Model Differences Using Latent Variable Mixture Modeling: A Comparison of Relative Model Fit Statistics

ERIC Educational Resources Information Center

Henson, James M.; Reise, Steven P.; Kim, Kevin H.

2007-01-01

The accuracy of structural model parameter estimates in latent variable mixture modeling was explored with a 3 (sample size) [times] 3 (exogenous latent mean difference) [times] 3 (endogenous latent mean difference) [times] 3 (correlation between factors) [times] 3 (mixture proportions) factorial design. In addition, the efficacy of several…
Refinements of Stout’s Procedure for Assessing Latent Trait Unidimensionality

DTIC Science & Technology

1992-08-01

in the presence of guessing when coupled with many high-discriminating items. A revision of DIMTEST is proposed to overcome this limitation. Also, an...used for factor analysis. When guessing is present in the responses to items, however, linear factor analysis of tetrachoric correlations can produce...significance when d=1 and maintaining good power when d=2, even when the correlation between the abilities is as high as .7. The present study provides a
Self-efficacy difference among patients with cancer with different socioeconomic status: application of latent class analysis and standardization and decomposition analysis.

PubMed

Yuan, Changrong; Wei, Chunlan; Wang, Jichuan; Qian, Huijuan; Ye, Xianghong; Liu, Yingyan; Hinds, Pamela S

2014-06-01

Although the relationship between partial socioeconomic status (SES) and self-efficacy has been studied in previous studies, few research have examined self-efficacy difference among patients with cancer with different SES. A cross-sectional survey involving 764 patients with cancer was completed. Latent class analysis (LCA) was applied to identify distinct groups of patients with cancer using four SES indicators (education, income, employment status and health insurance status). Standardization and decomposition analysis (SDA) was then used to examine differences in patients' self-efficacy among SES groups and the components of the differences attributed to confounding factors, such as gender, age, anxiety, depression and social support. Participants were classified into four distinctive SES groups via using LCA method, and the observed self-efficacy level significantly varied by SES groups; as theorized, higher self-efficacy was associated with higher SES. The self-efficacy differences by SES groups were decomposed into "real" group differences and factor component effects that are attributed to group differences in confounding factor compositions. Self-efficacy significantly varies by SES. Social support significantly confounded the observed differences in self-efficacy between different SES groups among Chinese patients with cancer. Copyright © 2014 Elsevier Ltd. All rights reserved.
Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text

PubMed Central

Xin, Yu; Hochberg, Ephraim; Joshi, Rohit; Uzuner, Ozlem; Szolovits, Peter

2015-01-01

Objective Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxes. Moreover, training data for these automated approaches at often sparsely annotated at best. The authors target unsupervised learning for modeling clinical narrative text, aiming at improving both accuracy and interpretability. Methods The authors introduce a novel framework named subgraph augmented non-negative tensor factorization (SANTF). In addition to relying on atomic features (e.g., words in clinical narrative text), SANTF automatically mines higher-order features (e.g., relations of lymphoid cells expressing antigens) from clinical narrative text by converting sentences into a graph representation and identifying important subgraphs. The authors compose a tensor using patients, higher-order features, and atomic features as its respective modes. We then apply non-negative tensor factorization to cluster patients, and simultaneously identify latent groups of higher-order features that link to patient clusters, as in clinical guidelines where a panel of immunophenotypic features and laboratory results are used to specify diagnostic criteria. Results and Conclusion SANTF demonstrated over 10% improvement in averaged F-measure on patient clustering compared to widely used non-negative matrix factorization (NMF) and k-means clustering methods. Multiple baselines were established by modeling patient data using patient-by-features matrices with different feature configurations and then performing NMF or k-means to cluster patients. Feature analysis identified latent groups of higher-order features that lead to medical insights. We also found that the latent groups of atomic features help to better correlate the latent groups of higher-order features. PMID:25862765
Fall Risk, Supports and Services, and Falls Following a Nursing Home Discharge.

PubMed

Noureldin, Marwa; Hass, Zachary; Abrahamson, Kathleen; Arling, Greg

2017-09-04

Falls are a major source of morbidity and mortality among older adults; however, little is known regarding fall occurrence during a nursing home (NH) to community transition. This study sought to examine whether the presence of supports and services impacts the relationship between fall-related risk factors and fall occurrence post NH discharge. Participants in the Minnesota Return to Community Initiative who were assisted in achieving a community discharge (N = 1459) comprised the study sample. The main outcome was fall occurrence within 30 days of discharge. Factor analyses were used to estimate latent models from variables of interest. A structural equation model (SEM) was estimated to determine the relationship between the emerging latent variables and falls. Fifteen percent of participants fell within 30 days of NH discharge. Factor analysis of fall-related risk factors produced three latent variables: fall concerns/history; activities of daily living impairments; and use of high-risk medications. A supports/services latent variable also emerged that included caregiver support frequency, medication management assistance, durable medical equipment use, discharge location, and receipt of home health or skilled nursing services. In the SEM model, high-risk medications use and fall concerns/history had direct positive effects on falling. Receiving supports/services did not affect falling directly; however, it reduced the effect of high-risk medication use on falling (p < .05). Within the context of a state-implemented transition program, findings highlight the importance of supports/services in mitigating against medication-related risk of falling post NH discharge. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches.

PubMed

Yang, Jun-Ho; Yoh, Jack J

2018-01-01

A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.
Multifactor valuation models of energy futures and options on futures

NASA Astrophysics Data System (ADS)

Bertus, Mark J.

The intent of this dissertation is to investigate continuous time pricing models for commodity derivative contracts that consider mean reversion. The motivation for pricing commodity futures and option on futures contracts leads to improved practical risk management techniques in markets where uncertainty is increasing. In the dissertation closed-form solutions to mean reverting one-factor, two-factor, three-factor Brownian motions are developed for futures contracts. These solutions are obtained through risk neutral pricing methods that yield tractable expressions for futures prices, which are linear in the state variables, hence making them attractive for estimation. These functions, however, are expressed in terms of latent variables (i.e. spot prices, convenience yield) which complicate the estimation of the futures pricing equation. To address this complication a discussion on Dynamic factor analysis is given. This procedure documents latent variables using a Kalman filter and illustrations show how this technique may be used for the analysis. In addition, to the futures contracts closed form solutions for two option models are obtained. Solutions to the one- and two-factor models are tailored solutions of the Black-Scholes pricing model. Furthermore, since these contracts are written on the futures contracts, they too are influenced by the same underlying parameters of the state variables used to price the futures contracts. To conclude, the analysis finishes with an investigation of commodity futures options that incorporate random discrete jumps.
Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.
Comparison of Factor Simplicity Indices for Dichotomous Data: DETECT R, Bentler's Simplicity Index, and the Loading Simplicity Index

ERIC Educational Resources Information Center

Finch, Holmes; Stage, Alan Kirk; Monahan, Patrick

2008-01-01

A primary assumption underlying several of the common methods for modeling item response data is unidimensionality, that is, test items tap into only one latent trait. This assumption can be assessed several ways, using nonlinear factor analysis and DETECT, a method based on the item conditional covariances. When multidimensionality is identified,…
Well-Being, School Climate, and the Social Identity Process: A Latent Growth Model Study of Bullying Perpetration and Peer Victimization

ERIC Educational Resources Information Center

Turner, Isobel; Reynolds, Katherine J.; Lee, Eunro; Subasic, Emina; Bromhead, David

2014-01-01

The present study concerns longitudinal research on bullying perpetration and peer victimization. A focus is on school factors of school climate (academic support, group support) and school identification (connectedness or belonging), which are conceptualized as related but distinct constructs. Analysis of change on these factors as well as…
A Confirmatory Factor Analysis of the California Verbal Learning Test-Second Edition (CVLT-II) in the Standardization Sample

ERIC Educational Resources Information Center

Donders, Jacobus

2008-01-01

The purpose of this study is to determine the latent structure of the California Verbal Learning Test-Second Edition (CVLT-II; Delis, Kramer, Kaplan, & Ober, 2000) at three different age levels, using the standardization sample. Maximum likelihood confirmatory factor analyses are performed to test four competing hypothetical models for fit and…
Multidimensional Self-Concept Structure for Preadolescents with Mild Intellectual Disabilities: A Hybrid Multigroup?MIMC Approach to Factorial Invariance and Latent Mean Differences

ERIC Educational Resources Information Center

Marsh, Herbert W.; Tracey, Danielle K.; Craven, Rhonda G.

2006-01-01

Confirmatory factor analysis of responses by 211 preadolescents (M age = 10.25 years,SD = 1.48) with mild intellectual disabilities (MIDs) to the individually administered Self Description Questionnaire I-Individual Administration (SDQI-IA) counters widely cited claims that these children cannot differentiate multiple self-concept factors. Results…
The Learning and Study Strategies Inventory-High School Version: Issues of Factorial Invariance Across Gender and Ethnicity

ERIC Educational Resources Information Center

Stevens, Tara; Tallent-Runnels, Mary K.

2004-01-01

The purpose of this study was to investigate the latent structure of the Learning and Study Strategies Inventory-High School (LASSI-HS) through confirmatory factor analysis and factorial invariance models. A simple modification of the three-factor structure was considered. Using a larger sample, cross-validation was completed and the equality of…
Using Comparison Data to Differentiate Categorical and Dimensional Data by Examining Factor Score Distributions: Resolving the Mode Problem

ERIC Educational Resources Information Center

Ruscio, John; Walters, Glenn D.

2009-01-01

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…
Multimethod latent class analysis

PubMed Central

Nussbeck, Fridtjof W.; Eid, Michael

2015-01-01

Correct and, hence, valid classifications of individuals are of high importance in the social sciences as these classifications are the basis for diagnoses and/or the assignment to a treatment. The via regia to inspect the validity of psychological ratings is the multitrait-multimethod (MTMM) approach. First, a latent variable model for the analysis of rater agreement (latent rater agreement model) will be presented that allows for the analysis of convergent validity between different measurement approaches (e.g., raters). Models of rater agreement are transferred to the level of latent variables. Second, the latent rater agreement model will be extended to a more informative MTMM latent class model. This model allows for estimating (i) the convergence of ratings, (ii) method biases in terms of differential latent distributions of raters and differential associations of categorizations within raters (specific rater bias), and (iii) the distinguishability of categories indicating if categories are satisfyingly distinct from each other. Finally, an empirical application is presented to exemplify the interpretation of the MTMM latent class model. PMID:26441714
Evidence for the Continuous Latent Structure of Mania in the Epidemiologic Catchment Area from Multiple Latent Structure and Construct Validation Methodologies

PubMed Central

Prisciandaro, James J.; Roberts, John E.

2011-01-01

Background Although psychiatric diagnostic systems have conceptualized mania as a discrete phenomenon, appropriate latent structure investigations testing this conceptualization are lacking. In contrast to these diagnostic systems, several influential theories of mania have suggested a continuous conceptualization. The present study examined whether mania has a continuous or discrete latent structure using a comprehensive approach including taxometric, information-theoretic latent distribution modeling (ITLDM), and predictive validity methodologies in the Epidemiologic Catchment Area (ECA) study. Methods Eight dichotomous manic symptom items were submitted to a variety of latent structural analyses; including factor analyses, taxometric procedures, and ITLDM; in 10,105 ECA community participants. Additionally, a variety of continuous and discrete models of mania were compared in terms of their relative abilities to predict outcomes (i.e., health service utilization, internalizing and externalizing disorders, and suicidal behavior). Results Taxometric and ITLDM analyses consistently supported a continuous conceptualization of mania. In ITLDM analyses, a continuous model of mania demonstrated 6:52:1 odds over the best fitting latent class model of mania. Factor analyses suggested that the continuous structure of mania was best represented by a single latent factor. Predictive validity analyses demonstrated a consistent superior ability of continuous models of mania relative to discrete models. Conclusions The present study provided three independent lines of support for a continuous conceptualization of mania. The implications of a continuous model of mania are discussed. PMID:20507671
Prevalence and risk factors for latent tuberculosis infection among healthcare workers in Nampula Central Hospital, Mozambique.

PubMed

Belo, Celso; Naidoo, Saloshni

2017-06-08

Healthcare workers in high tuberculosis burdened countries are occupationally exposed to the tuberculosis disease with uncomplicated and complicated tuberculosis on the increase among them. Most of them acquire Mycobacterium tuberculosis but do not progress to the active disease - latent tuberculosis infection. The objective of this study was to assess the prevalence and risk factors associated with latent tuberculosis infection among healthcare workers in Nampula Central Hospital, Mozambique. This cross-sectional study of healthcare workers was conducted between 2014 and 2015. Participants (n = 209) were administered a questionnaire on demographics and occupational tuberculosis exposure and had a tuberculin skin test administered. Multivariate linear and logistic regression tested for associations between independent variables and dependent outcomes (tuberculin skin test induration and latent tuberculosis infection status). The prevalence of latent tuberculosis infection was 34.4%. Latent tuberculosis infection was highest in those working for more than eight years (39.3%), those who had no BCG vaccination (39.6%) and were immunocompromised (78.1%). Being immunocompromised was significantly associated with latent tuberculosis infection (OR 5.97 [95% CI 1.89; 18.87]). Positive but non-significant associations occurred with working in the medical domain (OR 1.02 [95% CI 0.17; 6.37]), length of employment > eight years (OR 1.97 [95% CI 0.70; 5.53]) and occupational contact with tuberculosis patients (OR 1.24 [95% CI 0.47; 3.27]). Personal and occupational factors were positively associated with latent tuberculosis infection among healthcare workers in Mozambique.
Latent dimensions of posttraumatic stress disorder and their relations with alcohol use disorder.

PubMed

Biehn, Tracey L; Contractor, Ateka A; Elhai, Jon D; Tamburrino, Marijo; Fine, Thomas H; Cohen, Gregory; Shirley, Edwin; Chan, Philip K; Liberzon, Israel; Calabrese, Joseph R; Galea, Sandro

2016-03-01

The objective of this study was to evaluate the relationship between factors of posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) using confirmatory factor analysis (CFA) in order to further our understanding of the substantial comorbidity between these two disorders. CFA was used to examine which factors of PTSD's dysphoria model were most related to AUD in a military sample. Ohio National Guard soldiers with a history of overseas deployment participated in the survey (n = 1215). Participants completed the PTSD Checklist and a 12-item survey from the National Survey on Drug Use used to diagnosis AUD. The results of the CFA indicated that a combined model of PTSD's four factors and a single AUD factor fit the data very well. Correlations between PTSD's factors and a latent AUD factor ranged from correlation coefficients of 0.258-0.285, with PTSD's dysphoria factor demonstrating the strongest correlation. However, Wald tests of parameter constraints revealed that AUD was not more correlated with PTSD's dysphoria than other PTSD factors. All four factors of PTSD's dysphoria model demonstrate comparable correlations with AUD. The role of dysphoria to the construct of PTSD is discussed.

Construct validity evidence for the Male Role Norms Inventory-Short Form: A structural equation modeling approach using the bifactor model.

PubMed

Levant, Ronald F; Hall, Rosalie J; Weigold, Ingrid K; McCurdy, Eric R

2016-10-01

The construct validity of the Male Role Norms Inventory-Short Form (MRNI-SF) was assessed using a latent variable approach implemented with structural equation modeling (SEM). The MRNI-SF was specified as having a bifactor structure, and validation scales were also specified as latent variables. The latent variable approach had the advantages of separating effects of general and specific factors and controlling for some sources of measurement error. Data (N = 484) were from a diverse sample (38.8% men of color, 22.3% men of diverse sexualities) of community-dwelling and college men who responded to an online survey. The construct validity of the MRNI-SF General Traditional Masculinity Ideology factor was supported for all 4 of the proposed latent correlations with: (a) Male Role Attitudes Scale; (b) general factor of Conformity to Masculine Norms Inventory-46; (c) higher-order factor of Gender Role Conflict Scale; and (d) Personal Attributes Questionnaire-Masculinity Scale. Significant correlations with relevant other latent factors provided concurrent validity evidence for the MRNI-SF specific factors of Negativity toward Sexual Minorities, Importance of Sex, Restrictive Emotionality, and Toughness, with all 8 of the hypothesized relationships supported. However, 3 relationships concerning Dominance were not supported. (The construct validity of the remaining 2 MRNI-SF specific factors-Avoidance of Femininity and Self-Reliance through Mechanical Skills was not assessed.) Comparisons were made, and meaningful differences noted, between the latent correlations emphasized in this study and their raw variable counterparts. Results are discussed in terms of the advantages of an SEM approach and the unique characteristics of the bifactor model. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
The perception of the relationship between environment and health according to data from Italian Behavioural Risk Factor Surveillance System (PASSI).

PubMed

Sampaolo, Letizia; Tommaso, Giulia; Gherardi, Bianca; Carrozzi, Giuliano; Freni Sterrantino, Anna; Ottone, Marta; Goldoni, Carlo Alberto; Bertozzi, Nicoletta; Scaringi, Meri; Bolognesi, Lara; Masocco, Maria; Salmaso, Stefania; Lauriola, Paolo

2017-01-01

"OBJECTIVES: to identify groups of people in relation to the perception of environmental risk and to assess the main characteristics using data collected in the environmental module of the surveillance network Italian Behavioral Risk Factor Surveillance System (PASSI). perceptive profiles were identified using a latent class analysis; later they were included as outcome in multinomial logistic regression models to assess the association between environmental risk perception and demographic, health, socio-economic and behavioural variables. the latent class analysis allowed to split the sample in "worried", "indifferent", and "positive" people. The multinomial logistic regression model showed that the "worried" profile typically includes people of Italian nationality, living in highly urbanized areas, with a high level of education, and with economic difficulties; they pay special attention to their own health and fitness, but they have a negative perception of their own psychophysical state. the application of advanced statistical analysis enable to appraise PASSI data in order to characterize the perception of environmental risk, making the planning of interventions related to risk communication possible. ".
An NCME Instructional Module on Latent DIF Analysis Using Mixture Item Response Models

ERIC Educational Resources Information Center

Cho, Sun-Joo; Suh, Youngsuk; Lee, Woo-yeol

2016-01-01

The purpose of this ITEMS module is to provide an introduction to differential item functioning (DIF) analysis using mixture item response models. The mixture item response models for DIF analysis involve comparing item profiles across latent groups, instead of manifest groups. First, an overview of DIF analysis based on latent groups, called…
Latent Transition Analysis of Pre-Service Teachers' Efficacy in Mathematics and Science

ERIC Educational Resources Information Center

Ward, Elizabeth Kennedy

2009-01-01

This study modeled changes in pre-service teacher efficacy in mathematics and science over the course of the final year of teacher preparation using latent transition analysis (LTA), a longitudinal form of analysis that builds on two modeling traditions (latent class analysis (LCA) and auto-regressive modeling). Data were collected using the…
Disgust proneness predicts obsessive-compulsive disorder symptom severity in a clinical sample of youth: Distinctions from negative affect.

PubMed

Olatunji, Bunmi O; Ebesutani, Chad; Kim, Jingu; Riemann, Bradley C; Jacobi, David M

2017-04-15

Although studies have linked disgust proneness to the etiology and maintenance of obsessive-compulsive disorder (OCD) in adults, there remains a paucity of research examining the specificity of this association among youth. The present study employed structural equation modeling to examine the association between disgust proneness, negative affect, and OCD symptom severity in a clinical sample of youth admitted to a residential treatment facility (N =471). Results indicate that disgust proneness and negative affect latent factors independently predicted an OCD symptom severity latent factor. However, when both variables were modeled as predictors simultaneously, latent disgust proneness remained significantly associated with OCD symptom severity, whereas the association between latent negative affect and OCD symptom severity became nonsignificant. Tests of mediation converged in support of disgust proneness as a significant intervening variable between negative affect and OCD symptom severity. Subsequent analysis showed that the path from disgust proneness to OCD symptom severity in the structural model was significantly stronger among those without a primary diagnosis of OCD compared to those with a primary diagnosis of OCD. Given the cross-sectional design, the causal inferences that can be made are limited. The present study is also limited by the exclusive reliance on self-report measures. Disgust proneness may play a uniquely important role in OCD among youth. Copyright © 2017 Elsevier B.V. All rights reserved.
Patterns of Chronic Conditions and Their Associations With Behaviors and Quality of Life, 2010

PubMed Central

Mitchell, Sandra A.; Thompson, William W.; Zack, Matthew M.; Reeve, Bryce B.; Cella, David; Smith, Ashley Wilder

2015-01-01

Introduction Co-occurring chronic health conditions elevate the risk of poor health outcomes such as death and disability, are associated with poor quality of life, and magnify the complexities of self-management, care coordination, and treatment planning. This study assessed patterns of both singular and multiple chronic conditions, behavioral risk factors, and quality of life in a population-based sample. Methods In a national survey, adults (n = 4,184) answered questions about the presence of 27 chronic conditions. We used latent class analysis to identify patterns of chronic conditions and to explore associations of latent class membership with sociodemographic characteristics, behavioral risk factors, and health. Results Latent class analyses indicated 4 morbidity profiles: a healthy class (class 1), a class with predominantly physical health conditions (class 2), a class with predominantly mental health conditions (class 3), and a class with both physical and mental health conditions (class 4). Class 4 respondents reported significantly worse physical health and well-being and more days of activity limitation than those in the other latent classes. Class 4 respondents were also more likely to be obese and sedentary, and those with predominantly mental health conditions were most likely to be current smokers. Conclusions Subgroups with distinct patterns of chronic conditions can provide direction for screening and surveillance, guideline development, and the delivery of complex care services. PMID:26679491
Mental toughness latent profiles in endurance athletes

PubMed Central

Zeiger, Robert S.

2018-01-01

Mental toughness in endurance athletes, while an important factor for success, has been scarcely studied. An online survey was used to examine eight mental toughness factors in endurance athletes. The study aim was to determine mental toughness profiles via latent profile analysis in endurance athletes and whether associations exist between the latent profiles and demographics and sports characteristics. Endurance athletes >18 years of age were recruited via social media outlets (n = 1245, 53% female). Mental toughness was measured using the Sports Mental Toughness Questionnaire (SMTQ), Psychological Performance Inventory-Alternative (PPI-A), and self-esteem was measured using the Rosenberg Self-Esteem Scale (RSE). A three-class solution emerged, designated as high mental toughness (High MT), moderate mental toughness (Moderate MT) and low mental toughness (Low MT). ANOVA tests showed significant differences between all three classes on all 8 factors derived from the SMTQ, PPI-A and the RSE. There was an increased odds of being in the High MT class compared to the Low MT class for males (OR = 1.99; 95% CI, 1.39, 2.83; P<0.001), athletes who were over 55 compared to those who were 18–34 (OR = 2.52; 95% CI, 1.37, 4.62; P<0.01), high sports satisfaction (OR = 8.17; 95% CI, 5.63, 11.87; P<0.001), and high division placement (OR = 2.18; 95% CI, 1.46,3.26; P<0.001). The data showed that mental toughness latent profiles exist in endurance athletes. High MT is associated with demographics and sports characteristics. Mental toughness screening in athletes may help direct practitioners with mental skills training. PMID:29474398
The construct of maternal positivity in mothers of children with intellectual disability.

PubMed

Jess, M; Hastings, R P; Totsika, V

2017-10-01

Despite the elevated levels of stress, anxiety and depression reported by mothers of children with intellectual disabilities (ID), these mothers also experience positive well-being and describe positive perceptions of their child. To date, maternal positivity has been operationalised in different ways by using a variety of measures. In the present study, we tested whether a latent construct of maternal positivity could be derived from different measures of positivity. One hundred and thirty-five mothers of 89 boys and 46 girls with ID between 3 and 18 years of age completed measures on parental self-efficacy, their satisfaction with life, family satisfaction, their positive affect and their positive perceptions of their child with ID. We conducted a confirmatory factor analysis of latent positivity and subsequently tested its association with child social skills and behaviour problems, and maternal mental health. A latent maternal positivity factor achieved a statistically good fit by using the five observed indicators of positivity. Parental self-efficacy had the strongest loading on the latent factor. Maternal positivity was significantly negatively associated with maternal psychological distress, maternal stress and child problem behaviours and positively associated with child positive social behaviour. These findings lend support to the importance of examining parental positivity in families raising a child with ID, and using multiple indicators of positivity. Associations with negative psychological outcomes suggest that interventions focused on increasing parental positivity may have beneficial effects for parents. Further research is needed, especially in relation to such interventions. © 2017 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.
Invariance of parent ratings of the ADHD symptoms in Australian and Malaysian, and north European Australian and Malay Malaysia children: a mean and covariance structures analysis approach.

PubMed

Gomez, Rapson

2009-03-01

This study used the mean and covariance structures analysis approach to examine the equality or invariance of ratings of the 18 ADHD symptoms. 783 Australian and 928 Malaysian parents provided ratings for an ADHD rating scale. Invariance was tested across these groups (Comparison 1), and North European Australian (n = 623) and Malay Malaysian (n = 571, Comparison 2) groups. Results indicate support for form and item factor loading invariance; more than half the total number of symptoms showed item intercept invariance, and 14 symptoms showed invariance for error variances. There was invariance for both the factor variances and the covariance, and the latent mean scores for hyperactivity/impulsivity. For inattention latent scores, the Malaysian (Comparison 1) and Malay Malaysian (Comparison 2) groups had higher scores. These results indicate fairly good support for invariance for parent ratings of the ADHD symptoms across the groups compared.
Item Response Theory Analyses of the Cambridge Face Memory Test (CFMT)

PubMed Central

Cho, Sun-Joo; Wilmer, Jeremy; Herzmann, Grit; McGugin, Rankin; Fiset, Daniel; Van Gulick, Ana E.; Ryan, Katie; Gauthier, Isabel

2014-01-01

We evaluated the psychometric properties of the Cambridge face memory test (CFMT; Duchaine & Nakayama, 2006). First, we assessed the dimensionality of the test with a bi-factor exploratory factor analysis (EFA). This EFA analysis revealed a general factor and three specific factors clustered by targets of CFMT. However, the three specific factors appeared to be minor factors that can be ignored. Second, we fit a unidimensional item response model. This item response model showed that the CFMT items could discriminate individuals at different ability levels and covered a wide range of the ability continuum. We found the CFMT to be particularly precise for a wide range of ability levels. Third, we implemented item response theory (IRT) differential item functioning (DIF) analyses for each gender group and two age groups (Age ≤ 20 versus Age > 21). This DIF analysis suggested little evidence of consequential differential functioning on the CFMT for these groups, supporting the use of the test to compare older to younger, or male to female, individuals. Fourth, we tested for a gender difference on the latent facial recognition ability with an explanatory item response model. We found a significant but small gender difference on the latent ability for face recognition, which was higher for women than men by 0.184, at age mean 23.2, controlling for linear and quadratic age effects. Finally, we discuss the practical considerations of the use of total scores versus IRT scale scores in applications of the CFMT. PMID:25642930
Heterogeneity in the Latent Structure of PTSD Symptoms among Canadian Veterans

ERIC Educational Resources Information Center

Naifeh, James A.; Richardson, J. Don; Del Ben, Kevin S.; Elhai, Jon D.

2010-01-01

The current study used factor mixture modeling to identify heterogeneity (i.e., latent classes) in 2 well-supported models of posttraumatic stress disorder's (PTSD) factor structure. Data were analyzed from a clinical sample of 405 Canadian veterans evaluated for PTSD. Results were consistent with our hypotheses. Each PTSD factor model was best…
Structural Variability of Tropospheric Growth Factors Transforming Mid-latitude Cyclones to Severe Storms over the North Atlantic

NASA Astrophysics Data System (ADS)

Wild, Simon; Befort, Daniel J.; Leckebusch, Gregor C.

2015-04-01

The development of European surface wind storms out of normal mid-latitude cyclones is substantially influenced by upstream tropospheric growth factors over the Northern Atlantic. The main factors include divergence and vorticity advection in the upper troposphere, latent heat release and the presence of instabilities of short baroclinic waves of suitable wave lengths. In this study we examine a subset of these potential growth factors and their related influences on the transformation of extra-tropical cyclones into severe damage prone surface storm systems. Previous studies have shown links between specific growth factors and surface wind storms related to extreme cyclones. In our study we investigate in further detail spatial and temporal variability patterns of these upstream processes at different vertical levels of the troposphere. The analyses will comprise of the three growth factors baroclinicity, latent heat release and upper tropospheric divergence. Our definition of surface wind storms is based on the Storm Severity Index (SSI) alongside a wind tracking algorithm identifying areas of exceedances of the local 98th percentile of the 10m wind speed. We also make use of a well-established extra-tropical cyclone identification and tracking algorithm. These cyclone tracks form the base for a composite analysis of the aforementioned growth factors using ERA-Interim Reanalysis from 1979 - 2014 for the extended winter season (ONDJFM). Our composite analysis corroborates previous similar studies but extends them by using an impact based algorithm for the identification of strong wind systems. Based on this composite analysis we further identify variability patterns for each growth factor most important for the transformation of a cyclone into a surface wind storm. We thus also address the question whether the link between storm intensity and related growth factor anomaly taking into account its spatial variability is stable and can be quantified. While the robustness of our preliminary results is generally dependent on the growth factor investigated, some examples include i) the overall availability of latent heat seems to be less important than its spatial structure around the cyclone core and ii) the variability of upper-tropospheric baroclinicity appears to be highest north of the surface position of the cyclone, especially for those that transform into a surface storm.
Differentiation of functional constipation and constipation predominant irritable bowel syndrome based on Rome III criteria: a population-based study.

PubMed

Koloski, N A; Jones, M; Young, M; Talley, N J

2015-05-01

While the Rome III classification recognises functional constipation (FC) and constipation predominant IBS (IBS-C) as distinct disorders, recent evidence has suggested that these disorders are difficult to separate in clinical practice. To identify whether clinical and lifestyle factors differentiate Rome III-defined IBS-C from FC based on gastrointestinal symptoms and lifestyle characteristics. 3260 people randomly selected from the Australian population returned a postal survey. FC and IBS-C were defined according to Rome III. The first model used logistic regression to differentiate IBS-C from FC based on lifestyle, quality-of-life and psychological characteristics. The second approach was data-driven employing latent class analysis (LCA) to identify naturally occurring clusters in the data considering all symptoms involved in the Rome III criteria for IBS-C and FC. We found n = 206 (6.5%; 95% CI 5.7-7.4%) people met strict Rome III FC whereas n = 109 (3.5%; 95% CI 2.8-4.1%) met strict Rome III IBS-C. The case-control approach indicated that FC patients reported an older age at onset of constipation, were less likely to exercise, had higher mental QoL and less health care seeking than IBS-C. LCA yielded one latent class that was predominantly (75%) FC, while the other class was approximately half IBS-C and half FC. The FC-dominated latent class had clearly lower levels of symptoms used to classify IBS (pain-related symptoms) and was more likely to be male (P = 0.046) but was otherwise similar in distribution of lifestyle factors to the mixed class. The latent class analysis approach suggests a differentiation based more on symptom severity rather than the Rome III view. © 2015 John Wiley & Sons Ltd.
How do verbal short-term memory and working memory relate to the acquisition of vocabulary and grammar? A comparison between first and second language learners.

PubMed

Verhagen, Josje; Leseman, Paul

2016-01-01

Previous studies show that verbal short-term memory (VSTM) is related to vocabulary learning, whereas verbal working memory (VWM) is related to grammar learning in children learning a second language (L2) in the classroom. In this study, we investigated whether the same relationships apply to children learning an L2 in a naturalistic setting and to monolingual children. We also investigated whether relationships with verbal memory differ depending on the type of grammar skill investigated (i.e., morphology vs. syntax). Participants were 63 Turkish children who learned Dutch as an L2 and 45 Dutch monolingual children (mean age = 5 years). Children completed a series of VSTM and VWM tasks, a Dutch vocabulary task, and a Dutch grammar task. A confirmatory factor analysis showed that VSTM and VWM represented two separate latent factors in both groups. Structural equation modeling showed that VSTM, treated as a latent factor, significantly predicted vocabulary and grammar. VWM, treated as a latent factor, predicted only grammar. Both memory factors were significantly related to the acquisition of morphology and syntax. There were no differences between the two groups. These results show that (a) VSTM and VWM are differentially associated with language learning and (b) the same memory mechanisms are employed for learning vocabulary and grammar in L1 children and in L2 children who learn their L2 naturalistically. Copyright © 2015 Elsevier Inc. All rights reserved.
Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

PubMed Central

Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

2017-01-01

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780
Psychosocial factors of caregiver burden in child caregivers: results from the new national study of caregiving.

PubMed

Cohen, Steven A; Cook, Sarah; Kelley, Lauren; Sando, Trisha; Bell, Allison E

2015-08-07

Over 50 million informal caregivers in the United States provide care to an aging adult, saving the economy hundreds of billions of dollars annually from costly hospitalization or institutionalization. Despite the benefits associated with caregiving, caregiver stress can lead to negative physical and mental health consequences, or "caregiver burden". Given these potential negative consequences of caregiver burden, it is important not only to understand the multidimensional components of burden but to also understand the experience from the perspective of the caregiver themselves. Therefore, the objectives of our study are to use exploratory factor analysis to obtain a set of latent factors among a subset of caregiver burden questions identified in previous studies and assess their reliability. All data was obtained from the 2011 National Study of Caregiving (NSOC). Exploratory factor analysis (EFA) was performed to identify a set of latent factors assessing four domains of caregiver burden in "child caregivers": those informal caregivers who provide care to a parent or stepparent. Sensitivity analysis was also conducted by repeating the EFA on demographic subsets of caregivers. After multiple factor analyses, four consistent caregiver burden factors emerged from the 23 questions analyzed: Negative emotional, positive emotional, social, and financial. Reliability of each factor varied, and was strongest for the positive emotional domain for caregiver burden. These domains were generally consistent across demographic subsets of informal caregivers. These results provide researchers a more comprehensive understanding of caregiver burden to target interventions to protect caregiver health and maintain this vital component of the US health care system.
Reactivation of Latent HIV-1 Expression by Engineered TALE Transcription Factors

PubMed Central

Perdigão, Pedro; Gaj, Thomas; Santa-Marta, Mariana; Goncalves, Joao

2016-01-01

The presence of replication-competent HIV-1 –which resides mainly in resting CD4+ T cells–is a major hurdle to its eradication. While pharmacological approaches have been useful for inducing the expression of this latent population of virus, they have been unable to purge HIV-1 from all its reservoirs. Additionally, many of these strategies have been associated with adverse effects, underscoring the need for alternative approaches capable of reactivating viral expression. Here we show that engineered transcriptional modulators based on customizable transcription activator-like effector (TALE) proteins can induce gene expression from the HIV-1 long terminal repeat promoter, and that combinations of TALE transcription factors can synergistically reactivate latent viral expression in cell line models of HIV-1 latency. We further show that complementing TALE transcription factors with Vorinostat, a histone deacetylase inhibitor, enhances HIV-1 expression in latency models. Collectively, these findings demonstrate that TALE transcription factors are a potentially effective alternative to current pharmacological routes for reactivating latent virus and that combining synthetic transcriptional activators with histone deacetylase inhibitors could lead to the development of improved therapies for latent HIV-1 infection. PMID:26933881
General distress is more important than PTSD's cognition and mood alterations factor in accounting for PTSD and depression's comorbidity.

PubMed

Byllesby, Brianna M; Elhai, Jon D; Tamburrino, Marijo; Fine, Thomas H; Cohen, Gregory; Sampson, Laura; Shirley, Edwin; Chan, Philip K; Liberzon, Israel; Galea, Sandro; Calabrese, Joseph R

2017-03-15

Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are highly comorbid and exhibit strong correlations with each other at both the symptom level and latent factor level. Various theories have attempted to explain this relationship. Results have been inconsistent regarding whether PTSD's negative alterations in cognition and mood factor (NACM) is significantly more related to depression, in contrast to other factors of PTSD. Confirmatory factor analysis was used to attempt to address the relationships between PTSD and MDD in a large sample of trauma-exposed combat veterans from the Ohio National Guard as part of a larger longitudinal study. Confirmatory factor analysis was used to test a bifactor model of PTSD symptoms, testing relations between PTSD's factors and a latent depressive factor. After partitioning out the common variance into the bifactor, we found that in contrast to other PTSD factors, PTSD's NACM factor was not significantly more related to depression. Instead, only the general bifactor predicted depressive symptoms. The limitations of the present study include the following: the specific measures of PTSD and MDD used were based on self-report, and the sample consisted of non-clinical, non-treatment seeking veterans. The present study suggests that the high rate of comorbidity between posttraumatic stress disorder (PTSD) and major depressive disorder is more related to underlying general distress or negative affectivity than the symptom categories of the PTSD diagnostic criteria. Copyright © 2017 Elsevier B.V. All rights reserved.
Exploring the Factor Structure of Neurocognitive Measures in Older Individuals

PubMed Central

Santos, Nadine Correia; Costa, Patrício Soares; Amorim, Liliana; Moreira, Pedro Silva; Cunha, Pedro; Cotter, Jorge; Sousa, Nuno

2015-01-01

Here we focus on factor analysis from a best practices point of view, by investigating the factor structure of neuropsychological tests and using the results obtained to illustrate on choosing a reasonable solution. The sample (n=1051 individuals) was randomly divided into two groups: one for exploratory factor analysis (EFA) and principal component analysis (PCA), to investigate the number of factors underlying the neurocognitive variables; the second to test the “best fit” model via confirmatory factor analysis (CFA). For the exploratory step, three extraction (maximum likelihood, principal axis factoring and principal components) and two rotation (orthogonal and oblique) methods were used. The analysis methodology allowed exploring how different cognitive/psychological tests correlated/discriminated between dimensions, indicating that to capture latent structures in similar sample sizes and measures, with approximately normal data distribution, reflective models with oblimin rotation might prove the most adequate. PMID:25880732
Validation of Diagnostic Measures Based on Latent Class Analysis: A Step Forward in Response Bias Research

ERIC Educational Resources Information Center

Thomas, Michael L.; Lanyon, Richard I.; Millsap, Roger E.

2009-01-01

The use of criterion group validation is hindered by the difficulty of classifying individuals on latent constructs. Latent class analysis (LCA) is a method that can be used for determining the validity of scales meant to assess latent constructs without such a priori classifications. The authors used this method to examine the ability of the L…

Substance Use, Violence, and Antiretroviral Adherence: A Latent Class Analysis of Women Living with HIV in Canada.

PubMed

Carter, Allison; Roth, Eric Abella; Ding, Erin; Milloy, M-J; Kestler, Mary; Jabbari, Shahab; Webster, Kath; de Pokomandy, Alexandra; Loutfy, Mona; Kaida, Angela

2018-03-01

We used latent class analysis to identify substance use patterns for 1363 women living with HIV in Canada and assessed associations with socio-economic marginalization, violence, and sub-optimal adherence to combination antiretroviral therapy (cART). A six-class model was identified consisting of: abstainers (26.3%), Tobacco Users (8.81%), Alcohol Users (31.9%), 'Socially Acceptable' Poly-substance Users (13.9%), Illicit Poly-substance Users (9.81%) and Illicit Poly-substance Users of All Types (9.27%). Multinomial logistic regression showed that women experiencing recent violence had significantly higher odds of membership in all substance use latent classes, relative to Abstainers, while those reporting sub-optimal cART adherence had higher odds of being members of the poly-substance use classes only. Factors significantly associated with Illicit Poly-substance Users of All Types were sexual minority status, lower income, and lower resiliency. Findings underline a need for increased social and structural supports for women who use substances to support them in leading safe and healthy lives with HIV.
Global Processing Speed in Children with Low Reading Ability and in Children and Adults with Typical Reading Ability: Exploratory Factor Analytic Models

ERIC Educational Resources Information Center

Peter, Beate; Matsushita, Mark; Raskind, Wendy H.

2011-01-01

Purpose: To investigate processing speed as a latent dimension in children with dyslexia and children and adults with typical reading skills. Method: Exploratory factor analysis (FA) was based on a sample of multigenerational families, each ascertained through a child with dyslexia. Eleven measures--6 of them timed--represented verbal and…
Gender Differences in the Influence of Early Perceived Parental Support on Student Mathematics and Science Achievement and STEM Career Attainment

ERIC Educational Resources Information Center

Ing, Marsha

2014-01-01

The lack of females entering STEM careers is well documented. Reasons for the gender gaps at all stages of the educational pipeline include both internal factors such as self-concept and external factors such as the influence of parents, media, and educators. Using latent growth curve analysis and nationally representative longitudinal survey…
Bifactor latent structure of attention-deficit/hyperactivity disorder (ADHD)/oppositional defiant disorder (ODD) symptoms and first-order latent structure of sluggish cognitive tempo symptoms.

PubMed

Lee, SoYean; Burns, G Leonard; Beauchaine, Theodore P; Becker, Stephen P

2016-08-01

The objective was to determine if the latent structure of attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms is best explained by a general disruptive behavior factor along with specific inattention (IN), hyperactivity/impulsivity (HI), and ODD factors (a bifactor model) whereas the latent structure of sluggish cognitive tempo (SCT) symptoms is best explained by a first-order factor independent of the bifactor model of ADHD/ODD. Parents' (n = 703) and teachers' (n = 366) ratings of SCT, ADHD-IN, ADHD-HI, and ODD symptoms on the Child and Adolescent Disruptive Behavior Inventory (CADBI) in a community sample of children (ages 5-13; 55% girls) were used to evaluate 4 models of symptom organization. Results indicated that a bifactor model of ADHD/ODD symptoms, in conjunction with a separate first-order SCT factor, was the best model for both parent and teacher ratings. The first-order SCT factor showed discriminant validity with the general disruptive behavior and specific IN factors in the bifactor model. In addition, higher scores on the SCT factor predicted greater academic and social impairment, even after controlling for the general disruptive behavior and 3 specific factors. Consistent with predictions from the trait-impulsivity etiological model of externalizing liability, a single, general disruptive behavior factor accounted for nearly all common variance in ADHD/ODD symptoms, whereas SCT symptoms represented a factor different from the general disruptive behavior and specific IN factor. These results provide additional support for distinguishing between SCT and ADHD-IN. The study also demonstrates how etiological models can be used to predict specific latent structures of symptom organization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
On the validity and generality of transfer effects in cognitive training research.

PubMed

Noack, Hannes; Lövdén, Martin; Schmiedek, Florian

2014-11-01

Evaluation of training effectiveness is a long-standing problem of cognitive intervention research. The interpretation of transfer effects needs to meet two criteria, generality and specificity. We introduce each of the two, and suggest ways of implementing them. First, the scope of the construct of interest (e.g., working memory) defines the expected generality of transfer effects. Given that the constructs of interest are typically defined at the latent level, data analysis should also be conducted at the latent level. Second, transfer should be restricted to measures that are theoretically related to the trained construct. Hence, the construct of interest also determines the specificity of expected training effects; to test for specificity, study designs should aim at convergent and discriminant validity. We evaluate the recent cognitive training literature in relation to both criteria. We conclude that most studies do not use latent factors for transfer assessment, and do not test for convergent and discriminant validity.
Evidence of the dissociative PTSD subtype: A systematic literature review of latent class and profile analytic studies of PTSD.

PubMed

Hansen, Maj; Ross, Jana; Armour, Cherie

2017-04-15

The dissociative PTSD (D-PTSD) subtype was first introduced into the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) in 2013. Prior to this, studies using latent profile analysis (LPA) or latent class analysis (LCA), began to provide support for the D-PTSD construct and associated risk factors. This research is important, because dissociative symptoms in the context of PTSD may potentially interfere with treatment course or outcome. The aims of the present study were twofold: to systematically review the LCA and LPA studies investigating support for the D-PTSD construct; and to review the associated research on the risk factors or covariates of D-PTSD in the identified studies. Six databases (PubMed, Web of Science, Scopus, PILOTS, PsychInfo, and Embase) were systematically searched for relevant papers. Eleven studies were included in the present review. The majority of the studies were supportive of the D-PTSD subtype; primarily characterized by depersonalization and derealization. Several covariates of the D-PTSD subtype have been investigated with mixed results. Many limitations relate to the state of the current literature, including a small number of studies, the use of self-report measurements of PTSD, and heterogeneity across the samples in investigated covariates. The results were overall supportive of the D-PTSD construct. Future research on D-PTSD and associated risk factors is needed to shed light on the possibilities of facilitating preventive actions, screening, and implications on treatment effects. Copyright © 2017 Elsevier B.V. All rights reserved.
The classification of body dysmorphic disorder symptoms in male and female adolescents.

PubMed

Schneider, Sophie C; Baillie, Andrew J; Mond, Jonathan; Turner, Cynthia M; Hudson, Jennifer L

2018-01-01

Body dysmorphic disorder (BDD) was categorised in DSM-5 within the newly created 'obsessive-compulsive and related disorders' chapter, however this classification remains subject to debate. Confirmatory factor analysis was used to test competing models of the co-occurrence of symptoms of BDD, obsessive-compulsive disorder, unipolar depression, anxiety, and eating disorders in a community sample of adolescents, and to explore potential sex differences in these models. Self-report questionnaires assessing disorder symptoms were completed by 3149 Australian adolescents. The fit of correlated factor models was calculated separately in males and females, and measurement invariance testing compared parameters of the best-fitting model between males and females. All theoretical models of the classification of BDD had poor fit to the data. Good fit was found for a novel model where BDD symptoms formed a distinct latent factor, correlated with affective disorder and eating disorder latent factors. Metric non-invariance was found between males and females, and the majority of factor loadings differed between males and females. Correlations between some latent factors also differed by sex. Only cross-sectional data were collected, and the study did not assess a broad range of DSM-5 defined eating disorder symptoms or other disorders in the DSM-5 obsessive-compulsive and related disorders chapter. This study is the first to statistically evaluate competing models of BDD classification. The findings highlight the unique features of BDD and its associations with affective and eating disorders. Future studies examining the classification of BDD should consider developmental and sex differences in their models. Copyright © 2017. Published by Elsevier B.V.
TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS

PubMed Central

Johndrow, James E.; Bhattacharya, Anirban; Dunson, David B.

2017-01-01

Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. We derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions. PMID:29332971
A Latent Class Analysis of Online Sexual Experiences and Offline Sexual Behaviors Among Female Adolescents.

PubMed

Maas, Megan K; Bray, Bethany C; Noll, Jennie G

2017-11-20

This study used latent class analysis to identify patterns (i.e., classes) across a broad range of online sexual experiences among female adolescents (n = 312) and to explore offline sexual behavior and substance use correlates of as well as maltreatment differences in class membership. The following four classes were identified: Online Abstinent, Online Inclusive, Attractors, and Seekers. Maltreated female adolescents were more likely to be members of the Online Inclusive class and less likely to be members of the Online Abstinent class than nonmaltreated female adolescents. Offline sexual behaviors and substance use differentially predicted class membership. These results suggest online sexual experiences vary greatly and should not be aggregated together as a global risk factor for all female adolescents. © 2017 Society for Research on Adolescence.
The latent structure of alcohol misuse in young adults: Do taxometric results differ as a function of prior criminal history?

PubMed

Walters, Glenn D

2015-12-01

The 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. Data 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). Analyses 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. On 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. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Taxometric and Factor Analytic Models of Anxiety Sensitivity among Youth: Exploring the Latent Structure of Anxiety Psychopathology Vulnerability

ERIC Educational Resources Information Center

Bernstein, Amit; Zvolensky, Michael J.; Stewart, Sherry; Comeau, Nancy

2007-01-01

This study represents an effort to better understand the latent structure of anxiety sensitivity (AS), a well-established affect-sensitivity individual difference factor, among youth by employing taxometric and factor analytic approaches in an integrative manner. Taxometric analyses indicated that AS, as indexed by the Child Anxiety Sensitivity…
Korean immigrants' knowledge of heart attack symptoms and risk factors.

PubMed

Hwang, Seon Y; Ryan, Catherine J; Zerwic, Julie Johnson

2008-02-01

This study assessed the knowledge of heart attack symptoms and risk factors in a convenience sample of Korean immigrants. A total of 116 Korean immigrants in a Midwestern metropolitan area were recruited through Korean churches and markets. Knowledge was assessed using both open-ended questions and a structured questionnaire. Latent class cluster analysis and Chi-square tests were used to analyze the data. About 76% of the sample had at least one self-reported risk factor for cardiovascular disease. Using an open-ended question, the majority of subjects could only identify one symptom. In the structured questionnaire, subjects identified a mean of 5 out of 10 heart attack symptoms and a mean of 5 out of 9 heart attack risk factors. Latent class cluster analysis showed that subjects clustered into two groups for both risk factors and symptoms: a high knowledge group and a low knowledge group. Subjects who clustered into the risk factor low knowledge group (48%) were more likely than the risk factor high knowledge group to be older than 65 years, to have lower education, to not know to use 911 when a heart attack occurred, and to not have a family history of heart attack. Korean immigrants' knowledge of heart attack symptoms and risk factors was variable, ranging from high to very low. Education should be focused on those at highest risk for a heart attack, which includes the elderly and those with risk factors.
Refining the Measurement of Distress Intolerance

PubMed Central

McHugh, R. Kathryn; Otto, Michael W.

2012-01-01

Distress intolerance is an important transdiagnostic variable that has long been implicated in the development and maintenance of psychological disorders. Self-report measurement strategies for distress intolerance have emerged from several different models of psychopathology and these measures have been applied inconsistently in the literature in the absence of a clear gold standard. The absence of a consistent assessment strategy has limited the ability to compare across studies and samples, thus hampering the advancement of this research agenda. This study evaluated the latent factor structure of existing measures of DI to examine the degree to which they are capturing the same construct. Results of confirmatory factor analysis in 3 samples totaling 400 participants provided support for a single factor latent structure. Individual items of these four scales were then correlated with this factor to identify those that best capture the core construct. Results provided consistent supported for 10 items that demonstrated the strongest concordance with this factor. The use of these 10 items as a unifying measure in the study of DI and future directions for the evaluation of its utility are discussed. PMID:22697451
Data on the interexaminer variation of minutia markup on latent fingerprints.

PubMed

Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn

2016-09-01

The data in this article supports the research paper entitled "Interexaminer variation of minutia markup on latent fingerprints" [1]. The data in this article describes the variability in minutia markup during both analysis of the latents and comparison between latents and exemplars. The data was collected in the "White Box Latent Print Examiner Study," in which each of 170 volunteer latent print examiners provided detailed markup documenting their examinations of latent-exemplar pairs of prints randomly assigned from a pool of 320 pairs. Each examiner examined 22 latent-exemplar pairs; an average of 12 examiners marked each latent.
Prevalence Estimation and Validation of New Instruments in Psychiatric Research: An Application of Latent Class Analysis and Sensitivity Analysis

ERIC Educational Resources Information Center

Pence, Brian Wells; Miller, William C.; Gaynes, Bradley N.

2009-01-01

Prevalence and validation studies rely on imperfect reference standard (RS) diagnostic instruments that can bias prevalence and test characteristic estimates. The authors illustrate 2 methods to account for RS misclassification. Latent class analysis (LCA) combines information from multiple imperfect measures of an unmeasurable latent condition to…
Trajectories of Multidimensional Caregiver Burden in Chinese Informal Caregivers for Dementia: Evidence from Exploratory and Confirmatory Factor Analysis of the Zarit Burden Interview.

PubMed

Li, Dan; Hu, Nan; Yu, Yueyi; Zhou, Aihong; Li, Fangyu; Jia, Jianping

2017-01-01

Despite its popularity, the latent structure of 22-item Zarit Burden Interview (ZBI) remains unclear. There has been no study exploring how caregiver multidimensional burden changed. The aim of the work was to validate the latent structure of ZBI and to investigate how multidimensional burden evolves with increasing global burden. We studied 1,132 dyads of dementia patients and their informal caregivers. The caregivers completed the ZBI and a questionnaire regarding caregiving. The total sample was randomly split into two equal subsamples. Exploratory factor analysis (EFA) was performed in the first subsample. In the second subsample, confirmatory factor analysis (CFA) was conducted to validate models generated from EFA. The mean of weighted factor score was calculated to assess the change of dimension burden against the increasing ZBI total score. The result of EFA and CFA supported that a five-factor structure, including role strain, personal strain, incompetency, dependency, and guilt, had the best goodness-of-fit. The trajectories of multidimensional burden suggested that three different dimensions (guilt, role strain and personal strain) became the main subtype of burden in sequence as the ZBI total score increased from mild to moderate. Factor dependency contributed prominently to the total burden in severe stage. The five-factor ZBI is a psychometrically robust measure for assessing multidimensional burden in Chinese caregivers. The changes of multidimensional burden have deepened our understanding of the psychological characteristics of caregiving beyond a single total score and may be useful for developing interventions to reduce caregiver burden.
Life-Course Body Mass Index Trajectories Are Predicted by Childhood Socioeconomic Status but Not Exposure to Improved Nutrition during the First 1000 Days after Conception in Guatemalan Adults.

PubMed

Ford, Nicole D; Martorell, Reynaldo; Mehta, Neil K; Ramirez-Zea, Manuel; Stein, Aryeh D

2016-11-01

Latin America has experienced increases in obesity. Little is known about the role of early life factors on body mass index (BMI) gain over the life course. The objective of this research was to examine the role of early life factors [specifically, nutrition supplementation during the first 1000 d (from conception to 2 y of age) and childhood household socioeconomic status (SES)] on the pattern of BMI gain from birth or early childhood through midadulthood by using latent class growth analysis. Study participants (711 women, 742 men) who were born in 4 villages in Guatemala (1962-1977) were followed prospectively since participating in a randomized nutrition supplementation trial as children. Sex-specific BMI latent class trajectories were derived from 22 possible measures of height and weight from 1969 to 2004. To characterize early life determinants of BMI latent class membership, we used logistic regression modeling and estimated the difference-in-difference (DD) effect of nutrition supplementation during the first 1000 d. We identified 2 BMI latent classes in women [low (57%) and high (43%)] and 3 classes in men [low (38%), medium (47%), and high (15%)]. Nutrition supplementation during the first 1000 d after conception was not associated with BMI latent class membership (DD test: P > 0.15 for men and women), whereas higher SES was associated with increased odds of high BMI latent class membership in both men (OR: 1.98; 95% CI: 1.09, 3.61) and women (OR: 1.62; 95% CI: 1.07, 2.45) for the highest relative to the lowest tertile. In a cohort of Guatemalan men and women, nutrition supplementation provided during the first 1000 d was not significantly associated with higher BMI trajectory. Higher childhood household SES was associated with increased odds of high BMI latent class membership relative to the poorest households. The pathways through which this operates still need to be explored. © 2016 American Society for Nutrition.
The Impact of Noninvariant Intercepts in Latent Means Models

ERIC Educational Resources Information Center

Whittaker, Tiffany A.

2013-01-01

Latent means methods such as multiple-indicator multiple-cause (MIMIC) and structured means modeling (SMM) allow researchers to determine whether or not a significant difference exists between groups' factor means. Strong invariance is typically recommended when interpreting latent mean differences. The extent of the impact of noninvariant…
Resveratrol Reactivates Latent HIV through Increasing Histone Acetylation and Activating Heat Shock Factor 1.

PubMed

Zeng, Xiaoyun; Pan, Xiaoyan; Xu, Xinfeng; Lin, Jian; Que, Fuchang; Tian, Yuanxin; Li, Lin; Liu, Shuwen

2017-06-07

The persistence of latent HIV reservoirs presents a significant challenge to viral eradication. Effective latency reversing agents (LRAs) based on "shock and kill" strategy are urgently needed. The natural phytoalexin resveratrol has been demonstrated to enhance HIV gene expression, although its mechanism remains unclear. In this study, we demonstrated that resveratrol was able to reactivate latent HIV without global T cell activation in vitro. Mode of action studies showed resveratrol-mediated reactivation from latency did not involve the activation of silent mating type information regulation 2 homologue 1 (SIRT1), which belonged to class-3 histone deacetylase (HDAC). However, latent HIV was reactivated by resveratrol mediated through increasing histone acetylation and activation of heat shock factor 1 (HSF1). Additionally, synergistic activation of the latent HIV reservoirs was observed under cotreatment with resveratrol and conventional LRAs. Collectively, this research reveals that resveratrol is a natural LRA and shows promise for HIV therapy.
The Nature of Coping in Treatment for Marijuana Dependence: Latent Structure and Validation of the Coping Strategies Scale

PubMed Central

Litt, Mark D.; Kadden, Ronald M; Tennen, Howard

2012-01-01

The Coping Strategies Scale (CSS) was designed to assess adaptive changes in substance-use specific coping that result from treatment. The present study sought to examine the latent structure of the CSS in the hope that it might shed light on the coping processes of drug users, and guide the development of a brief version of the CSS. Respondents on the CSS were 751 men and women treated in three clinical trials for marijuana dependence. Posttreatment CSS data were analyzed to determine the nature of coping responses in patients who have been trained to use specific strategies to deal with substance use disorders. Exploratory factor analysis yielded two factors, categorized as problem-focused and emotion-focused coping, but confirmatory factor analysis did not support this structure. When infrequently endorsed items were removed, however, confirmatory factor analysis revealed a good fit to the data. Contrary to expectations, practical strategies that often form the basis for coping skills training, such as avoiding those who smoke, were not frequently endorsed. Problem focused items reflected cognitive commitments to change. Emotion-focused items included cognitive reinterpretations of emotions, to help manage emotional reactions. Brief versions of the CSS based on these factors showed good convergent and discriminant validity. The CSS, and the brief versions of the CSS, may prove useful in future treatment trials to evaluate effects of treatment on coping skills acquisition and utilization in substance dependent individuals. PMID:22082345

Understanding Human Error in Naval Aviation Mishaps.

PubMed

Miranda, Andrew T

2018-04-01

To better understand the external factors that influence the performance and decisions of aviators involved in Naval aviation mishaps. Mishaps in complex activities, ranging from aviation to nuclear power operations, are often the result of interactions between multiple components within an organization. The Naval aviation mishap database contains relevant information, both in quantitative statistics and qualitative reports, that permits analysis of such interactions to identify how the working atmosphere influences aviator performance and judgment. Results from 95 severe Naval aviation mishaps that occurred from 2011 through 2016 were analyzed using Bayes' theorem probability formula. Then a content analysis was performed on a subset of relevant mishap reports. Out of the 14 latent factors analyzed, the Bayes' application identified 6 that impacted specific aspects of aviator behavior during mishaps. Technological environment, misperceptions, and mental awareness impacted basic aviation skills. The remaining 3 factors were used to inform a content analysis of the contextual information within mishap reports. Teamwork failures were the result of plan continuation aggravated by diffused responsibility. Resource limitations and risk management deficiencies impacted judgments made by squadron commanders. The application of Bayes' theorem to historical mishap data revealed the role of latent factors within Naval aviation mishaps. Teamwork failures were seen to be considerably damaging to both aviator skill and judgment. Both the methods and findings have direct application for organizations interested in understanding the relationships between external factors and human error. It presents real-world evidence to promote effective safety decisions.
Analysis of the impact path on factors of China's energy-related CO2 emissions: a path analysis with latent variables.

PubMed

Chen, Wenhui; Lei, Yalin

2017-02-01

Identifying the impact path on factors of CO 2 emissions is crucial for the government to take effective measures to reduce carbon emissions. The most existing research focuses on the total influence of factors on CO 2 emissions without differentiating between the direct and indirect influence. Moreover, scholars have addressed the relationships among energy consumption, economic growth, and CO 2 emissions rather than estimating all the causal relationships simultaneously. To fill this research gaps and explore overall driving factors' influence mechanism on CO 2 emissions, this paper utilizes a path analysis model with latent variables (PA-LV) to estimate the direct and indirect effect of factors on China's energy-related carbon emissions and to investigate the causal relationships among variables. Three key findings emanate from the analysis: (1) The change in the economic growth pattern inhibits the growth rate of CO 2 emissions by reducing the energy intensity; (2) adjustment of industrial structure contributes to energy conservation and CO 2 emission reduction by raising the proportion of the tertiary industry; and (3) the growth of CO 2 emissions impacts energy consumption and energy intensity negatively, which results in a negative impact indirectly on itself. To further control CO 2 emissions, the Chinese government should (1) adjust the industrial structure and actively develop its tertiary industry to improve energy efficiency and develop low-carbon economy, (2) optimize population shifts to avoid excessive population growth and reduce energy consumption, and (3) promote urbanization steadily to avoid high energy consumption and low energy efficiency.
Men's and Women's Pathways to Adulthood and Their Adolescent Precursors

ERIC Educational Resources Information Center

Oesterle, Sabrina; Hawkins, J. David; Hill, Karl G.; Bailey, Jennifer A.

2010-01-01

This study compared men's and women's pathways to adulthood by examining how role transitions in education, work, marriage, and parenthood intersect and form developmental pathways from ages 18-30. The study investigated how sociodemographic factors and adolescent experiences were associated with these pathways. We used latent class analysis to…
Fitting and Testing Conditional Multinormal Partial Credit Models

ERIC Educational Resources Information Center

Hessen, David J.

2012-01-01

A multinormal partial credit model for factor analysis of polytomously scored items with ordered response categories is derived using an extension of the Dutch Identity (Holland in "Psychometrika" 55:5-18, 1990). In the model, latent variables are assumed to have a multivariate normal distribution conditional on unweighted sums of item…
Student Satisfaction with Online Learning: Is It a Psychological Contract?

ERIC Educational Resources Information Center

Dziuban, Charles; Moskal, Patsy; Thompson, Jessica; Kramer, Lauren; DeCantis, Genevieve; Hermsdorfer, Andrea

2015-01-01

The authors explore the possible relationship between student satisfaction with online learning and the theory of psychological contracts. The study incorporates latent trait models using the image analysis procedure and computation of Anderson and Rubin factors scores with contrasts for students who are satisfied, ambivalent, or dissatisfied with…
Does Teachers' Pedagogical Content Knowledge Affect Their Fluency Instruction?

ERIC Educational Resources Information Center

Van den Hurk, H. T. G.; Houtveen, A. A. M.; Van de Grift, W. J. C. M.

2017-01-01

The relation is studied between teachers' pedagogical content knowledge of reading and the quality of their subsequent classroom behaviour in teaching fluent reading. A confirmatory factor analysis model with two latent variables is tested and shows adequate goodness-of-fit indices. Contrary to our expectations, the results of structural equation…
An EM Algorithm for Maximum Likelihood Estimation of Process Factor Analysis Models

ERIC Educational Resources Information Center

Lee, Taehun

2010-01-01

In this dissertation, an Expectation-Maximization (EM) algorithm is developed and implemented to obtain maximum likelihood estimates of the parameters and the associated standard error estimates characterizing temporal flows for the latent variable time series following stationary vector ARMA processes, as well as the parameters defining the…
Bayesian Data-Model Fit Assessment for Structural Equation Modeling

ERIC Educational Resources Information Center

Levy, Roy

2011-01-01

Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…
The Latent Structure of Child Depression: A Taxometric Analysis

ERIC Educational Resources Information Center

Richey, J. Anthony; Schmidt, Norman B.; Lonigan, Christopher J.; Phillips, Beth M.; Catanzaro, Salvatore J.; Laurent, Jeff; Gerhardstein, Rebecca R.; Kotov, Roman

2009-01-01

Background: The current study examined the categorical versus continuous nature of child and adolescent depression among three samples of children and adolescents ranging from 5 to 19 years. Methods: Depression was measured using the Children's Depression Inventory (CDI). Indicators derived from the CDI were based on factor analytic research on…
Latent structure of the Wisconsin Card Sorting Test: a confirmatory factor analytic study.

PubMed

Greve, Kevin W; Stickle, Timothy R; Love, Jeffrey M; Bianchini, Kevin J; Stanford, Matthew S

2005-05-01

The present study represents the first large scale confirmatory factor analysis of the Wisconsin Card Sorting Test (WCST). The results generally support the three factor solutions reported in the exploratory factor analysis literature. However, only the first factor, which reflects general executive functioning, is statistically sound. The secondary factors, while likely reflecting meaningful cognitive abilities, are less stable except when all subjects complete all 128 cards. It is likely that having two discontinuation rules for the WCST has contributed to the varied factor analytic solutions reported in the literature and early discontinuation may result in some loss of useful information. Continued multivariate research will be necessary to better clarify the processes underlying WCST performance and their relationships to one another.
Latent variable modeling to analyze the effects of process parameters on the dissolution of paracetamol tablet

PubMed Central

Sun, Fei; Xu, Bing; Zhang, Yi; Dai, Shengyun; Shi, Xinyuan; Qiao, Yanjiang

2017-01-01

ABSTRACT The dissolution is one of the critical quality attributes (CQAs) of oral solid dosage forms because it relates to the absorption of drug. In this paper, the influence of raw materials, granules and process parameters on the dissolution of paracetamol tablet was analyzed using latent variable modeling methods. The variability in raw materials and granules was understood based on the principle component analysis (PCA), respectively. A multi-block partial least squares (MBPLS) model was used to determine the critical factors affecting the dissolution. The results showed that the binder amount, the post granulation time, the API content in granule, the fill depth and the punch tip separation distance were the critical factors with variable importance in the projection (VIP) values larger than 1. The importance of each unit of the whole process was also ranked using the block importance in the projection (BIP) index. It was concluded that latent variable models (LVMs) were very useful tools to extract information from the available data and improve the understanding on dissolution behavior of paracetamol tablet. The obtained LVMs were also helpful to propose the process design space and to design control strategies in the further research. PMID:27689242
Why aren’t they happy? An analysis of end-user satisfaction with Electronic health records

PubMed Central

Unni, Prasad; Staes, Catherine; Weeks, Howard; Kramer, Heidi; Borbolla, Damion; Slager, Stacey; Taft, Teresa; Chidambaram, Valliammai; Weir, Charlene

2016-01-01

Introduction. Implementations of electronic health records (EHR) have been met with mixed outcome reviews. Complaints about these systems have led to many attempts to have useful measures of end-user satisfaction. However, most user satisfaction assessments do not focus on high-level reasoning, despite the complaints of many physicians. Our study attempts to identify some of these determinants. Method. We developed a user satisfaction survey instrument, based on pre-identified and important clinical and non-clinical clinician tasks. We surveyed a sample of in-patient physicians and focused on using exploratory factor analyses to identify underlying high-level cognitive tasks. We used the results to create unique, orthogonal variables representative of latent structure predictive of user satisfaction. Results. Our findings identified 3 latent high-level tasks that were associated with end-user satisfaction: a) High- level clinical reasoning b) Communicate/coordinate care and c) Follow the rules/compliance. Conclusion: We were able to successfully identify latent variables associated with satisfaction. Identification of communicability and high-level clinical reasoning as important factors determining user satisfaction can lead to development and design of more usable electronic health records with higher user satisfaction. PMID:28269962
A Second-Order Confirmatory Factor Analysis of the Moral Distress Scale-Revised for Nurses.

PubMed

Sharif Nia, Hamid; Shafipour, Vida; Allen, Kelly-Ann; Heidari, Mohammad Reza; Yazdani-Charati, Jamshid; Zareiyan, Armin

2017-01-01

Moral distress is a growing problem for healthcare professionals that may lead to dissatisfaction, resignation, or occupational burnout if left unattended, and nurses experience different levels of this phenomenon. This study aims to investigate the factor structure of the Persian version of the Moral Distress Scale-Revised in intensive care and general nurses. This methodological research was conducted with 771 nurses from eight hospitals in the Mazandaran Province of Iran in 2017. Participants completed the Moral Distress Scale-Revised, data collected, and factor structure assessed using the construct, convergent, and divergent validity methods. The reliability of the scale was assessed using internal consistency (Cronbach's alpha, Theta, and McDonald's omega coefficients) and construct reliability. Ethical considerations: This study was approved by the Ethics Committee of Mazandaran University of Medical Sciences. The exploratory factor analysis ( N = 380) showed that the Moral Distress Scale-Revised has five factors: lack of professional competence at work, ignoring ethical issues and patient conditions, futile care, carrying out the physician's orders without question and unsafe care, and providing care under personal and organizational pressures, which explained 56.62% of the overall variance. The confirmatory factor analysis ( N = 391) supported the five-factor solution and the second-order latent factor model. The first-order model did not show a favorable convergent and divergent validity. Ultimately, the Moral Distress Scale-Revised was found to have a favorable internal consistency and construct reliability. The Moral Distress Scale-Revised was found to be a multidimensional construct. The data obtained confirmed the hypothesis of the factor structure model with a latent second-order variable. Since the convergent and divergent validity of the scale were not confirmed in this study, further assessment is necessary in future studies.
Temperament factors and dimensional, latent bifactor models of child psychopathology: Transdiagnostic and specific associations in two youth samples.

PubMed

Hankin, Benjamin L; Davis, Elysia Poggi; Snyder, Hannah; Young, Jami F; Glynn, Laura M; Sandman, Curt A

2017-06-01

Common emotional and behavioral symptoms co-occur and are associated with core temperament factors. This study investigated links between temperament and dimensional, latent psychopathology factors, including a general common psychopathology factor (p factor) and specific latent internalizing and externalizing liabilities, as captured by a bifactor model, in two independent samples of youth. Specifically, we tested the hypothesis that temperament factors of negative affectivity (NA), positive affectivity (PA), and effortful control (EC) could serve as both transdiagnostic and specific risks in relation to recent bifactor models of child psychopathology. Sample 1 included 571 youth (average age 13.6, SD =2.37, range 9.3-17.5) with both youth and parent report. Sample 2 included 554 preadolescent children (average age 7.7, SD =1.35, range =5-11 years) with parent report. Structural equation modeling showed that the latent bifactor models fit in both samples. Replicated in both samples, the p factor was associated with lower EC and higher NA (transdiagnostic risks). Several specific risks replicated in both samples after controlling for co-occurring symptoms via the p factor: internalizing was associated with higher NA and lower PA, lower EC related to externalizing problems. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.
The NEO Five-Factor Inventory: Latent Structure and Relationships with Dimensions of Anxiety and Depressive Disorders in a Large Clinical Sample

ERIC Educational Resources Information Center

Rosellini, Anthony J.; Brown, Timothy A.

2011-01-01

The present study evaluated the latent structure of the NEO Five-Factor Inventory (NEO FFI) and relations between the five-factor model (FFM) of personality and dimensions of "DSM-IV" anxiety and depressive disorders (panic disorder, generalized anxiety disorder [GAD], obsessive-compulsive disorder, social phobia [SOC], major depressive disorder…
Development of Physical Activity-Related Parenting Practices Scales for Urban Chinese Parents of Preschoolers: Confirmatory Factor Analysis and Reliability.

PubMed

Suen, Yi-Nam; Cerin, Ester; Barnett, Anthony; Huang, Wendy Y J; Mellecker, Robin R

2017-09-01

Valid instruments of parenting practices related to children's physical activity (PA) are essential to understand how parents affect preschoolers' PA. This study developed and validated a questionnaire of PA-related parenting practices for Chinese-speaking parents of preschoolers in Hong Kong. Parents (n = 394) completed a questionnaire developed using findings from formative qualitative research and literature searches. Test-retest reliability was determined on a subsample (n = 61). Factorial validity was assessed using confirmatory factor analysis. Subscale internal consistency was determined. The scale of parenting practices encouraging PA comprised 2 latent factors: Modeling, structure and participatory engagement in PA (23 items), and Provision of appropriate places for child's PA (4 items). The scale of parenting practices discouraging PA scale encompassed 4 latent factors: Safety concern/overprotection (6 items), Psychological/behavioral control (5 items), Promoting inactivity (4 items), and Promoting screen time (2 items). Test-retest reliabilities were moderate to excellent (0.58 to 0.82), and internal subscale reliabilities were acceptable (0.63 to 0.89). We developed a theory-based questionnaire for assessing PA-related parenting practices among Chinese-speaking parents of Hong Kong preschoolers. While some items were context and culture specific, many were similar to those previously found in other populations, indicating a degree of construct generalizability across cultures.
Factors influencing readiness to deploy in disaster response: findings from a cross-sectional survey of the Department of Veterans Affairs Disaster Emergency Medical Personnel System

PubMed Central

2014-01-01

Background The Disaster Emergency Medical Personnel System (DEMPS) program provides a system of volunteers whereby active or retired Department of Veterans Affairs (VA) personnel can register to be deployed to support other VA facilities or the nation during national emergencies or disasters. Both early and ongoing volunteer training is required to participate. Methods This study aims to identify factors that impact willingness to deploy in the event of an emergency. This analysis was based on responses from 2,385 survey respondents (response rate, 29%). Latent variable path models were developed and tested using the EQS structural equations modeling program. Background demographic variables of education, age, minority ethnicity, and female gender were used as predictors of intervening latent variables of DEMPS Volunteer Experience, Positive Attitude about Training, and Stress. The model had acceptable fit statistics, and all three intermediate latent variables significantly predicted the outcome latent variable Readiness to Deploy. Results DEMPS Volunteer Experience and a Positive Attitude about Training were associated with Readiness to Deploy. Stress was associated with decreased Readiness to Deploy. Female gender was negatively correlated with Readiness to Deploy; however, there was an indirect relationship between female gender and Readiness to Deploy through Positive Attitude about Training. Conclusions These findings suggest that volunteer emergency management response programs such as DEMPS should consider how best to address the factors that may make women less ready to deploy than men in order to ensure adequate gender representation among emergency responders. The findings underscore the importance of training opportunities to ensure that gender-sensitive support is a strong component of emergency response, and may apply to other emergency response programs such as the Medical Reserve Corps and the American Red Cross. PMID:25038628
Factors influencing readiness to deploy in disaster response: findings from a cross-sectional survey of the Department of Veterans Affairs Disaster Emergency Medical Personnel System.

PubMed

Zagelbaum, Nicole K; Heslin, Kevin C; Stein, Judith A; Ruzek, Josef; Smith, Robert E; Nyugen, Tam; Dobalian, Aram

2014-07-19

The Disaster Emergency Medical Personnel System (DEMPS) program provides a system of volunteers whereby active or retired Department of Veterans Affairs (VA) personnel can register to be deployed to support other VA facilities or the nation during national emergencies or disasters. Both early and ongoing volunteer training is required to participate. This study aims to identify factors that impact willingness to deploy in the event of an emergency. This analysis was based on responses from 2,385 survey respondents (response rate, 29%). Latent variable path models were developed and tested using the EQS structural equations modeling program. Background demographic variables of education, age, minority ethnicity, and female gender were used as predictors of intervening latent variables of DEMPS Volunteer Experience, Positive Attitude about Training, and Stress. The model had acceptable fit statistics, and all three intermediate latent variables significantly predicted the outcome latent variable Readiness to Deploy. DEMPS Volunteer Experience and a Positive Attitude about Training were associated with Readiness to Deploy. Stress was associated with decreased Readiness to Deploy. Female gender was negatively correlated with Readiness to Deploy; however, there was an indirect relationship between female gender and Readiness to Deploy through Positive Attitude about Training. These findings suggest that volunteer emergency management response programs such as DEMPS should consider how best to address the factors that may make women less ready to deploy than men in order to ensure adequate gender representation among emergency responders. The findings underscore the importance of training opportunities to ensure that gender-sensitive support is a strong component of emergency response, and may apply to other emergency response programs such as the Medical Reserve Corps and the American Red Cross.
Testing Specific Hypotheses Concerning Latent Group Differences in Multi-group Covariance Structure Analysis with Structured Means.

ERIC Educational Resources Information Center

Dolan, Conor V.; Molenaar, Peter C. M.

1994-01-01

In multigroup covariance structure analysis with structured means, the traditional latent selection model is formulated as a special case of phenotypic selection. Illustrations with real and simulated data demonstrate how one can test specific hypotheses concerning selection on latent variables. (SLD)
Factors influencing the quality of life of haemodialysis patients according to symptom cluster.

PubMed

Shim, Hye Yeung; Cho, Mi-Kyoung

2018-05-01

To identify the characteristics in each symptom cluster and factors influencing the quality of life of haemodialysis patients in Korea according to cluster. Despite developments in renal replacement therapy, haemodialysis still restricts the activities of daily living due to pain and impairs physical functioning induced by the disease and its complications. Descriptive survey. Two hundred and thirty dialysis patients aged >18 years. They completed self-administered questionnaires of Dialysis Symptom Index and Kidney Disease Quality of Life instrument-Short Form 1.3. To determine the optimal number of clusters, the collected data were analysed using polytomous variable latent class analysis in R software (poLCA) to estimate the latent class models and the latent class regression models for polytomous outcome variables. Differences in characteristics, symptoms and QOL according to the symptom cluster of haemodialysis patients were analysed using the independent t test and chi-square test. The factors influencing the QOL according to symptom cluster were identified using hierarchical multiple regression analysis. Physical and emotional symptoms were significantly more severe, and the QOL was significantly worse in Cluster 1 than in Cluster 2. The factors influencing the QOL were spouse, job, insurance type and physical and emotional symptoms in Cluster 1, with these variables having an explanatory power of 60.9%. Physical and emotional symptoms were the only influencing factors in Cluster 2, and they had an explanatory power of 37.4%. Mitigating the symptoms experienced by haemodialysis patients and improving their QOL require educational and therapeutic symptom management interventions that are tailored according to the characteristics and symptoms in each cluster. The findings of this study are expected to lead to practical guidelines for addressing the symptoms experienced by haemodialysis patients, and they provide basic information for developing nursing interventions to manage these symptoms and improve the QOL of these patients. © 2017 John Wiley & Sons Ltd.

Quantitative Ultrasound Using Texture Analysis of Myofascial Pain Syndrome in the Trapezius.

PubMed

Kumbhare, Dinesh A; Ahmed, Sara; Behr, Michael G; Noseworthy, Michael D

2018-01-01

Objective-The objective of this study is to assess the discriminative ability of textural analyses to assist in the differentiation of the myofascial trigger point (MTrP) region from normal regions of skeletal muscle. Also, to measure the ability to reliably differentiate between three clinically relevant groups: healthy asymptomatic, latent MTrPs, and active MTrP. Methods-18 and 19 patients were identified with having active and latent MTrPs in the trapezius muscle, respectively. We included 24 healthy volunteers. Images were obtained by research personnel, who were blinded with respect to the clinical status of the study participant. Histograms provided first-order parameters associated with image grayscale. Haralick, Galloway, and histogram-related features were used in texture analysis. Blob analysis was conducted on the regions of interest (ROIs). Principal component analysis (PCA) was performed followed by multivariate analysis of variance (MANOVA) to determine the statistical significance of the features. Results-92 texture features were analyzed for factorability using Bartlett's test of sphericity, which was significant. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.94. PCA demonstrated rotated eigenvalues of the first eight components (each comprised of multiple texture features) explained 94.92% of the cumulative variance in the ultrasound image characteristics. The 24 features identified by PCA were included in the MANOVA as dependent variables, and the presence of a latent or active MTrP or healthy muscle were independent variables. Conclusion-Texture analysis techniques can discriminate between the three clinically relevant groups.
Comparing the Performance of Improved Classify-Analyze Approaches For Distal Outcomes in Latent Profile Analysis

PubMed Central

Dziak, John J.; Bray, Bethany C.; Zhang, Jieting; Zhang, Minqiang; Lanza, Stephanie T.

2016-01-01

Several approaches are available for estimating the relationship of latent class membership to distal outcomes in latent profile analysis (LPA). A three-step approach is commonly used, but has problems with estimation bias and confidence interval coverage. Proposed improvements include the correction method of Bolck, Croon, and Hagenaars (BCH; 2004), Vermunt’s (2010) maximum likelihood (ML) approach, and the inclusive three-step approach of Bray, Lanza, & Tan (2015). These methods have been studied in the related case of latent class analysis (LCA) with categorical indicators, but not as well studied for LPA with continuous indicators. We investigated the performance of these approaches in LPA with normally distributed indicators, under different conditions of distal outcome distribution, class measurement quality, relative latent class size, and strength of association between latent class and the distal outcome. The modified BCH implemented in Latent GOLD had excellent performance. The maximum likelihood and inclusive approaches were not robust to violations of distributional assumptions. These findings broadly agree with and extend the results presented by Bakk and Vermunt (2016) in the context of LCA with categorical indicators. PMID:28630602
Age-Related Changes in Visual Temporal Order Judgment Performance: Relation to Sensory and Cognitive Capacities

PubMed Central

Busey, Thomas; Craig, James; Clark, Chris; Humes, Larry

2010-01-01

Five measures of temporal order judgments were obtained from 261 participants, including 146 elder, 44 middle aged, and 71 young participants. Strong age group differences were observed in all five measures, although the group differences were reduced when letter discriminability was matched for all participants. Significant relations were found between these measures of temporal processing and several cognitive and sensory assays, and structural equation modeling revealed the degree to which temporal order processing can be viewed as a latent factor that depends in part on contributions from sensory and cognitive capacities. The best-fitting model involved two different latent factors representing temporal order processing at same and different locations, and the sensory and cognitive factors were more successful predicting performance in the different location factor than the same-location factor. Processing speed, even measured using high-contrast symbols on a paper-and-pencil test, was a surprisingly strong predictor of variability in both latent factors. However, low-level sensory measures also made significant contributions to the latent factors. The results demonstrate the degree to which temporal order processing relates to other perceptual and cognitive capacities, and address the question of whether age-related declines in these capacities share a common cause. PMID:20580644
Age-related changes in visual temporal order judgment performance: Relation to sensory and cognitive capacities.

PubMed

Busey, Thomas; Craig, James; Clark, Chris; Humes, Larry

2010-08-06

Five measures of temporal order judgments were obtained from 261 participants, including 146 elder, 44 middle aged, and 71 young participants. Strong age group differences were observed in all five measures, although the group differences were reduced when letter discriminability was matched for all participants. Significant relations were found between these measures of temporal processing and several cognitive and sensory assays, and structural equation modeling revealed the degree to which temporal order processing can be viewed as a latent factor that depends in part on contributions from sensory and cognitive capacities. The best-fitting model involved two different latent factors representing temporal order processing at same and different locations, and the sensory and cognitive factors were more successful predicting performance in the different location factor than the same-location factor. Processing speed, even measured using high-contrast symbols on a paper-and-pencil test, was a surprisingly strong predictor of variability in both latent factors. However, low-level sensory measures also made significant contributions to the latent factors. The results demonstrate the degree to which temporal order processing relates to other perceptual and cognitive capacities, and address the question of whether age-related declines in these capacities share a common cause. Copyright 2010 Elsevier Ltd. All rights reserved.
Personal and Financial Risk Typologies Among Women Who Engage in Sex Work in Mongolia: A Latent Class Analysis.

PubMed

Offringa, Reid; Tsai, Laura Cordisco; Aira, Toivgoo; Riedel, Marion; Witte, Susan S

2017-08-01

Women engaged in sex work bear a disproportionate burden of HIV infection worldwide, particularly in low- to middle-income countries. Stakeholders interested in promoting prevention and treatment programs are challenged to efficiently and effectively target heterogeneous groups of women. This problem is particularly difficult because it is nearly impossible to know how those groups are composed a priori. Although grouping based on individual variables (e.g., age or place of solicitation) can describe a sample of women engaged in sex work, selecting these variables requires a strong intuitive understanding of the population. Furthermore, this approach is difficult to quantify and has the potential to reinforce preconceived notions, rather than generate new information. We aimed to investigate groupings of women engaged in sex work. The data were collected from a sample of 204 women who were referred to an HIV prevention intervention in Ulaanbaatar, Mongolia. Latent class analysis was used to create subgroups of women engaged in sex work, based on personal and financial risk factors. This analysis found three latent classes, representing unique response pattern profiles of personal and financial risk. The current study approached typology research in a novel, more empirical way and provided a description of different subgroups, which may respond differently to HIV risk interventions.
Socioeconomic Differences in the Risk Profiles of Susceptibility and Ever Use of Tobacco Among Indian Urban Youth: A Latent Class Approach

PubMed Central

2014-01-01

Purpose: To empirically determine the socioeconomic differences in risk profiles of susceptibility and ever use of tobacco among adolescents in India and to investigate the association between the risk profiles and the psychosocial factors for tobacco use. Methods: Students in 16 private (higher socioeconomic status [SES]; n = 4,489) and 16 government (lower SES; n = 7,153) schools in two large cities in India were surveyed about their tobacco use and related psychosocial factors in 2004. Latent class analysis was used to identify homogenous, mutually exclusive typologies existing within the data. Results: Overall, 3 and 4 latent classes of susceptibility and ever use of tobacco best described students in higher- and lower- SES schools, respectively. Profiles with various combinations of susceptibility and ever use of tobacco were differentially related to psychosocial factors, with lower- SES students being more vulnerable to increased levels of tobacco use than higher- SES students. Conclusions: Acknowledging the multiple dimensions of tobacco use behaviors and identifying constellations of risk behaviors will enable more accurate understanding of etiological processes and will provide information for refining and targeting preventive interventions. Additionally, identifying the socioeconomic differences in susceptibility and ever use risk profiles and their psychosocial correlates will enable policy makers to address these inequities through improved allocation of resources. PMID:24271966
The risk typology of healthcare access and its association with unmet healthcare needs in Asian Americans.

PubMed

Jang, Yuri; Park, Nan Sook; Yoon, Hyunwoo; Huang, Ya-Ching; Rhee, Min-Kyoung; Chiriboga, David A; Kim, Miyong T

2018-01-01

Using data from the 2015 Asian American Quality of Life Survey (N = 2,609), latent profile analysis was conducted on general (health insurance, usual place for care and income) and immigrant-specific (nativity, length of stay in the U.S., English proficiency and acculturation) risk factors of healthcare access. Latent profile analysis identified a three-cluster model (low-risk, moderate-risk and high-risk groups). Compared with the low-risk group, the odds of having an unmet healthcare need was 1.52 times greater in the moderate-risk group and 2.24 times greater in the high-risk group. Challenging the myth of model minority, the present sample of Asian Americans demonstrates its vulnerability in access to healthcare. Findings also show the heterogeneity in healthcare access risk profiles. © 2017 John Wiley & Sons Ltd.
Application of Local Linear Embedding to Nonlinear Exploratory Latent Structure Analysis

ERIC Educational Resources Information Center

Wang, Haonan; Iyer, Hari

2007-01-01

In this paper we discuss the use of a recent dimension reduction technique called Locally Linear Embedding, introduced by Roweis and Saul, for performing an exploratory latent structure analysis. The coordinate variables from the locally linear embedding describing the manifold on which the data reside serve as the latent variable scores. We…
Introduction to Latent Class Analysis with Applications

ERIC Educational Resources Information Center

Porcu, Mariano; Giambona, Francesca

2017-01-01

Latent class analysis (LCA) is a statistical method used to group individuals (cases, units) into classes (categories) of an unobserved (latent) variable on the basis of the responses made on a set of nominal, ordinal, or continuous observed variables. In this article, we introduce LCA in order to demonstrate its usefulness to early adolescence…
Applications of integrated human error identification techniques on the chemical cylinder change task.

PubMed

Cheng, Ching-Min; Hwang, Sheue-Ling

2015-03-01

This paper outlines the human error identification (HEI) techniques that currently exist to assess latent human errors. Many formal error identification techniques have existed for years, but few have been validated to cover latent human error analysis in different domains. This study considers many possible error modes and influential factors, including external error modes, internal error modes, psychological error mechanisms, and performance shaping factors, and integrates several execution procedures and frameworks of HEI techniques. The case study in this research was the operational process of changing chemical cylinders in a factory. In addition, the integrated HEI method was used to assess the operational processes and the system's reliability. It was concluded that the integrated method is a valuable aid to develop much safer operational processes and can be used to predict human error rates on critical tasks in the plant. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.

PubMed

Buettner, Florian; Natarajan, Kedar N; Casale, F Paolo; Proserpio, Valentina; Scialdone, Antonio; Theis, Fabian J; Teichmann, Sarah A; Marioni, John C; Stegle, Oliver

2015-02-01

Recent technical developments have enabled the transcriptomes of hundreds of cells to be assayed in an unbiased manner, opening up the possibility that new subpopulations of cells can be found. However, the effects of potential confounding factors, such as the cell cycle, on the heterogeneity of gene expression and therefore on the ability to robustly identify subpopulations remain unclear. We present and validate a computational approach that uses latent variable models to account for such hidden factors. We show that our single-cell latent variable model (scLVM) allows the identification of otherwise undetectable subpopulations of cells that correspond to different stages during the differentiation of naive T cells into T helper 2 cells. Our approach can be used not only to identify cellular subpopulations but also to tease apart different sources of gene expression heterogeneity in single-cell transcriptomes.
Patterns of HIV Risks and Related Factors among People Who Inject Drugs in Kermanshah, Iran: A Latent Class Analysis.

PubMed

Sharifi, Hamid; Mirzazadeh, Ali; Noroozi, Alireza; Marshall, Brandon D L; Farhoudian, Ali; Higgs, Peter; Vameghi, Meroe; Mohhamadi Shahboulaghi, Farahnaz; Qorbani, Mostafa; Massah, Omid; Armoon, Bahram; Noroozi, Mehdi

2017-01-01

The objective of this study was to explore patterns of drug use and sexual risk behaviors among people who inject drugs (PWID) in Iran. We surveyed 500 PWID in Kermanshah concerning demographic characteristics, sexual risk behaviors, and drug-related risk behaviors in the month prior to study. We used latent class analysis (LCA) to establish a baseline model of risk proﬁles and to identify the optimal number of latent classes, and we used ordinal regression to identify factors associated with class membership. Three classes of multiple HIV risk were identified. The probability of membership in the high-risk class was 0.33, compared to 0.26 and 0.40 for the low- and moderate-risk classes, respectively. Compared to members in the lowest-risk class (reference group), the highest-risk class members had higher odds of being homeless (OR = 4.5, CI: 1.44-8.22; p = 0.001) in the past 12 months. Members of the high-risk class had lower odds of regularly visiting a needle and syringe exchange program as compared to the lowest-risk class members (AOR = 0.42, CI: 0.2-0.81; p = 0.01). Findings show the sexual and drug-related HIV risk clusters among PWID in Iran, and emphasize the importance of developing targeted prevention and harm reduction programs for all domains of risk behaviors, both sexual and drug use related.
The heterogeneous health latent classes of elderly people and their socio-demographic characteristics in Taiwan.

PubMed

Liu, Li-Fan; Tian, Wei-Hua; Yao, Hui-Ping

2014-01-01

The health care needs of elderly people were influenced by their heterogeneity. This study aimed to identify the health latent classes of elderly people by using latent class analysis to deal with heterogeneity and examine their socio-demographic characteristics. Data came from the 2005 National Health Interview Survey (NHIS) in Taiwan. In total, 2449 elderly individuals with available health indicators were examined in latent class analysis (LCA), and 2217 elderly community-dwellings with complete socio-demographic data were analyzed by multinomial logistic regression. Four health latent classes were identified which included 1066 (43.5%) people in the High Comorbidity (HC), 152 (6.2%) in the Functional Impairment (FI), 252 (10.3%) in the Frail (FR), and 979 (40.0%) in the Relatively Healthy (RH) group. Multinomial logistic regressions revealed socio-demographic characteristics among health classes. The variables associated with an increased likelihood of being in the FR group were age, female, and living with families. They were also correlated to ethnicity and educations. Apart from age and gender, the Functional Impairment group was less likely to be ethnicity of Hakka, more likely to live with others than were the RH group. The HC group tended to be younger, with higher educations, and more likely to live in urban area than the Functional Impairment group. The correlations between health classes and socio-demographic factors were discussed. The health status of elderly people includes a variety of health indicators. A person-centered approach is critical to identify the health heterogeneity of elderly people and manage their care needs by targeting differential aging. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
The Blind Men and the Elephant: Identification of a Latent Maltreatment Construct for Youth in Foster Care

PubMed Central

Gabrielli, Joy; Jackson, Yo; Tunno, Angela M.; Hambrick, Erin P.

2017-01-01

Child maltreatment is a major public health concern due to its impact on developmental trajectories and consequences across mental and physical health outcomes. Operationalization of child maltreatment has been complicated, as research has used simple dichotomous counts to identification of latent class profiles. This study examines a latent measurement model assessed within foster youth inclusive of indicators of maltreatment chronicity and severity across four maltreatment types: physical, sexual, and psychological abuse, and neglect. Participants were 500 foster youth with a mean age of 12.99 years (SD = 2.95 years). Youth completed survey questions through a confidential audio computer-assisted self-interview program. A two-factor model with latent constructs of chronicity and severity of maltreatment revealed excellent fit across fit indices; however, the latent constructs were correlated .972. A one-factor model also demonstrated excellent model fit to the data (χ2 (16, n = 500) =28.087, p =.031, RMSEA (0.012 – 0.062) =.039, TLI =.990, CFI =.994, SRMR =.025) with a nonsignificant chi-square difference test comparing the one- and two-factor models. Invariance tests across age, gender, and placement type also were conducted with recommendations provided. Results suggest a single-factor latent model of maltreatment severity and chronicity can be attained. Thus, the maltreatment experiences reported by foster youth, though varied and complex, were captured in a model that may prove useful in later predictions of outcome behaviors. Appropriate identification of both the chronicity and severity of maltreatment inclusive of the range of maltreatment types remains a high priority for future research. PMID:28254690
Morphological and motor characteristics of Croatian first league female football players.

PubMed

Jelaska, Petra Mandić; Katić, Ratko; Jelaska, Igor

2013-05-01

The aim of this study was to determine the structure of morphological and motor characteristics of Croatian first league female football players and their impact on the estimated quality of the players. According to the goal of the research, a sample consisted of 70 Croatian first league female football players. Participants were measured in 18 tests for assessing morphological characteristics, a set of 12 basic motor abilities tests and a set of 7 tests for assessing football-specific motor abilities. Exploratory factor analysis strategy was applied separately to all measured tests: morphological, basic motor abilities and football specific motor abilities. Factor analysis of morphological tests has shown existence of 3 significant latent dimensions that explain 64% of the total variability. Factors are defined as transverse dimensionality of the skeleton and voluminosity (35%), subcutaneous fat tissue (16%) and longitudinal dimensionality of the skeleton (13%). In the area of basic motor abilities, four factors were extracted. The first factor is responsible for the integration of agility and explosive power of legs, i.e. a factor of movement regulation (agility/lower body explosiveness) (23%), the second one defines muscle tone regulation (15%), the third one defines the frequency of leg movements (12%), while the fourth one is recognized as responsible for the manifestation of basic strength, particularly of basic core strength (19%). Two factors were isolated in the space of football-specific motor abilities: football-specific efficiency (53%) and situational football coordination (27%). Furthermore, by use of factor analysis on extracted latent dimensions (morphological, basic and football specific motor abilities) two higher order factors (explaining 87% of common variability) were extracted. They were named morphological-motor factor (54%) and football-specific motor abilities factor (33%). It is assumed that two extracted higher-order factors fully describe morphological and motor status of first league female football players. Furthermore, the linear regression results in latent space showed that the identified factors are very good predictors of female football players quality (delta = 0.959). In doing so, both specific motor abilities factors and the first factor of basic motor abilities as a factor of general motor efficiency have the greatest impact on player quality, and these factors have been identified as most important predictors of player quality in Croatian women's first league and elite female football players in general. Obtained results provide deep insight into the structure of relations between the morphological, motor and specific motor variables and also indicate the importance of such definition of specific motor abilities. Consequently, results explicitly indicate the necessity of early, continuous, and systematic development of football-specific motor abilities in female football players of high competitive level but also, adjusted, to the younger age categories.
Posttraumatic stress disorder and depressive symptoms: joined or independent sequelae of trauma?

PubMed

Dekel, Sharon; Solomon, Zahava; Horesh, Danny; Ein-Dor, Tsachi

2014-07-01

The nature of co-morbidity between posttraumatic stress disorder (PTSD) and depression has been the subject of much controversy. This study addresses this issue by investigating associations between probable PTSD and depressive symptoms in a prospective, longitudinal sample of combat veterans. Symptoms of PTSD and depression were assessed at 3 points of time (i.e., 1991, 2003, 2008) over a period of 17 years utilizing the PTSD Inventory and the SCL-90 (Derogatis, 1977). Two groups of combat veterans, 275 former prisoners of war (ex-POWs) and 219 matched combatants (controls), were assessed. Data were analyzed using descriptive statistics, latent variable modeling, and confirmatory factor analysis. A series of χ(2) tests revealed that the prevalence proportions of depressive symptoms and probable PTSD were higher among ex-POWs compared to controls at all time points. The prevalence of depressive symptoms was higher than the prevalence of PTSD symptoms in both groups at the each of the times. Latent Trajectories Modeling (LTM) indicated that while ex-POWs' PTSD symptom severity increased over time, the severity of symptoms remained stable among controls. Parallel Process Latent Growth Modeling (PLGM) revealed a positive bi-directional relationship whereby PTSD symptoms mediated the affect of captivity on depressive symptoms and depressive symptoms mediated the affect of captivity on PTSD symptoms over time. Utilizing Confirmatory Factor Analysis (CFA), a single factor model emerged for depressive and PTSD symptoms. The findings suggest that while depression and PTSD seem to be different long-term manifestations of traumatic stress, accounted for in part by the severity of the trauma, they both may be parts of a common general traumatic stress construct. Clinical and theoretical implications of these findings are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.
A Proposed Model of Jazz Theory Knowledge Acquisition

ERIC Educational Resources Information Center

Ciorba, Charles R.; Russell, Brian E.

2014-01-01

The purpose of this study was to test a hypothesized model that proposes a causal relationship between motivation and academic achievement on the acquisition of jazz theory knowledge. A reliability analysis of the latent variables ranged from 0.92 to 0.94. Confirmatory factor analyses of the motivation (standardized root mean square residual…
Analyzing Response Times in Tests with Rank Correlation Approaches

ERIC Educational Resources Information Center

Ranger, Jochen; Kuhn, Jorg-Tobias

2013-01-01

It is common practice to log-transform response times before analyzing them with standard factor analytical methods. However, sometimes the log-transformation is not capable of linearizing the relation between the response times and the latent traits. Therefore, a more general approach to response time analysis is proposed in the current…
Data Visualization of Item-Total Correlation by Median Smoothing

ERIC Educational Resources Information Center

Yu, Chong Ho; Douglas, Samantha; Lee, Anna; An, Min

2016-01-01

This paper aims to illustrate how data visualization could be utilized to identify errors prior to modeling, using an example with multi-dimensional item response theory (MIRT). MIRT combines item response theory and factor analysis to identify a psychometric model that investigates two or more latent traits. While it may seem convenient to…
Testing a Developmental-Ecological Model of Student Engagement: A Multilevel Latent Growth Curve Analysis

ERIC Educational Resources Information Center

You, Sukkyung; Sharkey, Jill

2009-01-01

US schools fail to engage a significant proportion of adolescent students. Although student engagement is significantly related to academic achievement, there is a dearth of longitudinal research simultaneously examining the impact of personal and contextual factors on student engagement at both individual and school levels. Using a…

Characterizing Student Expectations: A Small Empirical Study

ERIC Educational Resources Information Center

Warwick, Jonathan

2016-01-01

This paper describes the results of a small empirical study (n = 130), in which undergraduate students in the Business Faculty of a UK university were asked to express views and expectations relating to the study of a mathematics. Factor analysis is used to identify latent variables emerging from clusters of the measured variables and these are…
The Semantic Distance Task: Quantifying Semantic Distance with Semantic Network Path Length

ERIC Educational Resources Information Center

Kenett, Yoed N.; Levi, Effi; Anaki, David; Faust, Miriam

2017-01-01

Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We…
The Influence of Family and Teacher Factors on Early Disruptive School Behaviors: A Latent Profile Transition Analysis

ERIC Educational Resources Information Center

Racz, Sarah J.; O'Brennan, Lindsey M.; Bradshaw, Catherine P.; Leaf, Philip J.

2016-01-01

The kindergarten year plays an important role in establishing children's academic, social, and behavioral adjustment. Early identification of children who experience difficulties with the kindergarten transition is crucial to prevent continued behavioral and emotional problems. Family and school predictors of these early behavioral patterns can…
On the Performance Characteristics of Latent-Factor and Knowledge Tracing Models

ERIC Educational Resources Information Center

Klingler, Severin; Käser, Tanja; Solenthaler, Barbara; Gross, Markus

2015-01-01

Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among them two novel models that unify BKT and Item Response Theory (IRT). Latent Factor Knowledge…
On the Relation between the Linear Factor Model and the Latent Profile Model

ERIC Educational Resources Information Center

Halpin, Peter F.; Dolan, Conor V.; Grasman, Raoul P. P. P.; De Boeck, Paul

2011-01-01

The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do not yield equivalent estimates of the…
Exploring the effects of attitudinal and perception characteristics on drinking and driving non-compliant behaviour.

PubMed

Politis, Ioannis; Basbas, Socrates; Papaioannou, Panagiotis

2013-11-01

The objective of this paper is to examine a number of factors (observed and latent) that might have a causal effect on drinking and driving (D&D) behaviour. Face-to-face surveys were conducted among patrons at bars and cafeterias and 305 valid questionnaires were filled. A confirmatory factor analysis was performed so as to identify the latent constructs and a mixed structural equation model was developed. From the analysis it came up that non-compliant behaviour of D&D is limited at older ages, also associated with high levels of income and car availability. Though men are consuming more alcohol, women seem to be more prone in driving under the influence (DUI) of alcohol. Furthermore, it was found that people who strongly support the examined interventions in the study (e.g. better enforcement, more traffic safety campaigns, stricter penalties) are more unlikely to drive after drinking compare to those who have some objections. Finally, it was not found any statistically significant relation between individuals' level of awareness and D&D behaviour. Copyright © 2013 Elsevier Ltd. All rights reserved.
Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype.

PubMed

Frewen, Paul A; Brown, Matthew F D; Steuwe, Carolin; Lanius, Ruth A

2015-01-01

A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD). However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5) currently does not assess depersonalization and derealization. We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1) severe or 2) moderate PTSD symptom severity (D-PTSD classes). Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1) Reexperiencing, 2) Emotional Numbing/Anhedonia, 3) Dissociation, 4) Negative Alterations in Cognition & Mood, 5) Avoidance, and 6) Hyperarousal. The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD.
Understanding planning ability measured by the Tower of London: an evaluation of its internal structure by latent variable modeling.

PubMed

Koppenol-Gonzalez, Gabriela V; Bouwmeester, Samantha; Boonstra, A Marije

2010-12-01

The Tower of London (TOL) is a widely used instrument for assessing planning ability. Inhibition and (spatial) working memory are assumed to contribute to performance on the TOL, but findings about the relationship between these cognitive processes are often inconsistent. Moreover, the influence of specific properties of TOL problems on cognitive processes and difficulty level is often not taken into account. Furthermore, it may be expected that several planning strategies can be distinguished that cannot be extracted from the total score. In this study, a factor analysis and a latent class regression analysis were performed to address these issues. The results showed that 4 strategy groups that differed with respect to preplanning time could be distinguished. The effect of problem properties also differed for the 4 groups. Additional analyses showed that the groups differed on average planning performance but that there were no significant differences between inhibition and spatial working memory performance. Finally, it seemed that multiple factors influence performance on the TOL, the most important ones being the score measurements, the problem properties, and strategy use.
Maternal anaemia at delivery and haemoglobin evolution in children during their first 18 months of life using latent class analysis.

PubMed

Koura, Kobto G; Ouédraogo, Smaïla; Cottrell, Gilles; Le Port, Agnès; Massougbodji, Achille; Garcia, André

2012-01-01

Anaemia during pregnancy and at delivery is an important public health problem in low- and middle-income countries. Its association with the children's haemoglobin level over time remains unclear. Our goals were to identify distinct haemoglobin level trajectories using latent class analysis and to assess the association between these trajectories and maternal anaemia and other risk factors. A prospective study of children from birth to 18 months of life was conducted in a rural setting in Tori-Bossito, Benin. The main outcome measure was the haemoglobin levels repeatedly measured at 3, 6, 9, 12, 15 and 18 months. Variables were collected from the mothers at delivery and from their children at birth and during the follow-up. The analyses were performed by means of Latent Class Analysis which has never been used for this kind of data. All the analyses were performed with Stata software, version 11.0, using the generalized linear latent and mixed model (GLLAMM) framework. We showed that 33.7% of children followed a low haemoglobin trajectory and 66.3% a high trajectory during the first 18 months of life. Newborn anaemia, placental malaria, malaria attack, sickle cell trait and male gender were significantly associated with a lower children's haemoglobin level over time, whereas maternal age, children living in a polygamous family and with good feeding practices had a higher Hb level in the first18 months. We also showed that maternal anaemia was a predictor for 'low haemoglobin level trajectory' group membership but have no significant effect on children haemoglobin level over time. Latent Class Analyses framework seems well suited to analyse longitudinal data under the hypothesis that different subpopulations of subjects are present in the data, each with its own set of parameters, with distinctive evolutions that themselves may reflect distinctive aetiologies.
Maternal Anaemia at Delivery and Haemoglobin Evolution in Children during Their First 18 Months of Life Using Latent Class Analysis

PubMed Central

Koura, Kobto G.; Ouédraogo, Smaïla; Cottrell, Gilles; Le Port, Agnès; Massougbodji, Achille; Garcia, André

2012-01-01

Background Anaemia during pregnancy and at delivery is an important public health problem in low- and middle-income countries. Its association with the children’s haemoglobin level over time remains unclear. Our goals were to identify distinct haemoglobin level trajectories using latent class analysis and to assess the association between these trajectories and maternal anaemia and other risk factors. Method A prospective study of children from birth to 18 months of life was conducted in a rural setting in Tori-Bossito, Benin. The main outcome measure was the haemoglobin levels repeatedly measured at 3, 6, 9, 12, 15 and 18 months. Variables were collected from the mothers at delivery and from their children at birth and during the follow-up. The analyses were performed by means of Latent Class Analysis which has never been used for this kind of data. All the analyses were performed with Stata software, version 11.0, using the generalized linear latent and mixed model (GLLAMM) framework. Results We showed that 33.7% of children followed a low haemoglobin trajectory and 66.3% a high trajectory during the first 18 months of life. Newborn anaemia, placental malaria, malaria attack, sickle cell trait and male gender were significantly associated with a lower children’s haemoglobin level over time, whereas maternal age, children living in a polygamous family and with good feeding practices had a higher Hb level in the first18 months. We also showed that maternal anaemia was a predictor for ‘low haemoglobin level trajectory’ group membership but have no significant effect on children haemoglobin level over time. Conclusion Latent Class Analyses framework seems well suited to analyse longitudinal data under the hypothesis that different subpopulations of subjects are present in the data, each with its own set of parameters, with distinctive evolutions that themselves may reflect distinctive aetiologies. PMID:23185556
Modeling change in learning strategies throughout higher education: a multi-indicator latent growth perspective.

PubMed

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2013-01-01

The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.
Modeling Change in Learning Strategies throughout Higher Education: A Multi-Indicator Latent Growth Perspective

PubMed Central

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2013-01-01

The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles – Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain. PMID:23844112
Patterns of perceived barriers to medical care in older adults: a latent class analysis.

PubMed

Thorpe, Joshua M; Thorpe, Carolyn T; Kennelty, Korey A; Pandhi, Nancy

2011-08-03

This study examined multiple dimensions of healthcare access in order to develop a typology of perceived barriers to healthcare access in community-dwelling elderly. Secondary aims were to define distinct classes of older adults with similar perceived healthcare access barriers and to examine predictors of class membership to identify risk factors for poor healthcare access. A sample of 5,465 community-dwelling elderly was drawn from the 2004 wave of the Wisconsin Longitudinal Study. Perceived barriers to healthcare access were measured using items from the Group Health Association of America Consumer Satisfaction Survey. We used latent class analysis to assess the constellation of items measuring perceived barriers in access and multinomial logistic regression to estimate how risk factors affected the probability of membership in the latent barrier classes. Latent class analysis identified four classes of older adults. Class 1 (75% of sample) consisted of individuals with an overall low level of risk for perceived access problems (No Barriers). Class 2 (5%) perceived problems with the availability/accessibility of healthcare providers such as specialists or mental health providers (Availability/Accessibility Barriers). Class 3 (18%) perceived problems with how well their providers' operations arise organized to accommodate their needs and preferences (Accommodation Barriers). Class 4 (2%) perceived problems with all dimension of access (Severe Barriers). Results also revealed that healthcare affordability is a problem shared by members of all three barrier groups, suggesting that older adults with perceived barriers tend to face multiple, co-occurring problems. Compared to those classified into the No Barriers group, those in the Severe Barrier class were more likely to live in a rural county, have no health insurance, have depressive symptomatology, and speech limitations. Those classified into the Availability/Accessibility Barriers group were more likely to live in rural and micropolitan counties, have depressive symptomatology, more chronic conditions, and hearing limitations. Those in the Accommodation group were more likely to have depressive symptomatology and cognitive limitations. The current study identified a typology of perceived barriers in healthcare access in older adults. The identified risk factors for membership in perceived barrier classes could potentially assist healthcare organizations and providers with targeting polices and interventions designed to improve access in their most vulnerable older adult populations, particularly those in rural areas, with functional disabilities, or in poor mental health.
Investigation of Latent Traces Using Infrared Reflectance Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

Schubert, Till; Wenzel, Susanne; Roscher, Ribana; Stachniss, Cyrill

2016-06-01

The detection of traces is a main task of forensics. Hyperspectral imaging is a potential method from which we expect to capture more fluorescence effects than with common forensic light sources. This paper shows that the use of hyperspectral imaging is suited for the analysis of latent traces and extends the classical concept to the conservation of the crime scene for retrospective laboratory analysis. We examine specimen of blood, semen and saliva traces in several dilution steps, prepared on cardboard substrate. As our key result we successfully make latent traces visible up to dilution factor of 1:8000. We can attribute most of the detectability to interference of electromagnetic light with the water content of the traces in the shortwave infrared region of the spectrum. In a classification task we use several dimensionality reduction methods (PCA and LDA) in combination with a Maximum Likelihood classifier, assuming normally distributed data. Further, we use Random Forest as a competitive approach. The classifiers retrieve the exact positions of labelled trace preparation up to highest dilution and determine posterior probabilities. By modelling the classification task with a Markov Random Field we are able to integrate prior information about the spatial relation of neighboured pixel labels.
CCCTC-Binding Factor Acts as a Heterochromatin Barrier on Herpes Simplex Viral Latent Chromatin and Contributes to Poised Latent Infection

PubMed Central

2018-01-01

ABSTRACT Herpes simplex virus 1 (HSV-1) establishes latent infection in neurons via a variety of epigenetic mechanisms that silence its genome. The cellular CCCTC-binding factor (CTCF) functions as a mediator of transcriptional control and chromatin organization and has binding sites in the HSV-1 genome. We constructed an HSV-1 deletion mutant that lacked a pair of CTCF-binding sites (CTRL2) within the latency-associated transcript (LAT) coding sequences and found that loss of these CTCF-binding sites did not alter lytic replication or levels of establishment of latent infection, but their deletion reduced the ability of the virus to reactivate from latent infection. We also observed increased heterochromatin modifications on viral chromatin over the LAT promoter and intron. We therefore propose that CTCF binding at the CTRL2 sites acts as a chromatin insulator to keep viral chromatin in a form that is poised for reactivation, a state which we call poised latency. PMID:29437926
Assessing a dysphoric arousal model of acute stress disorder symptoms in a clinical sample of rape and bank robbery victims

PubMed Central

Hansen, Maj; Armour, Cherie; Elklit, Ask

2012-01-01

Background Since the introduction of Acute Stress Disorder (ASD) into the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) research has focused on the ability of ASD to predict PTSD rather than focusing on addressing ASD's underlying latent structure. The few existing confirmatory factor analytic (CFA) studies of ASD have failed to reach a clear consensus regarding ASD's underlying dimensionality. Although, the discrepancy in the results may be due to varying ASD prevalence rates, it remains possible that the model capturing the latent structure of ASD has not yet been put forward. One such model may be a replication of a new five-factor model of PTSD, which separates the arousal symptom cluster into Dysphoric and Anxious Arousal. Given the pending DSM-5, uncovering ASD's latent structure is more pertinent than ever. Objective Using CFA, four different models of the latent structure of ASD were specified and tested: the proposed DSM-5 model, the DSM-IV model, a three factor model, and a five factor model separating the arousal symptom cluster. Method The analyses were based on a combined sample of rape and bank robbery victims, who all met the diagnostic criteria for ASD (N = 404) using the Acute Stress Disorder Scale. Results The results showed that the five factor model provided the best fit to the data. Conclusions The results of the present study suggest that the dimensionality of ASD may be best characterized as a five factor structure which separates dysphoric and anxious arousal items into two separate factors, akin to recent research on PTSD's latent structure. Thus, the current study adds to the debate about how ASD should be conceptualized in the pending DSM-5. PMID:22893845
Assessing a dysphoric arousal model of acute stress disorder symptoms in a clinical sample of rape and bank robbery victims.

PubMed

Hansen, Maj; Armour, Cherie; Elklit, Ask

2012-01-01

Since the introduction of Acute Stress Disorder (ASD) into the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) research has focused on the ability of ASD to predict PTSD rather than focusing on addressing ASD's underlying latent structure. The few existing confirmatory factor analytic (CFA) studies of ASD have failed to reach a clear consensus regarding ASD's underlying dimensionality. Although, the discrepancy in the results may be due to varying ASD prevalence rates, it remains possible that the model capturing the latent structure of ASD has not yet been put forward. One such model may be a replication of a new five-factor model of PTSD, which separates the arousal symptom cluster into Dysphoric and Anxious Arousal. Given the pending DSM-5, uncovering ASD's latent structure is more pertinent than ever. USING CFA, FOUR DIFFERENT MODELS OF THE LATENT STRUCTURE OF ASD WERE SPECIFIED AND TESTED: the proposed DSM-5 model, the DSM-IV model, a three factor model, and a five factor model separating the arousal symptom cluster. The analyses were based on a combined sample of rape and bank robbery victims, who all met the diagnostic criteria for ASD (N = 404) using the Acute Stress Disorder Scale. The results showed that the five factor model provided the best fit to the data. The results of the present study suggest that the dimensionality of ASD may be best characterized as a five factor structure which separates dysphoric and anxious arousal items into two separate factors, akin to recent research on PTSD's latent structure. Thus, the current study adds to the debate about how ASD should be conceptualized in the pending DSM-5.
Latent Variable Modeling of Brain Gray Matter Volume and Psychopathy in Incarcerated Offenders

PubMed Central

Baskin-Sommers, Arielle R.; Neumann, Craig S.; Cope, Lora M.; Kiehl, Kent A.

2016-01-01

Advanced statistical modeling has become a prominent feature in psychological science and can be a useful approach for representing the neural architecture linked to psychopathology. Psychopathy, a disorder characterized by dysfunction in interpersonal-affective and impulsive-antisocial domains, is associated with widespread neural abnormalities. Several imaging studies suggest that underlying structural deficits in paralimbic regions are associated with psychopathy. While these studies are useful, they make assumptions about the organization of the brain and its relevance to individuals displaying psychopathic features. Capitalizing on statistical modeling, the present study (N=254) used latent variable methods to examine the structure of gray matter volume in male offenders, and assessed the latent relations between psychopathy and gray matter factors reflecting paralimbic and non-paralimbic regions. Results revealed good fit for a four-factor gray matter paralimbic model and these first-order factors were accounted for by a super-ordinate paralimbic ‘system’ factor. Moreover, a super-ordinate psychopathy factor significantly predicted the paralimbic, but not the non-paralimbic factor. The latent variable paralimbic model, specifically linked with psychopathy, goes beyond understanding of single brain regions within the system and provides evidence for psychopathy-related gray matter volume reductions in the paralimbic system as a whole. PMID:27269123
A Latent Transition Analysis Model for Assessing Change in Cognitive Skills

ERIC Educational Resources Information Center

Li, Feiming; Cohen, Allan; Bottge, Brian; Templin, Jonathan

2016-01-01

Latent transition analysis (LTA) was initially developed to provide a means of measuring change in dynamic latent variables. In this article, we illustrate the use of a cognitive diagnostic model, the DINA model, as the measurement model in a LTA, thereby demonstrating a means of analyzing change in cognitive skills over time. An example is…
Developmental Trajectories in Toddlers’ Self-restraint Predict Individual Differences in Executive Functions 14 Years Later: A Behavioral Genetic Analysis

PubMed Central

Friedman, Naomi P.; Miyake, Akira; Robinson, JoAnn L.; Hewitt, John K.

2011-01-01

We examined whether self-restraint in early childhood predicted individual differences in three executive functions (EFs; inhibiting prepotent responses, updating working memory, and shifting task sets) in late adolescence in a sample of ~950 twins. At ages 14, 20, 24, and 36 months, the children were shown an attractive toy and told not to touch it for 30 seconds. Latency to touch the toy increased with age, and latent class growth modeling distinguished two groups of children that differed in their latencies to touch the toy at all 4 time points. Using confirmatory factor analysis, the three EFs (measured with latent variables at age 17 years) were decomposed into a Common EF factor (isomorphic to response inhibition ability) and two factors specific to updating and shifting, respectively. Less restrained children had significantly lower scores on the Common EF factor, equivalent scores on the Updating-specific factor, and higher scores on the Shifting-specific factor than the more restrained children. The less restrained group also had lower IQ scores, but this effect was entirely mediated by the EF components. Twin models indicated that the associations were primarily genetic in origin for the Common EF variable but split between genetics and nonshared environment for the Shifting-specific variable. These results suggest a biological relation between individual differences in self-restraint and EFs, one that begins early in life and persists into late adolescence. PMID:21668099

A Factor Analytic Model of Drug-Related Behavior in Adolescence and Its Impact on Arrests at Multiple Stages of the Life Course

PubMed Central

2016-01-01

Objectives Recognizing the inherent variability of drug-related behaviors, this study develops an empirically-driven and holistic model of drug-related behavior during adolescence using factor analysis to simultaneously model multiple drug behaviors. Methods The factor analytic model uncovers latent dimensions of drug-related behaviors, rather than patterns of individuals. These latent dimensions are treated as empirical typologies which are then used to predict an individual’s number of arrests accrued at multiple phases of the life course. The data are robust enough to simultaneously capture drug behavior measures typically considered in isolation in the literature, and to allow for behavior to change and evolve over the period of adolescence. Results Results show that factor analysis is capable of developing highly descriptive patterns of drug offending, and that these patterns have great utility in predicting arrests. Results further demonstrate that while drug behavior patterns are predictive of arrests at the end of adolescence for both males and females, the impacts on arrests are longer lasting for females. Conclusions The various facets of drug behaviors have been a long-time concern of criminological research. However, the ability to model multiple behaviors simultaneously is often constrained by data that do not measure the constructs fully. Factor analysis is shown to be a useful technique for modeling adolescent drug involvement patterns in a way that accounts for the multitude and variability of possible behaviors, and in predicting future negative life outcomes, such as arrests. PMID:28435183
Investigating the Latent Structure of the Teacher Efficacy Scale

ERIC Educational Resources Information Center

Wagler, Amy; Wagler, Ron

2013-01-01

This article reevaluates the latent structure of the Teacher Efficacy Scale using confirmatory factor analyses (CFAs) on a sample of preservice teachers from a public university in the U.S. Southwest. The fit of a proposed two-factor CFA model with an error correlation structure consistent with internal/ external locus of control is compared to…
Using Trait-State Models to Evaluate the Longitudinal Consistency of Global Self-Esteem From Adolescence to Adulthood.

PubMed

Donnellan, M Brent; Kenny, David A; Trzesniewski, Kali H; Lucas, Richard E; Conger, Rand D

2012-12-01

The present research used a latent variable trait-state model to evaluate the longitudinal consistency of self-esteem during the transition from adolescence to adulthood. Analyses were based on ten administrations of the Rosenberg Self-Esteem scale (Rosenberg, 1965) spanning the ages of approximately 13 to 32 for a sample of 451 participants. Results indicated that a completely stable trait factor and an autoregressive trait factor accounted for the majority of the variance in latent self-esteem assessments, whereas state factors accounted for about 16% of the variance in repeated assessments of latent self-esteem. The stability of individual differences in self-esteem increased with age consistent with the cumulative continuity principle of personality development.
Using Trait-State Models to Evaluate the Longitudinal Consistency of Global Self-Esteem From Adolescence to Adulthood

PubMed Central

Donnellan, M. Brent; Kenny, David A.; Trzesniewski, Kali H.; Lucas, Richard E.; Conger, Rand D.

2012-01-01

The present research used a latent variable trait-state model to evaluate the longitudinal consistency of self-esteem during the transition from adolescence to adulthood. Analyses were based on ten administrations of the Rosenberg Self-Esteem scale (Rosenberg, 1965) spanning the ages of approximately 13 to 32 for a sample of 451 participants. Results indicated that a completely stable trait factor and an autoregressive trait factor accounted for the majority of the variance in latent self-esteem assessments, whereas state factors accounted for about 16% of the variance in repeated assessments of latent self-esteem. The stability of individual differences in self-esteem increased with age consistent with the cumulative continuity principle of personality development. PMID:23180899
Comprehensive discovery of subsample gene expression components by information explanation: therapeutic implications in cancer.

PubMed

Pepke, Shirley; Ver Steeg, Greg

2017-03-15

De novo inference of clinically relevant gene function relationships from tumor RNA-seq remains a challenging task. Current methods typically either partition patient samples into a few subtypes or rely upon analysis of pairwise gene correlations that will miss some groups in noisy data. Leveraging higher dimensional information can be expected to increase the power to discern targetable pathways, but this is commonly thought to be an intractable computational problem. In this work we adapt a recently developed machine learning algorithm for sensitive detection of complex gene relationships. The algorithm, CorEx, efficiently optimizes over multivariate mutual information and can be iteratively applied to generate a hierarchy of relatively independent latent factors. The learned latent factors are used to stratify patients for survival analysis with respect to both single factors and combinations. These analyses are performed and interpreted in the context of biological function annotations and protein network interactions that might be utilized to match patients to multiple therapies. Analysis of ovarian tumor RNA-seq samples demonstrates the algorithm's power to infer well over one hundred biologically interpretable gene cohorts, several times more than standard methods such as hierarchical clustering and k-means. The CorEx factor hierarchy is also informative, with related but distinct gene clusters grouped by upper nodes. Some latent factors correlate with patient survival, including one for a pathway connected with the epithelial-mesenchymal transition in breast cancer that is regulated by a microRNA that modulates epigenetics. Further, combinations of factors lead to a synergistic survival advantage in some cases. In contrast to studies that attempt to partition patients into a small number of subtypes (typically 4 or fewer) for treatment purposes, our approach utilizes subgroup information for combinatoric transcriptional phenotyping. Considering only the 66 gene expression groups that are found to both have significant Gene Ontology enrichment and are small enough to indicate specific drug targets implies a computational phenotype for ovarian cancer that allows for 3 66 possible patient profiles, enabling truly personalized treatment. The findings here demonstrate a new technique that sheds light on the complexity of gene expression dependencies in tumors and could eventually enable the use of patient RNA-seq profiles for selection of personalized and effective cancer treatments.
Defining failed induction of labor.

PubMed

Grobman, William A; Bailit, Jennifer; Lai, Yinglei; Reddy, Uma M; Wapner, Ronald J; Varner, Michael W; Thorp, John M; Leveno, Kenneth J; Caritis, Steve N; Prasad, Mona; Tita, Alan T N; Saade, George; Sorokin, Yoram; Rouse, Dwight J; Blackwell, Sean C; Tolosa, Jorge E

2018-01-01

While there are well-accepted standards for the diagnosis of arrested active-phase labor, the definition of a "failed" induction of labor remains less certain. One approach to diagnosing a failed induction is based on the duration of the latent phase. However, a standard for the minimum duration that the latent phase of a labor induction should continue, absent acute maternal or fetal indications for cesarean delivery, remains lacking. The objective of this study was to determine the frequency of adverse maternal and perinatal outcomes as a function of the duration of the latent phase among nulliparous women undergoing labor induction. This study is based on data from an obstetric cohort of women delivering at 25 US hospitals from 2008 through 2011. Nulliparous women who had a term singleton gestation in the cephalic presentation were eligible for this analysis if they underwent a labor induction. Consistent with prior studies, the latent phase was determined to begin once cervical ripening had ended, oxytocin was initiated, and rupture of membranes had occurred, and was determined to end once 5-cm dilation was achieved. The frequencies of cesarean delivery, as well as of adverse maternal (eg, postpartum hemorrhage, chorioamnionitis) and perinatal (eg, a composite frequency of seizures, sepsis, bone or nerve injury, encephalopathy, or death) outcomes, were compared as a function of the duration of the latent phase (analyzed with time both as a continuous measure and categorized in 3-hour increments). A total of 10,677 women were available for analysis. In the vast majority (96.4%) of women, the active phase had been reached by 15 hours. The longer the duration of a woman's latent phase, the greater her chance of ultimately undergoing a cesarean delivery (P < .001, for time both as a continuous and categorical independent variable), although >40% of women whose latent phase lasted ≥18 hours still had a vaginal delivery. Several maternal morbidities, such as postpartum hemorrhage (P < .001) and chorioamnionitis (P < .001), increased in frequency as the length of latent phase increased. Conversely, the frequencies of most adverse perinatal outcomes were statistically stable over time. The large majority of women undergoing labor induction will have entered the active phase by 15 hours after oxytocin has started and rupture of membranes has occurred. Maternal adverse outcomes become statistically more frequent with greater time in the latent phase, although the absolute increase in frequency is relatively small. These data suggest that cesarean delivery should not be undertaken during the latent phase prior to at least 15 hours after oxytocin and rupture of membranes have occurred. The decision to continue labor beyond this point should be individualized, and may take into account factors such as other evidence of labor progress. Copyright © 2017 Elsevier Inc. All rights reserved.
Text mining factor analysis (TFA) in green tea patent data

NASA Astrophysics Data System (ADS)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

Factor analysis has become one of the most widely used multivariate statistical procedures in applied research endeavors across a multitude of domains. There are two main types of analyses based on factor analysis: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Both EFA and CFA aim to observed relationships among a group of indicators with a latent variable, but they differ fundamentally, a priori and restrictions made to the factor model. This method will be applied to patent data technology sector green tea to determine the development technology of green tea in the world. Patent analysis is useful in identifying the future technological trends in a specific field of technology. Database patent are obtained from agency European Patent Organization (EPO). In this paper, CFA model will be applied to the nominal data, which obtain from the presence absence matrix. While doing processing, analysis CFA for nominal data analysis was based on Tetrachoric matrix. Meanwhile, EFA model will be applied on a title from sector technology dominant. Title will be pre-processing first using text mining analysis.
A Comparison of Approaches for the Analysis of Interaction Effects between Latent Variables Using Partial Least Squares Path Modeling

ERIC Educational Resources Information Center

Henseler, Jorg; Chin, Wynne W.

2010-01-01

In social and business sciences, the importance of the analysis of interaction effects between manifest as well as latent variables steadily increases. Researchers using partial least squares (PLS) to analyze interaction effects between latent variables need an overview of the available approaches as well as their suitability. This article…
The Ecology of Early Childhood Risk: A Canonical Correlation Analysis of Children’s Adjustment, Family, and Community Context in a High-Risk Sample

PubMed Central

Aiyer, Sophie M.; Wilson, Melvin N.; Shaw, Daniel S.; Dishion, Thomas J.

2013-01-01

The ecology of the emergence of psycho-pathology in early childhood is often approached by the analysis of a limited number of contextual risk factors. In the present study, we provide a comprehensive analysis of ecological risk by conducting a canonical correlation analysis of 13 risk factors at child age 2 and seven narrow-band scales of internalizing and externalizing problem behaviors at child age 4, using a sample of 364 geographically and ethnically diverse, disadvantaged primary caregivers, alternative caregivers, and preschool-age children. Participants were recruited from Special Supplemental Nutrition Program for Women, Infants, and Children sites and were screened for family risk. Canonical correlation analysis revealed that (1) a first latent combination of family and individual risks of caregivers predicted combinations of child emotional and behavioral problems, and that (2) a second latent combination of contextual and structural risks predicted child somatic complaints. Specifically, (1) the combination of chaotic home, conflict with child, parental depression, and parenting hassles predicted a co-occurrence of internalizing and externalizing behaviors, and (2) the combination of father absence, perceived discrimination, neighborhood danger, and fewer children living in the home predicted child somatic complaints. The research findings are discussed in terms of the development of psychopathology, as well as the potential prevention needs of families in high-risk contexts. PMID:23700232
Latino cigarette smoking patterns by gender in a US national sample

PubMed Central

Kristman-Valente, Allison; Flaherty, Brian P.

2015-01-01

Background Latino smokers are a rising public health concern who experience elevated tobacco related health disparities. Purpose Additional information on Latino smoking is needed to inform screening and treatment. Analysis Latent class analysis using smoking frequency, cigarette preferences, onset, smoking duration, cigarettes per day and minutes to first cigarette were used to create multivariate latent smoking profiles for Latino men and women. Results Final models found seven classes for Latinas and nine classes for Latinos. Despite a common finding in the literature that Latino smokers are more likely to be low-risk, intermittent smokers, the majority of classes, for both males and females, described patterns of high-risk, daily smoking. Gender variations in smoking classes were noted. Conclusions Several markers of smoking risk were identified among both male and female Latino smokers including long durations of smoking, daily smoking and preference for specialty cigarettes, all factors associated with long-term health consequences. PMID:26304857
The Attitudes to Ageing Questionnaire: Mokken Scaling Analysis

PubMed Central

Shenkin, Susan D.; Watson, Roger; Laidlaw, Ken; Starr, John M.; Deary, Ian J.

2014-01-01

Background Hierarchical scales are useful in understanding the structure of underlying latent traits in many questionnaires. The Attitudes to Ageing Questionnaire (AAQ) explored the attitudes to ageing of older people themselves, and originally described three distinct subscales: (1) Psychosocial Loss (2) Physical Change and (3) Psychological Growth. This study aimed to use Mokken analysis, a method of Item Response Theory, to test for hierarchies within the AAQ and to explore how these relate to underlying latent traits. Methods Participants in a longitudinal cohort study, the Lothian Birth Cohort 1936, completed a cross-sectional postal survey. Data from 802 participants were analysed using Mokken Scaling analysis. These results were compared with factor analysis using exploratory structural equation modelling. Results Participants were 51.6% male, mean age 74.0 years (SD 0.28). Three scales were identified from 18 of the 24 items: two weak Mokken scales and one moderate Mokken scale. (1) ‘Vitality’ contained a combination of items from all three previously determined factors of the AAQ, with a hierarchy from physical to psychosocial; (2) ‘Legacy’ contained items exclusively from the Psychological Growth scale, with a hierarchy from individual contributions to passing things on; (3) ‘Exclusion’ contained items from the Psychosocial Loss scale, with a hierarchy from general to specific instances. All of the scales were reliable and statistically significant with ‘Legacy’ showing invariant item ordering. The scales correlate as expected with personality, anxiety and depression. Exploratory SEM mostly confirmed the original factor structure. Conclusions The concurrent use of factor analysis and Mokken scaling provides additional information about the AAQ. The previously-described factor structure is mostly confirmed. Mokken scaling identifies a new factor relating to vitality, and a hierarchy of responses within three separate scales, referring to vitality, legacy and exclusion. This shows what older people themselves consider important regarding their own ageing. PMID:24892302
Using Confirmatory Factor Analysis to Understand Executive Control in Preschool Children: Sources of Variation in Emergent Mathematic Achievement

ERIC Educational Resources Information Center

Bull, Rebecca; Espy, Kimberly Andrews; Wiebe, Sandra A.; Sheffield, Tiffany D.; Nelson, Jennifer Mize

2011-01-01

Latent variable modeling methods have demonstrated utility for understanding the structure of executive control (EC) across development. These methods are utilized to better characterize the relation between EC and mathematics achievement in the preschool period, and to understand contributing sources of individual variation. Using the sample and…
The Counseling Opportunity Structure: Examining Correlates of Four-Year College-Going Rates

ERIC Educational Resources Information Center

Engberg, Mark E.; Gilbert, Aliza J.

2014-01-01

This study examines the relationships between the normative and resource dimensions of a high school counseling department and four-year college-going rates. Utilizing data from the High School Longitudinal Study of 2009 (HSLS: 09), we employ multiple regression and latent class analysis to identify salient factors related to the college-going…
Interference Control, Working Memory Capacity, and Cognitive Abilities: A Latent Variable Analysis

ERIC Educational Resources Information Center

Unsworth, Nash

2010-01-01

The present study examined whether various indices of interference control were related to one another and to other cognitive abilities. It was found that the interference control measures were weakly correlated and could form a single factor that was related to overall memory performance on the tasks as well as to measures of working memory…
Trajectories of Delinquent Behaviour in Adolescence and Their Covariates: Relations with Initial and Time-Averaged Factors

ERIC Educational Resources Information Center

Wiesner, Margit; Silbereisen, Rainer K.

2003-01-01

This longitudinal study examined individual, family, and peer covariates of distinctive trajectories of juvenile delinquency, using data from a community sample of 318 German adolescents (mean age at the first wave was 11.45 years). Latent growth mixture modelling analysis revealed four trajectory groups: high-level offenders, medium-level…
Early Childhood Teachers' Beliefs about Readiness for Teaching Science, Technology, Engineering, and Mathematics

ERIC Educational Resources Information Center

Park, Mi-Hwa; Dimitrov, Dimiter M.; Patterson, Lynn G.; Park, Do-Yong

2017-01-01

The purpose of this study was to examine beliefs of early childhood teachers about their readiness for teaching science, technology, engineering, and mathematics, with a focus on testing for heterogeneity of such beliefs and differential effects of teacher-related factors. The results from latent class analysis of survey data revealed two latent…
Use of Item Parceling in Structural Equation Modeling with Missing Data

ERIC Educational Resources Information Center

Orcan, Fatih

2013-01-01

Parceling is referred to as a procedure for computing sums or average scores across multiple items. Parcels instead of individual items are then used as indicators of latent factors in the structural equation modeling analysis (Bandalos 2002, 2008; Little et al., 2002; Yang, Nay, & Hoyle, 2010). Item parceling may be applied to alleviate some…
Differences between Peer Victimization in Cyber and Physical Settings and Associated Psychosocial Adjustment in Early Adolescence

ERIC Educational Resources Information Center

Dempsey, Allison G.; Sulkowski, Michael L.; Nichols, Rebecca; Storch, Eric A.

2009-01-01

The increasing use of cyberspace as a social networking forum creates a new medium for youth to become victims of peer aggression. This study used factor analysis techniques to confirm whether survey questions about frequency of cyber victimization formed a distinct latent construct from questions about relational and overt victimization…
Cumulative Disadvantage and Connections between Welfare Problems

ERIC Educational Resources Information Center

Bask, Miia

2011-01-01

In this paper, we perform a latent class factor analysis of a panel that involves two waves of data from an annual survey of living conditions in Sweden that were gathered in the years 1994-1995 and 2002-2003. We follow the same 3,149 individuals over both waves, describing them by sex, age group, family type, nationality background, education…
Partitioning of sublimation and evaporation from Lake Bonney using water vapor isotope and latent heat fluxes

NASA Astrophysics Data System (ADS)

Bellagamba, A. W.; Berkelhammer, M. B.; Winslow, L.; Peter, D.; Myers, K. F.

2017-12-01

The landscapes of the McMurdo Dry Valleys in Antarctica are characterized by a series of frozen lakes. Although the conditions in this region are severe, the lakes share common characteristics with lakes at glacial termini elsewhere. Geochemical and geomorphological evidence suggest these lakes have experienced large historical changes indicative of changes water balances. While part of these shifts in lake volume arise from changes in glacial inflow, they likely also reflect changes in the latent heat flux from the lake surfaces. Here we present a joint analysis of the stable isotopic ratio of surface ice/water and the water vapor flux over Dry Valley frozen lakes to ascertain the processes controlling water losses from the lake surfaces. We compare the isotopic ratio of the latent heat flux with the surface water isotopes to derive a fractionation factor associated with latent flux. This data is then used to provide insight into how much of the water vapor flux is sublimated versus evaporated, as well as how the sublimation and evaporative components of the flux change with synoptic weather. We used a Picarro L2130-I isotopic water analyzer to measure humidity and the isotopic ratio of water vapor at three heights over Lake Bonney in Taylor Valley, Antarctica and used the flux-gradient approach to convert the isotopic ratio of the vapor to an "isoflux". An on-site meteorological station recorded temperature, relative humidity and wind direction/intensity at two different heights above the lake and an infrared radiometer recorded lake skin temperature. These data were used to calculate the sensible and latent heat fluxes. The fractionation factor was close to 0, which indicates that sublimation was the primary component of the flux although evaporation became increasingly prominent following a katabatic wind event. The results suggest this technique could be an effective tool to study the sensitivity of latent heat fluxes to weather here and in other similar environments. The trial run performed at Lake Bonney in November-December 2016 was performed as part of the ongoing LTER (Long Term Ecological Research) project at the McMurdo Dry Valleys and a second experiment will be performed in January 2018.

Nuclear Localization of the C1 Factor (Host Cell Factor) in Sensory Neurons Correlates with Reactivation of Herpes Simplex Virus from Latency

NASA Astrophysics Data System (ADS)

Kristie, Thomas M.; Vogel, Jodi L.; Sears, Amy E.

1999-02-01

After a primary infection, herpes simplex virus is maintained in a latent state in neurons of sensory ganglia until complex stimuli reactivate viral lytic replication. Although the mechanisms governing reactivation from the latent state remain unknown, the regulated expression of the viral immediate early genes represents a critical point in this process. These genes are controlled by transcription enhancer complexes whose assembly requires and is coordinated by the cellular C1 factor (host cell factor). In contrast to other tissues, the C1 factor is not detected in the nuclei of sensory neurons. Experimental conditions that induce the reactivation of herpes simplex virus in mouse model systems result in rapid nuclear localization of the protein, indicating that the C1 factor is sequestered in these cells until reactivation signals induce a redistribution of the protein. The regulated localization suggests that C1 is a critical switch determinant of the viral lytic-latent cycle.
Latent-Trait Latent-Class Analysis of Self-Disclosure in the Work Environment

ERIC Educational Resources Information Center

Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk

2005-01-01

Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of self-disclosure. The model was used to analyze the data…
Latent Class Detection and Class Assignment: A Comparison of the MAXEIG Taxometric Procedure and Factor Mixture Modeling Approaches

ERIC Educational Resources Information Center

Lubke, Gitta; Tueller, Stephen

2010-01-01

Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class clustering, but they have very different sets of strengths and weaknesses. Taxometric procedures, popular in psychiatric and psychopathology applications, do not rely on distributional assumptions. Their sole purpose is to detect the presence of latent…
Taxometric and Factor Analytic Models of Anxiety Sensitivity: Integrating Approaches to Latent Structural Research

ERIC Educational Resources Information Center

Bernstein, Amit; Zvolensky, Michael J.; Norton, Peter J.; Schmidt, Norman B.; Taylor, Steven; Forsyth, John P.; Lewis, Sarah F.; Feldner, Matthew T.; Leen-Feldner, Ellen W.; Stewart, Sherry H.; Cox, Brian

2007-01-01

This study represents an effort to better understand the latent structure of anxiety sensitivity (AS), as indexed by the 16-item Anxiety Sensitivity Index (ASI; S. Reiss, R. A. Peterson, M. Gursky, & R. J. McNally, 1986), by using taxometric and factor-analytic approaches in an integrative manner. Taxometric analyses indicated that AS has a…
Factorial Invariance and Latent Mean Differences for the Five Factor Wellness Inventory with Korean and American Counselors

ERIC Educational Resources Information Center

Jang, Yoo Jin; Lee, Jayoung; Puig, Ana; Lee, Sang Min

2012-01-01

This study aimed to examine the factorial equivalence of the Five Factor Wellness Inventory across U.S. and Korean professional counselors and counselors-in-training. Latent means analyses demonstrated that there were significant differences between U.S. and Korean counselors for the five domains of wellness. (Contains 4 tables and 1 figure.)
The Latent Structure of Impulsivity: Impulsive Choice, Impulsive Action, and Impulsive Personality Traits

PubMed Central

MacKillop, James; Weafer, Jessica; Gray, Joshua; Oshri, Assaf; Palmer, Abraham; de Wit, Harriet

2016-01-01

Rationale Impulsivity has been strongly linked to addictive behaviors, but can be operationalized in a number of ways that vary considerably in overlap, suggesting multidimensionality. Objective This study tested the hypothesis that the latent structure among multiple measures of impulsivity would reflect three broad categories: impulsive choice, reflecting discounting of delayed rewards; impulsive action, reflecting ability to inhibit a prepotent motor response; and impulsive personality traits, reflecting self-reported attributions of self-regulatory capacity. Methods The study used a cross-sectional confirmatory factor analysis of multiple impulsivity assessments. Participants were 1252 young adults (62% female) with low levels of addictive behavior who were assessed in individual laboratory rooms at the University of Chicago and the University of Georgia. The battery comprised a delay discounting task, Monetary Choice Questionnaire, Conners Continuous Performance Test, Go/NoGo Task, Stop Signal Task, Barratt Impulsivity Scale, and the UPPS-P Impulsive Behavior Scale. Results The hypothesized three-factor model provided the best fit to the data, although Sensation Seeking was excluded from the final model. The three latent factors were largely unrelated to each other and were variably associated with substance use. Conclusions These findings support the hypothesis that diverse measures of impulsivity can broadly be organized into three categories that are largely distinct from one another. These findings warrant investigation among individuals with clinical levels of addictive behavior and may be applied to understanding the underlying biological mechanisms of these categories. PMID:27449350
Latent Class Analysis of Differential Item Functioning on the Peabody Picture Vocabulary Test-III

ERIC Educational Resources Information Center

Webb, Mi-young Lee; Cohen, Allan S.; Schwanenflugel, Paula J.

2008-01-01

This study investigated the use of latent class analysis for the detection of differences in item functioning on the Peabody Picture Vocabulary Test-Third Edition (PPVT-III). A two-class solution for a latent class model appeared to be defined in part by ability because Class 1 was lower in ability than Class 2 on both the PPVT-III and the…
The Use of a Context-Based Information Retrieval Technique

DTIC Science & Technology

2009-07-01

provided in context. Latent Semantic Analysis (LSA) is a statistical technique for inferring contextual and structural information, and previous studies...WAIS). 10 DSTO-TR-2322 1.4.4 Latent Semantic Analysis LSA, which is also known as latent semantic indexing (LSI), uses a statistical and...1.4.6 Language Models In contrast, natural language models apply algorithms that combine statistical information with semantic information. Semantic
The Houdini Transformation: True, but Illusory.

PubMed

Bentler, Peter M; Molenaar, Peter C M

2012-01-01

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This paper verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory, in the sense that the Houdini transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model.
The Houdini Transformation: True, but Illusory

PubMed Central

Bentler, Peter M.; Molenaar, Peter C. M.

2012-01-01

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This paper verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory, in the sense that the Houdini transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model. PMID:23180888
Structural Equation Model Trees

PubMed Central

Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman

2015-01-01

In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree structures that separate a data set recursively into subsets with significantly different parameter estimates in a SEM. SEM Trees provide means for finding covariates and covariate interactions that predict differences in structural parameters in observed as well as in latent space and facilitate theory-guided exploration of empirical data. We describe the methodology, discuss theoretical and practical implications, and demonstrate applications to a factor model and a linear growth curve model. PMID:22984789
Development of fraction comparison strategies: A latent transition analysis.

PubMed

Rinne, Luke F; Ye, Ai; Jordan, Nancy C

2017-04-01

The present study investigated the development of fraction comparison strategies through a longitudinal analysis of children's responses to a fraction comparison task in 4th through 6th grades (N = 394). Participants were asked to choose the larger value for 24 fraction pairs blocked by fraction type. Latent class analysis of performance over item blocks showed that most children initially exhibited a "whole number bias," indicating that larger numbers in numerators and denominators produce larger fraction values. However, some children instead chose fractions with smaller numerators and denominators, demonstrating a partial understanding that smaller numbers can yield larger fractions. Latent transition analysis showed that most children eventually adopted normative comparison strategies. Children who exhibited a partial understanding by choosing fractions with smaller numbers were more likely to adopt normative comparison strategies earlier than those with larger number biases. Controlling for general math achievement and other cognitive abilities, whole number line estimation accuracy predicted the probability of transitioning to normative comparison strategies. Exploratory factor analyses showed that over time, children appeared to increasingly represent fractions as discrete magnitudes when simpler strategies were unavailable. These results support the integrated theory of numerical development, which posits that an understanding of numbers as magnitudes unifies the process of learning whole numbers and fractions. The findings contrast with conceptual change theories, which propose that children must move from a view of numbers as counting units to a new view that accommodates fractions to overcome whole number bias. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Co-infection of two beta-herpesviruses (CMV and HHV-7) as an increased risk factor for 'CMV disease' in patients undergoing renal transplantation.

PubMed

Chapenko, S; Folkmane, I; Tomsone, V; Amerika, D; Rozentals, R; Murovska, M

2000-10-01

The ubiquity of human cytomegalovirus (CMV) and human herpesvirus-7 (HHV-7), as well as activation of these viruses during immunosuppression, allows the suggestion that both viruses could participate in the development of 'CMV disease' in patients after renal transplantation (RT). The aim of our research was to study the prevalence of latent CMV and HHV-7 infections in patients before RT, to determine interaction between these viruses in dual infection and possible association of their reactivation with the progression of 'CMV disease' after RT. Peripheral blood samples were collected from 49 patients before and up to 10-12 wk after RT. The methods used for diagnostics of viral infections were: serology, nested polymerase chain reaction (nPCR) analysis of peripheral blood leukocytes (PBL) and plasma, and virus isolation in cell cultures (morphological changes, nPCR analysis of cellular and cell-free samples, indirect immunofluorescence analysis). Before RT, CMV and HHV-7 DNAs were detected in PBL but not in the plasma samples, which indicates the presence of latent viral infection in patients. Latent dual (CMV + HHV-7) infection was prevalent (51.0%) in 49 patients, while CMV and HHV-7 infections alone were detected in 26.5 and 12.2% of patients, respectively. Risk of viral disease after RT, for recipients with latent dual infection before RT, was 12- and 2.2-fold higher in comparison with CMV and HHV-7 infections alone, respectively. Frequency of dual infection in 18 recipients with 'viral syndrome' or 'CMV disease' after RT was reliably higher (13/18, 81.3%) than CMV (1/18, 6.2%) (p < 0.025) and HHV-7 (2/18, 12.5%) (p < 0.025) infections alone. HHV-7 reactivation preceded CMV reactivation in 77.0% of the cases of dual infection in the recipients with viral disease and reactivation of both viruses preceded the development of viral disease. Severe 'CMV disease' developed in 2 out of 2 recipients with CMV primary infection and 'viral syndrome' in 1 recipient with CMV reinfection. The reactivation of CMV was detected in all recipients prior to onset of the disease. Correlation was shown between reactivation of latent HHV-7 infection and development of febrile syndrome in 2 out of 2 recipients with HHV-7 infection alone. Taking into account that dual infection is an increased risk factor for 'viral syndrome' and 'CMV disease' development, screening diagnostic should include testing for both viral infections in transplant donors as well as in recipients before and after RT.
Peplau's Theory of Interpersonal Relations: An Alternate Factor Structure for Patient Experience Data?

PubMed

Hagerty, Thomas A; Samuels, William; Norcini-Pala, Andrea; Gigliotti, Eileen

2017-04-01

A confirmatory factor analysis of data from the responses of 12,436 patients to 16 items on the Consumer Assessment of Healthcare Providers and Systems-Hospital survey was used to test a latent factor structure based on Peplau's middle-range theory of interpersonal relations. A two-factor model based on Peplau's theory fit these data well, whereas a three-factor model also based on Peplau's theory fit them excellently and provided a suitable alternate factor structure for the data. Though neither the two- nor three-factor model fit as well as the original factor structure, these results support using Peplau's theory to demonstrate nursing's extensive contribution to the experiences of hospitalized patients.
Do gender and directness of trauma exposure moderate PTSD's latent structure?

PubMed

Frankfurt, Sheila B; Armour, Cherie; Contractor, Ateka A; Elhai, Jon D

2016-11-30

The PTSD diagnosis and latent structure were substantially revised in the transition from DSM-IV to DSM-5. However, three alternative models (i.e., anhedonia model, externalizing behavior model, and hybrid model) of PTSD fit the DSM-5 symptom criteria better than the DSM-5 factor model. Thus, the psychometric performance of the DSM-5 and alternative models' PTSD factor structure needs to be critically evaluated. The current study examined whether gender or trauma directness (i.e., direct or indirect trauma exposure) moderates the PTSD latent structure when using the DSM-5 or alternative models. Model performance was evaluated with measurement invariance testing procedures on a large undergraduate sample (n=455). Gender and trauma directness moderated the DSM-5 PTSD and externalizing behavior model and did not moderate the anhedonia and hybrid models' latent structure. Clinical implications and directions for future research are discussed. Published by Elsevier Ireland Ltd.
Assessing DSM-5 latent subtypes of acute stress disorder dissociative or intrusive?

PubMed

Armour, Cherie; Hansen, Maj

2015-02-28

Acute Stress Disorder (ASD) was first included in the DSM-IV in 1994. It was proposed to account for traumatic responding in the early post trauma phase and to act as an identifier for later Posttraumatic Stress Disorder (PTSD). Unlike PTSD it included a number of dissociative indicators. The revised DSM-5 PTSD criterion included a dissociative-PTSD subtype. The current study assessed if a dissociative-ASD subtype may be present for DSM-5 ASD. Moreover, we assessed if a number of risk factors resulted in an increased probability of membership in symptomatic compared to a baseline ASD profile. We used data from 450 bank robbery victims. Latent profile analysis (LPA) was used to uncover latent profiles of ASD. Multinomial logistic regression was used to determine if female gender, age, social support, peritraumatic panic, somatization, and number of trauma exposures increased or decreased the probability of profile membership. Four latent profiles were uncovered and included an intrusion rather than dissociative subtype. Increased age and social support decreased the probability of individuals being grouped into the intrusion subtype whereas increased peritraumatic panic and somatization increased the probability of individuals being grouped into the intrusion subtype. Findings are discussed in regard to the ICD-11 and the DSM-5. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Exploring heterogeneity in clinical trials with latent class analysis

PubMed Central

Abarda, Abdallah; Contractor, Ateka A.; Wang, Juan; Dayton, C. Mitchell

2018-01-01

Case-mix is common in clinical trials and treatment effect can vary across different subgroups. Conventionally, a subgroup analysis is performed by dividing the overall study population by one or two grouping variables. It is usually impossible to explore complex high-order intersections among confounding variables. Latent class analysis (LCA) provides a framework to identify latent classes by observed manifest variables. Distal clinical outcomes and treatment effect can be different across these classes. This paper provides a step-by-step tutorial on how to perform LCA with R. A simulated dataset is generated to illustrate the process. In the example, the classify-analyze approach is employed to explore the differential treatment effects on distal outcomes across latent classes. PMID:29955579
A Bayesian Approach to a Multiple-Group Latent Class-Profile Analysis: The Timing of Drinking Onset and Subsequent Drinking Behaviors among U.S. Adolescents

ERIC Educational Resources Information Center

Chung, Hwan; Anthony, James C.

2013-01-01

This article presents a multiple-group latent class-profile analysis (LCPA) by taking a Bayesian approach in which a Markov chain Monte Carlo simulation is employed to achieve more robust estimates for latent growth patterns. This article describes and addresses a label-switching problem that involves the LCPA likelihood function, which has…
Development of the Anxiety Scale for Natural Disaster: Examination of its Reliability

NASA Astrophysics Data System (ADS)

Matsumoto, Miki; Yatabe, Ryuichi

The objective of present study was to develop the a nxiety scale for natural disaster, and to examineits reliability. We developed the 14 items for the anxiety scale based on anticipated damage of Nankai earthquake in Ehime prefecture. The subjects consist of 391 people in Yawatahama city, Ehime prefecture. Firstly, we analyzed the latent factors which influenced the anxiety for natural disaster by using the factor analysis method. Secondly, we cal culated Cronbach's coefficient alpha. The result of the factor analysis confirmed the three factors such as "anxiety for lifeline damage", "anxiety for second ary disaster" and "fear for others". Cronbach's coefficient alpha for each factor showed the high interna l consistency reliability. We considered that each factor could prove to be a valuable tool for researc h about the person's anxiety for natural disaster.
Gradient of association between parenting styles and patterns of drug use in adolescence: A latent class analysis.

PubMed

Valente, Juliana Y; Cogo-Moreira, Hugo; Sanchez, Zila M

2017-11-01

To identify different patterns of drug use in adolescence and determine if these are associated with parenting styles and other sociodemographic factors. A latent class analysis was conducted using baseline data collected in a sample (n=6381) from a randomized controlled trial conducted to evaluate the effectiveness of the #Tamojunto drug-use prevention program, carried out with 7th- and 8th-grade public school students in six Brazilian cities. Three latent classes were identified among the students: 1) abstainers/low users (81.54%), 2) alcohol users/binge drinkers (16.65%), and 3) polydrug users (1.80%). A gradient of inverse association was found between parenting styles (authoritative, authoritarian, and indulgent, with the neglectful style as a reference point) and the classes "alcohol users/binge drinkers" (aOR=0.36, 95%CI=0.27-0.47; aOR=0.56, 95%CI=0.43-0.72; and aOR=0.64, 95%CI=0.51-0.80, respectively) and "polydrug users" (aOR=0.09, 95%CI=0.03-0.24; aOR=0.23, 95%CI=0.11-0.52; and aOR=0.24, 95%CI=0.08-0.74, respectively). Associations were also revealed between the latent classes and the adolescent's age and socioeconomic status. The results suggest that activities to develop parenting skills should be included in school programs aimed at the prevention of drug use among adolescents in order to reduce neglectful practices and thereby possibly reduce drug use among the children. Copyright © 2017. Published by Elsevier B.V.

A Latent Profile Analysis and Structural Equation Modeling of the Instructional Quality of Mathematics Classrooms Based on the PISA 2012 Results of Korea and Singapore

ERIC Educational Resources Information Center

Yi, Hyun Sook; Lee, Yuree

2017-01-01

Teachers' classroom behaviors and their effects on student learning have received significant attention from educators, because the quality of instruction is a critical factor closely tied to students' learning experiences. Based on a theoretical model conceptualizing the quality of instruction, this study examined the characteristics of…
Cumulative Socioeconomic Status Risk, Allostatic Load, and Adjustment: A Prospective Latent Profile Analysis with Contextual and Genetic Protective Factors

ERIC Educational Resources Information Center

Brody, Gene H.; Yu, Tianyi; Chen, Yi-Fu; Kogan, Steven M.; Evans, Gary W.; Beach, Steven R. H.; Windle, Michael; Simons, Ronald L.; Gerrard, Meg; Gibbons, Frederick X.; Philibert, Robert A.

2013-01-01

The health disparities literature has identified a common pattern among middle-aged African Americans that includes high rates of chronic disease along with low rates of psychiatric disorders despite exposure to high levels of cumulative socioeconomic status (SES) risk. The current study was designed to test hypotheses about the developmental…
The Beck Depression Inventory, Second Edition (BDI-II): A Cross-Sample Structural Analysis

ERIC Educational Resources Information Center

Strunk, Kamden K.; Lane, Forrest C.

2017-01-01

A common concern about the Beck Depression Inventory, Second edition (BDI-II) among researchers in the area of depression has long been the single-factor scoring scheme. Methods exist for making cross-sample comparisons of latent structure but tend to rely on estimation methods that can be imprecise and unnecessarily complex. This study presents a…
The Cognitive Foundations of Reading and Arithmetic Skills in 7- to 10-Year-Olds

ERIC Educational Resources Information Center

Durand, Marianne; Hulme, Charles; Larkin, Rebecca; Snowling, Margaret

2005-01-01

A range of possible predictors of arithmetic and reading were assessed in a large sample (N=162) of children between ages 7 years 5 months and 10 years 4 months. A confirmatory factor analysis of the predictors revealed a good fit to a model consisting of four latent variables (verbal ability, nonverbal ability, search speed, and phonological…
A Latent Variable Approach to Determining the Structure of Executive Function in Preschool Children

ERIC Educational Resources Information Center

Miller, Michael R.; Giesbrecht, Gerald F.; Muller, Ulrich; McInerney, Robert J.; Kerns, Kimberly A.

2012-01-01

The composition of executive function (EF) in preschool children was examined using confirmatory factor analysis (CFA). A sample of 129 children between 3 and 5 years of age completed a battery of EF tasks. Using performance indicators of working memory and inhibition similar to previous CFA studies with preschoolers, we replicated a unitary EF…
A Confirmatory Factor Analysis of the California Verbal Learning Test-Second Edition (CVLT-II) in a Traumatic Brain Injury Sample

ERIC Educational Resources Information Center

DeJong, Joy; Donders, Jacobus

2009-01-01

The latent structure of the California Verbal Learning Test-Second Edition (CVLT-II) was examined in a clinical sample of 223 persons with traumatic brain injury that had been screened to remove individuals with complicating premorbid (e.g., psychiatric) or comorbid (e.g., financial compensation seeking) histories. Analyses incorporated the…
Factor Structure and Stability of Smoking-Related Health Beliefs in the National Lung Screening Trial

PubMed Central

Koblitz, Amber R.; Persoskie, Alexander; Ferrer, Rebecca A.; Klein, William M. P.; Dwyer, Laura A.; Park, Elyse R.

2016-01-01

Introduction: Absolute and comparative risk perceptions, worry, perceived severity, perceived benefits, and self-efficacy are important theoretical determinants of tobacco use, but no measures have been validated to ensure the discriminant validity as well as test-retest reliability of these measures in the tobacco context. The purpose of the current study is to examine the reliability and factor structure of a measure assessing smoking-related health cognitions and emotions in a national sample of current and former heavy smokers in the National Lung Screening Trial. Methods: A sub-study of the National Lung Screening Trial assessed current and former smokers’ (age 55–74; N = 4379) self-reported health cognitions and emotions at trial enrollment and at 12-month follow-up. Items were derived from the Health Belief Model and Self-Regulation Model. Results: An exploratory factor analysis of baseline responses revealed a five-factor structure for former smokers (risk perceptions, worry, perceived severity, perceived benefits, and self-efficacy) and a six-factor structure for current smokers, such that absolute risk and comparative risk perceptions emerged as separate factors. A confirmatory factor analysis of 12-month follow-up responses revealed a good fit for the five latent constructs for former smokers and six latent constructs for current smokers. Longitudinal stability of these constructs was also demonstrated. Conclusions: This is the first study to examine tobacco-related health cognition and emotional constructs over time in current and former heavy smokers undergoing lung screening. This study found that the theoretical constructs were stable across time and that the factor structure differed based on smoking status (current vs. former). PMID:25964503
Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype

PubMed Central

Frewen, Paul A.; Brown, Matthew F. D.; Steuwe, Carolin; Lanius, Ruth A.

2015-01-01

Objective A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD). However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5) currently does not assess depersonalization and derealization. Method We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. Results A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1) severe or 2) moderate PTSD symptom severity (D-PTSD classes). Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1) Reexperiencing, 2) Emotional Numbing/Anhedonia, 3) Dissociation, 4) Negative Alterations in Cognition & Mood, 5) Avoidance, and 6) Hyperarousal. Conclusions The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD. PMID:25854673
Simple construct evaluation with latent class analysis: An investigation of Facebook addiction and the development of a short form of the Facebook Addiction Test (F-AT).

PubMed

Dantlgraber, Michael; Wetzel, Eunike; Schützenberger, Petra; Stieger, Stefan; Reips, Ulf-Dietrich

2016-09-01

In psychological research, there is a growing interest in using latent class analysis (LCA) for the investigation of quantitative constructs. The aim of this study is to illustrate how LCA can be applied to gain insights on a construct and to select items during test development. We show the added benefits of LCA beyond factor-analytic methods, namely being able (1) to describe groups of participants that differ in their response patterns, (2) to determine appropriate cutoff values, (3) to evaluate items, and (4) to evaluate the relative importance of correlated factors. As an example, we investigated the construct of Facebook addiction using the Facebook Addiction Test (F-AT), an adapted version of the Internet Addiction Test (I-AT). Applying LCA facilitates the development of new tests and short forms of established tests. We present a short form of the F-AT based on the LCA results and validate the LCA approach and the short F-AT with several external criteria, such as chatting, reading newsfeeds, and posting status updates. Finally, we discuss the benefits of LCA for evaluating quantitative constructs in psychological research.
Person Re-Identification via Distance Metric Learning With Latent Variables.

PubMed

Sun, Chong; Wang, Dong; Lu, Huchuan

2017-01-01

In this paper, we propose an effective person re-identification method with latent variables, which represents a pedestrian as the mixture of a holistic model and a number of flexible models. Three types of latent variables are introduced to model uncertain factors in the re-identification problem, including vertical misalignments, horizontal misalignments and leg posture variations. The distance between two pedestrians can be determined by minimizing a given distance function with respect to latent variables, and then be used to conduct the re-identification task. In addition, we develop a latent metric learning method for learning the effective metric matrix, which can be solved via an iterative manner: once latent information is specified, the metric matrix can be obtained based on some typical metric learning methods; with the computed metric matrix, the latent variables can be determined by searching the state space exhaustively. Finally, extensive experiments are conducted on seven databases to evaluate the proposed method. The experimental results demonstrate that our method achieves better performance than other competing algorithms.
Persistence of low levels of plasma viremia and of the latent reservoir in patients under ART: A fractional-order approach

NASA Astrophysics Data System (ADS)

Pinto, Carla M. A.

2017-02-01

Low levels of viral load are found in HIV-infected patients, after many years under successful suppressive anti-retroviral therapy (ART). The factors leading to this persistence are still under debate, but it is now more or less accepted that the latent reservoir may be crucial to the maintenance of this residual viremia. In this paper, we study the role of the latent reservoir in the persistence of the latent reservoir and of the plasma viremia in a fractional-order (FO) model for HIV infection. Our model assumes that (i) the latently infected cells may undergo bystander proliferation, without active viral production, (ii) the latent cell activation rate decreases with time on ART, (iii) the productively infected cells' death rate is a function of the infected cell density. The proposed model provides new insights on the role of the latent reservoir in the persistence of the latent reservoir and of the plasma virus. Moreover, the fractional-order derivative distinguishes distinct velocities in the dynamics of the latent reservoir and of plasma virus. The later may be used to better approximations of HIV-infected patients data. To our best knowledge, this is the first FO model that deals with the role of the latent reservoir in the persistence of low levels of viremia and of the latent reservoir.
Alexithymia and psychosocial problems among Italian preadolescents. A latent class analysis approach.

PubMed

Mannarini, Stefania; Balottin, Laura; Toldo, Irene; Gatta, Michela

2016-10-01

The study, conducted on Italian preadolscents aged 11 to 13 belonging to the general population, aims to investigate the relationship between the emotional functioning, namely, alexithymia, and the risk of developing behavioral and emotional problems measured using the Strength and Difficulty Questionnaire. The latent class analysis approach allowed to identify two latent variables, accounting for the internalizing (emotional symptoms and difficulties in emotional awareness) and for the externalizing problems (conduct problems and hyperactivity, problematic relationships with peers, poor prosocial behaviors and externally oriented thinking). The two latent variables featured two latent classes: the difficulty in dealing with problems and the strength to face problems that was representative of most of the healthy participants with specific gender differences. Along with the analysis of psychopathological behaviors, the study of resilience and strengths can prove to be a key step in order to develop valuable preventive approaches to tackle psychiatric disorders. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.
LAT region factors mediating differential neuronal tropism of HSV-1 and HSV-2 do not act in trans.

PubMed

Bertke, Andrea S; Apakupakul, Kathleen; Ma, AyeAye; Imai, Yumi; Gussow, Anne M; Wang, Kening; Cohen, Jeffrey I; Bloom, David C; Margolis, Todd P

2012-01-01

After HSV infection, some trigeminal ganglion neurons support productive cycle gene expression, while in other neurons the virus establishes a latent infection. We previously demonstrated that HSV-1 and HSV-2 preferentially establish latent infection in A5+ and KH10+ sensory neurons, respectively, and that exchanging the latency-associated transcript (LAT) between HSV-1 and HSV-2 also exchanges the neuronal preference. Since many viral genes besides the LAT are functionally interchangeable between HSV-1 and HSV-2, we co-infected HSV-1 and HSV-2, both in vivo and in vitro, to determine if trans-acting viral factors regulate whether HSV infection follows a productive or latent pattern of gene expression in sensory neurons. The pattern of HSV-1 and HSV-2 latent infection in trigeminal neurons was no different following co-infection than with either virus alone, consistent with the hypothesis that a trans-acting viral factor is not responsible for the different patterns of latent infection of HSV-1 and HSV-2 in A5+ and KH10+ neurons. Since exchanging the LAT regions between the viruses also exchanges neuronal preferences, we infected transgenic mice that constitutively express 2.8 kb of the LAT region with the heterologous viral serotype. Endogenous expression of LAT did not alter the pattern of latent infection after inoculation with the heterologous serotype virus, demonstrating that the LAT region does not act in trans to direct preferential establishment of latency of HSV-1 and HSV-2. Using HSV1-RFP and HSV2-GFP in adult trigeminal ganglion neurons in vitro, we determined that HSV-1 and HSV-2 do not exert trans-acting effects during acute infection to regulate neuron specificity. Although some neurons were productively infected with both HSV-1 and HSV-2, no A5+ or KH10+ neurons were productively infected with both viruses. Thus, trans-acting viral factors do not regulate preferential permissiveness of A5+ and KH10+ neurons for productive HSV infection and preferential establishment of latent infection.
LAT Region Factors Mediating Differential Neuronal Tropism of HSV-1 and HSV-2 Do Not Act in Trans

PubMed Central

Bertke, Andrea S.; Apakupakul, Kathleen; Ma, AyeAye; Imai, Yumi; Gussow, Anne M.; Wang, Kening; Cohen, Jeffrey I.; Bloom, David C.; Margolis, Todd P.

2012-01-01

After HSV infection, some trigeminal ganglion neurons support productive cycle gene expression, while in other neurons the virus establishes a latent infection. We previously demonstrated that HSV-1 and HSV-2 preferentially establish latent infection in A5+ and KH10+ sensory neurons, respectively, and that exchanging the latency-associated transcript (LAT) between HSV-1 and HSV-2 also exchanges the neuronal preference. Since many viral genes besides the LAT are functionally interchangeable between HSV-1 and HSV-2, we co-infected HSV-1 and HSV-2, both in vivo and in vitro, to determine if trans-acting viral factors regulate whether HSV infection follows a productive or latent pattern of gene expression in sensory neurons. The pattern of HSV-1 and HSV-2 latent infection in trigeminal neurons was no different following co-infection than with either virus alone, consistent with the hypothesis that a trans-acting viral factor is not responsible for the different patterns of latent infection of HSV-1 and HSV-2 in A5+ and KH10+ neurons. Since exchanging the LAT regions between the viruses also exchanges neuronal preferences, we infected transgenic mice that constitutively express 2.8 kb of the LAT region with the heterologous viral serotype. Endogenous expression of LAT did not alter the pattern of latent infection after inoculation with the heterologous serotype virus, demonstrating that the LAT region does not act in trans to direct preferential establishment of latency of HSV-1 and HSV-2. Using HSV1-RFP and HSV2-GFP in adult trigeminal ganglion neurons in vitro, we determined that HSV-1 and HSV-2 do not exert trans-acting effects during acute infection to regulate neuron specificity. Although some neurons were productively infected with both HSV-1 and HSV-2, no A5+ or KH10+ neurons were productively infected with both viruses. Thus, trans-acting viral factors do not regulate preferential permissiveness of A5+ and KH10+ neurons for productive HSV infection and preferential establishment of latent infection. PMID:23300908
A Chromatin Insulator-Like Element in the Herpes Simplex Virus Type 1 Latency-Associated Transcript Region Binds CCCTC-Binding Factor and Displays Enhancer-Blocking and Silencing Activities

PubMed Central

Amelio, Antonio L.; McAnany, Peterjon K.; Bloom, David C.

2006-01-01

A previous study demonstrated that the latency-associated transcript (LAT) promoter and the LAT enhancer/reactivation critical region (rcr) are enriched in acetyl histone H3 (K9, K14) during herpes simplex virus type 1 (HSV-1) latency, whereas all lytic genes analyzed (ICP0, UL54, ICP4, and DNA polymerase) are not (N. J. Kubat, R. K. Tran, P. McAnany, and D. C. Bloom, J. Virol. 78:1139-1149, 2004). This suggests that the HSV-1 latent genome is organized into histone H3 (K9, K14) hyperacetylated and hypoacetylated regions corresponding to transcriptionally permissive and transcriptionally repressed chromatin domains, respectively. Such an organization implies that chromatin insulators, similar to those of cellular chromosomes, may separate distinct transcriptional domains of the HSV-1 latent genome. In the present study, we sought to identify cis elements that could partition the HSV-1 genome into distinct chromatin domains. Sequence analysis coupled with chromatin immunoprecipitation and luciferase reporter assays revealed that (i) the long and short repeats and the unique-short region of the HSV-1 genome contain clustered CTCF (CCCTC-binding factor) motifs, (ii) CTCF motif clusters similar to those in HSV-1 are conserved in other alphaherpesviruses, (iii) CTCF binds to these motifs on latent HSV-1 genomes in vivo, and (iv) a 1.5-kb region containing the CTCF motif cluster in the LAT region possesses insulator activities, specifically, enhancer blocking and silencing. The finding that CTCF, a cellular protein associated with chromatin insulators, binds to motifs on the latent genome and insulates the LAT enhancer suggests that CTCF may facilitate the formation of distinct chromatin boundaries during herpesvirus latency. PMID:16474142
Measuring Latent Quantities

ERIC Educational Resources Information Center

McDonald, Roderick P.

2011-01-01

A distinction is proposed between measures and predictors of latent variables. The discussion addresses the consequences of the distinction for the true-score model, the linear factor model, Structural Equation Models, longitudinal and multilevel models, and item-response models. A distribution-free treatment of calibration and…
Latent feature decompositions for integrative analysis of multi-platform genomic data

PubMed Central

Gregory, Karl B.; Momin, Amin A.; Coombes, Kevin R.; Baladandayuthapani, Veerabhadran

2015-01-01

Increased availability of multi-platform genomics data on matched samples has sparked research efforts to discover how diverse molecular features interact both within and between platforms. In addition, simultaneous measurements of genetic and epigenetic characteristics illuminate the roles their complex relationships play in disease progression and outcomes. However, integrative methods for diverse genomics data are faced with the challenges of ultra-high dimensionality and the existence of complex interactions both within and between platforms. We propose a novel modeling framework for integrative analysis based on decompositions of the large number of platform-specific features into a smaller number of latent features. Subsequently we build a predictive model for clinical outcomes accounting for both within- and between-platform interactions based on Bayesian model averaging procedures. Principal components, partial least squares and non-negative matrix factorization as well as sparse counterparts of each are used to define the latent features, and the performance of these decompositions is compared both on real and simulated data. The latent feature interactions are shown to preserve interactions between the original features and not only aid prediction but also allow explicit selection of outcome-related features. The methods are motivated by and applied to, a glioblastoma multiforme dataset from The Cancer Genome Atlas to predict patient survival times integrating gene expression, microRNA, copy number and methylation data. For the glioblastoma data, we find a high concordance between our selected prognostic genes and genes with known associations with glioblastoma. In addition, our model discovers several relevant cross-platform interactions such as copy number variation associated gene dosing and epigenetic regulation through promoter methylation. On simulated data, we show that our proposed method successfully incorporates interactions within and between genomic platforms to aid accurate prediction and variable selection. Our methods perform best when principal components are used to define the latent features. PMID:26146492
A unified statistical approach to non-negative matrix factorization and probabilistic latent semantic indexing

PubMed Central

Wang, Guoli; Ebrahimi, Nader

2014-01-01

Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H, such that V ∼ W H. It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H. In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data. PMID:25821345
A unified statistical approach to non-negative matrix factorization and probabilistic latent semantic indexing.

PubMed

Devarajan, Karthik; Wang, Guoli; Ebrahimi, Nader

2015-04-01

Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H , such that V ∼ W H . It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H . In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data.
Longitudinal Models of Reliability and Validity: A Latent Curve Approach.

ERIC Educational Resources Information Center

Tisak, John; Tisak, Marie S.

1996-01-01

Dynamic generalizations of reliability and validity that will incorporate longitudinal or developmental models, using latent curve analysis, are discussed. A latent curve model formulated to depict change is incorporated into the classical definitions of reliability and validity. The approach is illustrated with sociological and psychological…

Syndemic Risk Classes and Substance Use Problems among Adults in High-Risk Urban Areas: A Latent Class Analysis.

PubMed

Cleland, Charles M; Lanza, Stephanie T; Vasilenko, Sara A; Gwadz, Marya

2017-01-01

Substance use problems tend to co-occur with risk factors that are especially prevalent in urban communities with high rates of poverty. The present study draws on Syndemics Theory to understand profiles of risk and resilience and their associations with substance use problems in a population at risk for adverse outcomes. African-American/Black and Hispanic heterosexual adults ( N = 2,853) were recruited by respondent-driven sampling from an urban area with elevated poverty rates, and completed a structured assessment battery covering sociodemographics, syndemic factors (that is, multiple, co-occurring risk factors), and substance use. More than one-third of participants (36%) met criteria for either an alcohol or a drug problem in the past year. Latent class analysis identified profiles of risk and resilience, separately for women and men, which were associated with the probability of a substance use problem. Almost a third of women (27%) and 38% of men had lower risk profiles-patterns of resilience not apparent in other types of analyses. Profiles with more risk and fewer resilience factors were associated with an increased probability of substance use problems, but profiles with fewer risk and more resilience factors had rates of substance use problems that were very similar to the general adult population. Relative to the lowest risk profile, profiles with the most risk and fewest resilience factors were associated with increased odds of a substance use problem for both women [adjusted odds ratio (aOR) = 8.50; 95% CI: 3.85-18.74] and men (aOR = 11.68; 95% CI: 6.91-19.74). Addressing syndemic factors in substance use treatment and prevention may yield improved outcomes.
Measurement invariance of big-five factors over the life span: ESEM tests of gender, age, plasticity, maturity, and la dolce vita effects.

PubMed

Marsh, Herbert W; Nagengast, Benjamin; Morin, Alexandre J S

2013-06-01

This substantive-methodological synergy applies evolving approaches to factor analysis to substantively important developmental issues of how five-factor-approach (FFA) personality measures vary with gender, age, and their interaction. Confirmatory factor analyses (CFAs) conducted at the item level often do not support a priori FFA structures, due in part to the overly restrictive assumptions of CFA models. Here we demonstrate that exploratory structural equation modeling (ESEM), an integration of CFA and exploratory factor analysis, overcomes these problems with the 15-item Big Five Inventory administered as part of the nationally representative British Household Panel Study (N = 14,021; age: 15-99 years, Mage = 47.1). ESEM fitted the data substantially better and resulted in much more differentiated (less correlated) factors than did CFA. Methodologically, we extended ESEM (introducing ESEM-within-CFA models and a hybrid of multiple groups and multiple indicators multiple causes models), evaluating full measurement invariance and latent mean differences over age, gender, and their interaction. Substantively the results showed that women had higher latent scores for all Big Five factors except for Openness and that these gender differences were consistent over the entire life span. Substantial nonlinear age effects led to the rejection of the plaster hypothesis and the maturity principle but did support a newly proposed la dolce vita effect in old age. In later years, individuals become happier (more agreeable and less neurotic), more self-content and self-centered (less extroverted and open), more laid back and satisfied with what they have (less conscientious, open, outgoing and extroverted), and less preoccupied with productivity. PsycINFO Database Record (c) 2013 APA, all rights reserved
The intergenerational transmission of conduct problems.

PubMed

Raudino, Alessandra; Fergusson, David M; Woodward, Lianne J; Horwood, L John

2013-03-01

Drawing on prospective longitudinal data, this paper examines the intergenerational transmission of childhood conduct problems in a sample of 209 parents and their 331 biological offspring studied as part of the Christchurch Health and Developmental Study. The aims were to estimate the association between parental and offspring conduct problems and to examine the extent to which this association could be explained by (a) confounding social/family factors from the parent's childhood and (b) intervening factors reflecting parental behaviours and family functioning. The same item set was used to assess childhood conduct problems in parents and offspring. Two approaches to data analysis (generalised estimating equation regression methods and latent variable structural equation modelling) were used to examine possible explanations of the intergenerational continuity in behaviour. Regression analysis suggested that there was moderate intergenerational continuity (r = 0.23, p < 0.001) between parental and offspring conduct problems. This continuity was not explained by confounding factors but was partially mediated by parenting behaviours, particularly parental over-reactivity. Latent variable modelling designed to take account of non-observed common genetic and environmental factors underlying the continuities in problem behaviours across generations also suggested that parenting behaviour played a role in mediating the intergenerational transmission of conduct problems. There is clear evidence of intergenerational continuity in conduct problems. In part this association reflects a causal chain process in which parental conduct problems are associated (directly or indirectly) with impaired parenting behaviours that in turn influence risks of conduct problems in offspring.
Extracellular heat shock protein HSP90{beta} secreted by MG63 osteosarcoma cells inhibits activation of latent TGF-{beta}1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suzuki, Shigeki; Kulkarni, Ashok B., E-mail: ak40m@nih.gov

2010-07-30

Transforming growth factor-beta 1 (TGF-{beta}1) is secreted as a latent complex, which consists of latency-associated peptide (LAP) and the mature ligand. The release of the mature ligand from LAP usually occurs through conformational change of the latent complex and is therefore considered to be the first step in the activation of the TGF-{beta} signaling pathway. So far, factors such as heat, pH changes, and proteolytic cleavage are reportedly involved in this activation process, but the precise molecular mechanism is still far from clear. Identification and characterization of the cell surface proteins that bind to LAP are important to our understandingmore » of the latent TGF-{beta} activation process. In this study, we have identified heat shock protein 90 {beta} (HSP90{beta}) from the cell surface of the MG63 osteosarcoma cell line as a LAP binding protein. We have also found that MG63 cells secrete HSP90{beta} into extracellular space which inhibits the activation of latent TGF-{beta}1, and that there is a subsequent decrease in cell proliferation. TGF-{beta}1-mediated stimulation of MG63 cells resulted in the increased cell surface expression of HSP90{beta}. Thus, extracellular HSP90{beta} is a negative regulator for the activation of latent TGF-{beta}1 modulating TGF-{beta} signaling in the extracellular domain. -- Research highlights: {yields} Transforming growth factor-beta 1 (TGF-{beta}1) is secreted as a latent complex. {yields} This complex consists of latency-associated peptide (LAP) and the mature ligand. {yields} The release of the mature ligand from LAP is the first step in TGF-{beta} activation. {yields} We identified for the first time a novel mechanism for this activation process. {yields} Heat shock protein 90 {beta} is discovered as a negative regulator for this process.« less
Tuberculosis and latent tuberculosis infection among healthcare workers in Kisumu, Kenya.

PubMed

Agaya, Janet; Nnadi, Chimeremma D; Odhiambo, Joseph; Obonyo, Charles; Obiero, Vincent; Lipke, Virginia; Okeyo, Elisha; Cain, Kevin; Oeltmann, John E

2015-12-01

To assess prevalence and occupational risk factors of latent TB infection and history of TB disease ascribed to work in a healthcare setting in western Kenya. We conducted a cross-sectional survey among healthcare workers in western Kenya in 2013. They were recruited from dispensaries, health centres and hospitals that offer both TB and HIV services. School workers from the health facilities' catchment communities were randomly selected to serve as the community comparison group. Latent TB infection was diagnosed by tuberculin skin testing. HIV status of participants was assessed. Using a logistic regression model, we determined the adjusted odds of latent TB infection among healthcare workers compared to school workers; and among healthcare workers only, we assessed work-related risk factors for latent TB infection. We enrolled 1005 healthcare workers and 411 school workers. Approximately 60% of both groups were female. A total of 22% of 958 healthcare workers and 12% of 392 school workers tested HIV positive. Prevalence of self-reported history of TB disease was 7.4% among healthcare workers and 3.6% among school workers. Prevalence of latent TB infection was 60% among healthcare workers and 48% among school workers. Adjusted odds of latent TB infection were 1.5 times higher among healthcare workers than school workers (95% confidence interval 1.2-2.0). Healthcare workers at all three facility types had similar prevalence of latent TB infection (P = 0.72), but increasing years of employment was associated with increased odds of LTBI (P < 0.01). Healthcare workers at facilities in western Kenya which offer TB and HIV services are at increased risk of latent TB infection, and the risk is similar across facility types. Implementation of WHO-recommended TB infection control measures are urgently needed in health facilities to protect healthcare workers. © 2015 John Wiley & Sons Ltd.
Meta-analysis of human gene expression in response to Mycobacterium tuberculosis infection reveals potential therapeutic targets.

PubMed

Wang, Zhang; Arat, Seda; Magid-Slav, Michal; Brown, James R

2018-01-10

With the global emergence of multi-drug resistant strains of Mycobacterium tuberculosis, new strategies to treat tuberculosis are urgently needed such as therapeutics targeting potential human host factors. Here we performed a statistical meta-analysis of human gene expression in response to both latent and active pulmonary tuberculosis infections from nine published datasets. We found 1655 genes that were significantly differentially expressed during active tuberculosis infection. In contrast, no gene was significant for latent tuberculosis. Pathway enrichment analysis identified 90 significant canonical human pathways, including several pathways more commonly related to non-infectious diseases such as the LRRK2 pathway in Parkinson's disease, and PD-1/PD-L1 signaling pathway important for new immuno-oncology therapies. The analysis of human genome-wide association studies datasets revealed tuberculosis-associated genetic variants proximal to several genes in major histocompatibility complex for antigen presentation. We propose several new targets and drug-repurposing opportunities including intravenous immunoglobulin, ion-channel blockers and cancer immuno-therapeutics for development as combination therapeutics with anti-mycobacterial agents. Our meta-analysis provides novel insights into host genes and pathways important for tuberculosis and brings forth potential drug repurposing opportunities for host-directed therapies.
Latent variable model for suicide risk in relation to social capital and socio-economic status.

PubMed

Congdon, Peter

2012-08-01

There is little evidence on the association between suicide outcomes (ideation, attempts, self-harm) and social capital. This paper investigates such associations using a structural equation model based on health survey data, and allowing for both individual and contextual risk factors. Social capital and other major risk factors for suicide, namely socioeconomic status and social isolation, are modelled as latent variables that are proxied (or measured) by observed indicators or question responses for survey subjects. These latent scales predict suicide risk in the structural component of the model. Also relevant to explaining suicide risk are contextual variables, such as area deprivation and region of residence, as well as the subject's demographic status. The analysis is based on the 2007 Adult Psychiatric Morbidity Survey and includes 7,403 English subjects. A Bayesian modelling strategy is used. Models with and without social capital as a predictor of suicide risk are applied. A benefit to statistical fit is demonstrated when social capital is added as a predictor. Social capital varies significantly by geographic context variables (neighbourhood deprivation, region), and this impacts on the direct effects of these contextual variables on suicide risk. In particular, area deprivation is not confirmed as a distinct significant influence. The model develops a suicidality risk score incorporating social capital, and the success of this risk score in predicting actual suicide events is demonstrated. Social capital as reflected in neighbourhood perceptions is a significant factor affecting risks of different types of self-harm and may mediate the effects of other contextual variables such as area deprivation.
Global, broad, or specific cognitive differences? Using a MIMIC model to examine differences in CHC abilities in children with learning disabilities.

PubMed

Niileksela, Christopher R; Reynolds, Matthew R

2014-01-01

This study was designed to better understand the relations between learning disabilities and different levels of latent cognitive abilities, including general intelligence (g), broad cognitive abilities, and specific abilities based on the Cattell-Horn-Carroll theory of intelligence (CHC theory). Data from the Differential Ability Scales-Second Edition (DAS-II) were used to create a multiple-indicator multiple cause model to examine the latent mean differences in cognitive abilities between children with and without learning disabilities in reading (LD reading), math (LD math), and reading and writing(LD reading and writing). Statistically significant differences were found in the g factor between the norm group and the LD groups. After controlling for differences in g, the LD reading and LD reading and writing groups showed relatively lower latent processing speed, and the LD math group showed relatively higher latent comprehension-knowledge. There were also some differences in some specific cognitive abilities, including lower scores in spatial relations and numerical facility for the LD math group, and lower scores in visual memory for the LD reading and writing group. These specific mean differences were above and beyond any differences in the latent cognitive factor means.
Types of Dual and Poly-Tobacco Users in the US Military.

PubMed

Little, Melissa A; Bursac, Zoran; Derefinko, Karen J; Ebbert, Jon O; Talcott, Gerald W; Hryshko-Mullen, Ann; Klesges, Robert C

2016-08-01

The present investigation was designed to determine the prevalence and types of dual and poly-use of tobacco products in the US Air Force, as well as characteristics and factors associated with these types. We conducted a cross-sectional assessment of tobacco-product use among 13,873 Air Force trainees from 2013 to 2014. The assessment included prevalence of the use of 10 different tobacco products and demographic and environmental factors, such as risk perceptions of tobacco use, peer use, and tobacco-company influences. Latent class analysis was carried out to determine types of poly-tobacco users. Tobacco-product use was reported by 27.1% of participants, and of those, over half reported using more than 1 tobacco product. Latent class analysis indicated 5 classes of poly-tobacco use. Factors associated with poly-tobacco (vs. mono-tobacco) use included lower confidence to remain tobacco-free, low harm perceptions, and receiving tobacco products free at bars or social events. Rates of dual and poly-tobacco use are high among trainees, and while these groups are similar to mono users in some ways, there are a number of differences that need to be considered when developing targeted interventions to address use of multiple tobacco products. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Isolation of virus from brain after immunosuppression of mice with latent herpes simplex

NASA Astrophysics Data System (ADS)

Kastrukoff, Lorne; Long, Carol; Doherty, Peter C.; Wroblewska, Zofia; Koprowski, Hilary

1981-06-01

Herpes simplex virus (HSV) is usually present in a latent form in the trigeminal ganglion of man1-3. Various stress factors may induce virus reactivation, which is manifest by a lip lesion (innervated from the trigeminal ganglion) and the production of infectious virus. The considerable experimental efforts to define the conditions that lead to the reactivation of latent HSV have concentrated on isolating virus either from the original extraneural site of virus inoculation, or from cell-free homogenates of sensory ganglia from latently infected animals4-15. Recent DNA hybridization experiments resulted in the demonstration of the presence of HSV genomes in the brain tissue of both latently infected mice, and of humans who showed no clinical symptoms of HSV (ref. 16 and N. Fraser, personal communication). This led us to consider the possibility that HSV may be present in brain tissue as the result of either reactivation of the virus in brain cells or the passage of reactivated virus from trigeminal ganglia through the brain stem to the brain. The presence of infectious HSV in brain tissue has not previously been demonstrated; yet this could be a factor in chronic, relapsing neurological diseases such as multiple sclerosis. We have now shown experimentally that mice carrying latent HSV in their trigeminal ganglia may, following massive immunosuppression, express infectious virus in the central nervous system (CNS).
Nonlinear and Quasi-Simplex Patterns in Latent Growth Models

ERIC Educational Resources Information Center

Bianconcini, Silvia

2012-01-01

In the SEM literature, simplex and latent growth models have always been considered competing approaches for the analysis of longitudinal data, even if they are strongly connected and both of specific importance. General dynamic models, which simultaneously estimate autoregressive structures and latent curves, have been recently proposed in the…
An integrated phenomic approach to multivariate allelic association

PubMed Central

Medland, Sarah Elizabeth; Neale, Michael Churton

2010-01-01

The increased feasibility of genome-wide association has resulted in association becoming the primary method used to localize genetic variants that cause phenotypic variation. Much attention has been focused on the vast multiple testing problems arising from analyzing large numbers of single nucleotide polymorphisms. However, the inflation of experiment-wise type I error rates through testing numerous phenotypes has received less attention. Multivariate analyses can be used to detect both pleiotropic effects that influence a latent common factor, and monotropic effects that operate at a variable-specific levels, whilst controlling for non-independence between phenotypes. In this study, we present a maximum likelihood approach, which combines both latent and variable-specific tests and which may be used with either individual or family data. Simulation results indicate that in the presence of factor-level association, the combined multivariate (CMV) analysis approach performs well with a minimal loss of power as compared with a univariate analysis of a factor or sum score (SS). As the deviation between the pattern of allelic effects and the factor loadings increases, the power of univariate analyses of both factor and SSs decreases dramatically, whereas the power of the CMV approach is maintained. We show the utility of the approach by examining the association between dopamine receptor D2 TaqIA and the initiation of marijuana, tranquilizers and stimulants in data from the Add Health Study. Perl scripts that takes ped and dat files as input and produces Mx scripts and data for running the CMV approach can be downloaded from www.vipbg.vcu.edu/~sarahme/WriteMx. PMID:19707246
Validating the Copenhagen Psychosocial Questionnaire (COPSOQ-II) Using Set-ESEM: Identifying Psychosocial Risk Factors in a Sample of School Principals

PubMed Central

Dicke, Theresa; Marsh, Herbert W.; Riley, Philip; Parker, Philip D.; Guo, Jiesi; Horwood, Marcus

2018-01-01

School principals world-wide report high levels of strain and attrition resulting in a shortage of qualified principals. It is thus crucial to identify psychosocial risk factors that reflect principals' occupational wellbeing. For this purpose, we used the Copenhagen Psychosocial Questionnaire (COPSOQ-II), a widely used self-report measure covering multiple psychosocial factors identified by leading occupational stress theories. We evaluated the COPSOQ-II regarding factor structure and longitudinal, discriminant, and convergent validity using latent structural equation modeling in a large sample of Australian school principals (N = 2,049). Results reveal that confirmatory factor analysis produced marginally acceptable model fit. A novel approach we call set exploratory structural equation modeling (set-ESEM), where cross-loadings were only allowed within a priori defined sets of factors, fit well, and was more parsimonious than a full ESEM. Further multitrait-multimethod models based on the set-ESEM confirm the importance of a principal's psychosocial risk factors; Stressors and depression were related to demands and ill-being, while confidence and autonomy were related to wellbeing. We also show that working in the private sector was beneficial for showing a low psychosocial risk, while other demographics have little effects. Finally, we identify five latent risk profiles (high risk to no risk) of school principals based on all psychosocial factors. Overall the research presented here closes the theory application gap of a strong multi-dimensional measure of psychosocial risk-factors. PMID:29760670
Validating the Copenhagen Psychosocial Questionnaire (COPSOQ-II) Using Set-ESEM: Identifying Psychosocial Risk Factors in a Sample of School Principals.

PubMed

Dicke, Theresa; Marsh, Herbert W; Riley, Philip; Parker, Philip D; Guo, Jiesi; Horwood, Marcus

2018-01-01

School principals world-wide report high levels of strain and attrition resulting in a shortage of qualified principals. It is thus crucial to identify psychosocial risk factors that reflect principals' occupational wellbeing. For this purpose, we used the Copenhagen Psychosocial Questionnaire (COPSOQ-II), a widely used self-report measure covering multiple psychosocial factors identified by leading occupational stress theories. We evaluated the COPSOQ-II regarding factor structure and longitudinal, discriminant, and convergent validity using latent structural equation modeling in a large sample of Australian school principals ( N = 2,049). Results reveal that confirmatory factor analysis produced marginally acceptable model fit. A novel approach we call set exploratory structural equation modeling (set-ESEM), where cross-loadings were only allowed within a priori defined sets of factors, fit well, and was more parsimonious than a full ESEM. Further multitrait-multimethod models based on the set-ESEM confirm the importance of a principal's psychosocial risk factors; Stressors and depression were related to demands and ill-being, while confidence and autonomy were related to wellbeing. We also show that working in the private sector was beneficial for showing a low psychosocial risk, while other demographics have little effects. Finally, we identify five latent risk profiles (high risk to no risk) of school principals based on all psychosocial factors. Overall the research presented here closes the theory application gap of a strong multi-dimensional measure of psychosocial risk-factors.
Brazilian cross-cultural adaptation and validation of the List of Threatening Events Questionnaire (LTE-Q).

PubMed

Abreu, Patrícia B de; Cogo-Moreira, Hugo; Pose, Regina A; Laranjeira, Ronaldo; Caetano, Raul; Gaya, Carolina M; Madruga, Clarice S

2017-01-01

To perform a construct validation of the List of Threatening Events Questionnaire (LTE-Q), as well as convergence validation by identifying its association with drug use in a sample of the Brazilian population. This is a secondary analysis of the Second Brazilian National Alcohol and Drugs Survey (II BNADS), which used a cross-cultural adaptation of the LTE-Q in a probabilistic sample of 4,607 participants aged 14 years and older. Latent class analysis was used to validate the latent trait adversity (which considered the number of events from the list of 12 item in the LTE experienced by the respondent in the previous year) and logistic regression was performed to find its association with binge drinking and cocaine use. The confirmatory factor analysis returned a chi-square of 108.341, weighted root mean square residual (WRMR) of 1.240, confirmatory fit indices (CFI) of 0.970, Tucker-Lewis index (TLI) of 0.962, and root mean square error approximation (RMSEA) score of 1.000. LTE-Q convergence validation showed that the adversity latent trait increased the chances of binge drinking by 1.31 time and doubled the chances of previous year cocaine use (adjusted by sociodemographic variables). The use of the LTE-Q in Brazil should be encouraged in different research fields, including large epidemiological surveys, as it is also appropriate when time and budget are limited. The LTE-Q can be a useful tool in the development of targeted and more efficient prevention strategies.
Latent profile analysis of neuropsychological measures to determine preschoolers' risk for ADHD.

PubMed

Rajendran, Khushmand; O'Neill, Sarah; Marks, David J; Halperin, Jeffrey M

2015-09-01

Hyperactive/Inattentive preschool children show clear evidence of neuropsychological dysfunction. We examined whether patterns and severity of test scores could reliably identify subgroups of preschoolers with differential risk for ADHD during school-age. Typically developing (TD: n = 76) and Hyperactive/Inattentive (HI: n = 138) 3-4 year olds were assessed annually for 6 years (T1-T6). Latent profile analysis (LPA) was used to form subgroups among the HI group based on objective/neuropsychological measures (NEPSY, Actigraph and Continuous Performance Test). Logistic regression assessed the predictive validity of empirically formed subgroups at risk for ADHD diagnosis relative to the TD group and to each other from T2 to T6. Latent profile analysis yielded two subgroups of HI preschoolers: (a) selectively weak Attention/Executive functions, and (b) pervasive neuropsychological dysfunction across all measures. Both subgroups were more likely to have ADHD at all follow-up time-points relative to the TD group (OR range: 11.29-86.32), but there were no significant differences between the LPA-formed subgroups of HI children at any time-point. Objective/neuropsychological measures distinguish HI preschoolers from their TD peers, but patterns and severity of neuropsychological dysfunction do not predict risk for ADHD during school-age. We hypothesize that trajectories in at-risk children are influenced by subsequent environmental and neurodevelopmental factors, raising the possibility that they are amenable to early intervention. © 2015 Association for Child and Adolescent Mental Health.
A Latent Variable Investigation of the Phonological Awareness Literacy Screening-Kindergarten Assessment: Construct Identification and Multigroup Comparisons between Spanish-Speaking English-Language Learners (ELLs) and Non-ELL Students

ERIC Educational Resources Information Center

Huang, Francis L.; Konold, Timothy R.

2014-01-01

Psychometric properties of the Phonological Awareness Literacy Screening for Kindergarten (PALS-K) instrument were investigated in a sample of 2844 first-time public school kindergarteners. PALS-K is a widely used English literacy screening assessment. Exploratory factor analysis revealed a theoretically defensible measurement structure that was…
When Can Categorical Variables Be Treated as Continuous? A Comparison of Robust Continuous and Categorical SEM Estimation Methods under Suboptimal Conditions

ERIC Educational Resources Information Center

Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria

2012-01-01

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…
Characterizing Health Disparities in the Age of Autism Diagnosis in a Study of 8-Year-Old Children

ERIC Educational Resources Information Center

Parikh, Chandni; Kurzius-Spencer, Margaret; Mastergeorge, Ann M.; Pettygrove, Sydney

2018-01-01

The diagnosis of autism spectrum disorder (ASD) is often delayed from the time of noted concerns to the actual diagnosis. The current study used child- and family-level factors to identify homogeneous classes in a surveillance-based sample (n = 2303) of 8-year-old children with ASD. Using latent class analysis, a 5-class model emerged and the…
HIV-related sexual risk behavior among African American adolescent girls.

PubMed

Danielson, Carla Kmett; Walsh, Kate; McCauley, Jenna; Ruggiero, Kenneth J; Brown, Jennifer L; Sales, Jessica M; Rose, Eve; Wingood, Gina M; Diclemente, Ralph J

2014-05-01

Latent class analysis (LCA) is a useful statistical tool that can be used to enhance understanding of how various patterns of combined sexual behavior risk factors may confer differential levels of HIV infection risk and to identify subtypes among African American adolescent girls. Data for this analysis is derived from baseline assessments completed prior to randomization in an HIV prevention trial. Participants were African American girls (n=701) aged 14-20 years presenting to sexual health clinics. Girls completed an audio computer-assisted self-interview, which assessed a range of variables regarding sexual history and current and past sexual behavior. Two latent classes were identified with the probability statistics for the two groups in this model being 0.89 and 0.88, respectively. In the final multivariate model, class 1 (the "higher risk" group; n=331) was distinguished by a higher likelihood of >5 lifetime sexual partners, having sex while high on alcohol/drugs, less frequent condom use, and history of sexually transmitted diseases (STDs), when compared with class 2 (the "lower risk" group; n=370). The derived model correctly classified 85.3% of participants into the two groups and accounted for 71% of the variance in the latent HIV-related sexual behavior risk variable. The higher risk class also had worse scores on all hypothesized correlates (e.g., self-esteem, history of sexual assault or physical abuse) relative to the lower risk class. Sexual health clinics represent a unique point of access for HIV-related sexual risk behavior intervention delivery by capitalizing on contact with adolescent girls when they present for services. Four empirically supported risk factors differentiated higher versus lower HIV risk. Replication of these findings is warranted and may offer an empirical basis for parsimonious screening recommendations for girls presenting for sexual healthcare services.

Psychometric Properties of the Problematic Internet Use Questionnaire Short-Form (PIUQ-SF-6) in a Nationally Representative Sample of Adolescents.

PubMed

Demetrovics, Zsolt; Király, Orsolya; Koronczai, Beatrix; Griffiths, Mark D; Nagygyörgy, Katalin; Elekes, Zsuzsanna; Tamás, Domokos; Kun, Bernadette; Kökönyei, Gyöngyi; Urbán, Róbert

2016-01-01

Despite the large number of measurement tools developed to assess problematic Internet use, numerous studies use measures with only modest investigation into their psychometric properties. The goal of the present study was to validate the short (6-item) version of the Problematic Internet Use Questionnaire (PIUQ) on a nationally representative adolescent sample (n = 5,005; mean age 16.4 years, SD = 0.87) and to determine a statistically established cut-off value. Data were collected within the framework of the European School Survey Project on Alcohol and Other Drugs project. Results showed an acceptable fit of the original three-factor structure to the data. In addition, a MIMIC model was carried out to justify the need for three distinct factors. The sample was divided into users at-risk of problematic Internet use and those with no-risk using a latent profile analysis. Two latent classes were obtained with 14.4% of adolescents belonging to the at-risk group. Concurrent and convergent validity were tested by comparing the two groups across a number of variables (i.e., time spent online, academic achievement, self-esteem, depressive symptoms, and preferred online activities). Using the at-risk latent profile analysis class as the gold standard, a cut-off value of 15 (out of 30) was suggested based on sensitivity and specificity analyses. In conclusion, the brief version of the (6-item) PIUQ also appears to be an appropriate measure to differentiate between Internet users at risk of developing problematic Internet use and those not at risk. Furthermore, due to its brevity, the shortened PIUQ is advantageous to utilize within large-scale surveys assessing many different behaviors and/or constructs by reducing the overall number of survey questions, and as a consequence, likely increasing completion rates.
Do recognizable lifetime eating disorder phenotypes naturally occur in a culturally asian population? A combined latent profile and taxometric approach.

PubMed

Thomas, Jennifer J; Eddy, Kamryn T; Ruscio, John; Ng, King Lam; Casale, Kristen E; Becker, Anne E; Lee, Sing

2015-05-01

We examined whether empirically derived eating disorder (ED) categories in Hong Kong Chinese patients (N = 454) would be consistent with recognizable lifetime ED phenotypes derived from latent structure models of European and American samples. We performed latent profile analysis (LPA) using indicator variables from data collected during routine assessment, and then applied taxometric analysis to determine whether latent classes were qualitatively versus quantitatively distinct. Latent profile analysis identified four classes: (i) binge/purge (47%); (ii) non-fat-phobic low-weight (34%); (iii) fat-phobic low-weight (12%); and (iv) overweight disordered eating (6%). Taxometric analysis identified qualitative (categorical) distinctions between the binge/purge and non-fat-phobic low-weight classes, and also between the fat-phobic and non-fat-phobic low-weight classes. Distinctions between the fat-phobic low-weight and binge/purge classes were indeterminate. Empirically derived categories in Hong Kong showed recognizable correspondence with recognizable lifetime ED phenotypes. Although taxometric findings support two distinct classes of low weight EDs, LPA findings also support heterogeneity among non-fat-phobic individuals. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.
Using structural equation modeling for network meta-analysis.

PubMed

Tu, Yu-Kang; Wu, Yun-Chun

2017-07-14

Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison. SEM provides a very flexible framework for univariate and multivariate meta-analysis, and its potential as a powerful tool for advanced meta-analysis is still to be explored.
DNA Methylation Alterations Associated with Latent Carcinogenic Activity of Dichloroacetic Acid in Mice

EPA Science Inventory

Early-life environmental factors can influence later-life susceptibility to cancer. Epigenetic changes serve as promising biomarkers for these latent effects. Previously, we reported that short-term postnatal exposure to dichloroacetic acid (DCA), a byproduct of drinking water ch...
Systematic monitoring of male circumcision scale-up in Nyanza, Kenya: exploratory factor analysis of service quality instrument and performance ranking.

PubMed

Omondi Aduda, Dickens S; Ouma, Collins; Onyango, Rosebella; Onyango, Mathews; Bertrand, Jane

2014-01-01

Considerable conceptual and operational complexities related to service quality measurements and variability in delivery contexts of scaled-up medical male circumcision, pose real challenges to monitoring implementation of quality and safety. Clarifying latent factors of the quality instruments can enhance contextual applicability and the likelihood that observed service outcomes are appropriately assessed. To explore factors underlying SYMMACS service quality assessment tool (adopted from the WHO VMMC quality toolkit) and; determine service quality performance using composite quality index derived from the latent factors. Using a comparative process evaluation of Voluntary Medical Male Circumcision Scale-Up in Kenya site level data was collected among health facilities providing VMMC over two years. Systematic Monitoring of the Medical Male Circumcision Scale-Up quality instrument was used to assess availability of guidelines, supplies and equipment, infection control, and continuity of care services. Exploratory factor analysis was performed to clarify quality structure. Fifty four items and 246 responses were analyzed. Based on Eigenvalue >1.00 cut-off, factors 1, 2 & 3 were retained each respectively having eigenvalues of 5.78; 4.29; 2.99. These cumulatively accounted for 29.1% of the total variance (12.9%; 9.5%; 6.7%) with final communality estimates being 13.06. Using a cut-off factor loading value of ≥0.4, fifteen items loading on factor 1, five on factor 2 and one on factor 3 were retained. Factor 1 closely relates to preparedness to deliver safe male circumcisions while factor two depicts skilled task performance and compliance with protocols. Of the 28 facilities, 32% attained between 90th and 95th percentile (excellent); 45% between 50th and 75th percentiles (average) and 14.3% below 25th percentile (poor). the service quality assessment instrument may be simplified to have nearly 20 items that relate more closely to service outcomes. Ranking of facilities and circumcision procedure using a composite index based on these items indicates that majority performed above average.
What is the latent structure of alcohol use disorders? A taxometric analysis of the Personality Assessment Inventory Alcohol Problems Scale in male and female prison inmates.

PubMed

Walters, Glenn D; Diamond, Pamela M; Magaletta, Philip R

2010-03-01

Three indicators derived from the Personality Assessment Inventory (PAI) Alcohol Problems scale (ALC)-tolerance/high consumption, loss of control, and negative social and psychological consequences-were subjected to taxometric analysis-mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent mode factor analysis (L-Mode)-in 1,374 federal prison inmates (905 males, 469 females). Whereas the total sample yielded ambiguous results, the male subsample produced dimensional results, and the female subsample produced taxonic results. Interpreting these findings in light of previous taxometric research on alcohol abuse and dependence it is speculated that while alcohol use disorders may be taxonic in female offenders, they are probably both taxonic and dimensional in male offenders. Two models of male alcohol use disorder in males are considered, one in which the diagnostic features are categorical and the severity of symptomatology is dimensional, and one in which some diagnostic features (e.g., withdrawal) are taxonic and other features (e.g., social problems) are dimensional.
Changes in Classes of Injury-Related Risks and Consequences of Risk-Level Drinking: a Latent Transition Analysis.

PubMed

Cochran, Gerald; Field, Craig; Caetano, Raul

2015-07-01

Risk-level drinking, drinking and driving, and alcohol-related violence are risk factors that result in injuries. The current study sought to identify which subgroups of patients experience the most behavioral change following a brief intervention. A secondary analysis of data from a brief alcohol intervention study was conducted. The sample (N = 664) includes at-risk drinkers who experienced an injury and were admitted for care to a Level 1 trauma center. Injury-related items from the Short Inventory of Problems+6 were used to perform a latent transition analysis to describe class transitions participants experienced following discharge. Four classes emerged for the year before and after the current injury. Most individuals transitioned from higher-risk classes into those with lower risk. Some participants maintained risky profiles, and others increased risks and consequences. Drinking and driving remained a persistent problem among the study participants. Although a large portion of intervention recipients improved risks and consequences of alcohol use following discharge, more intensive intervention services may be needed for a subset of patients who showed little or no improvement.
Using Latent Class Analysis to Model Temperament Types.

PubMed

Loken, Eric

2004-10-01

Mixture models are appropriate for data that arise from a set of qualitatively different subpopulations. In this study, latent class analysis was applied to observational data from a laboratory assessment of infant temperament at four months of age. The EM algorithm was used to fit the models, and the Bayesian method of posterior predictive checks was used for model selection. Results show at least three types of infant temperament, with patterns consistent with those identified by previous researchers who classified the infants using a theoretically based system. Multiple imputation of group memberships is proposed as an alternative to assigning subjects to the latent class with maximum posterior probability in order to reflect variance due to uncertainty in the parameter estimation. Latent class membership at four months of age predicted longitudinal outcomes at four years of age. The example illustrates issues relevant to all mixture models, including estimation, multi-modality, model selection, and comparisons based on the latent group indicators.
Tuberculosis infection among homeless persons and caregivers in a high-tuberculosis-prevalence area in Japan: a cross-sectional study

PubMed Central

2011-01-01

Background Tuberculosis (TB) is a major public health problem. The Airin district of Osaka City has a large population of homeless persons and caregivers and is estimated to be the largest TB-endemic area in the intermediate-prevalence country, Japan. However, there have been few studies of homeless persons and caregivers. The objective of this study is to detect active TB and to assess the prevalence and risk factors for latent TB infection among homeless persons and caregivers. Methods We conducted a cross-sectional study for screening TB infection (active and latent TB infections) using questionnaire, chest X-ray (CXR), newly available assay for latent TB infection (QuantiFERON-TB Gold In-Tube; QFT) and clinical evaluation by physicians at the Osaka Socio-Medical Center Hospital between July 2007 and March 2008. Homeless persons and caregivers, aged 30-74 years old, who had not received CXR examination within one year, were recruited. As for risk factors of latent TB infection, the odds ratios (OR) and 95% confidence intervals (95% CI) for QFT-positivity were calculated using logistic regression model. Results Complete responses were available from 436 individuals (263 homeless persons and 173 caregivers). Four active TB cases (1.5%) among homeless persons were found, while there were no cases among caregivers. Out of these four, three had positive QFT results. One hundred and thirty-three (50.6%) homeless persons and 42 (24.3%) caregivers had positive QFT results. In multivariate analysis, QFT-positivity was independently associated with a long time spent in the Airin district: ≥10 years versus <10 years for homeless (OR = 2.53; 95% CI, 1.39-4.61) and for caregivers (OR = 2.32; 95% CI, 1.05-5.13), and the past exposure to TB patients for caregivers (OR = 3.21; 95% CI, 1.30-7.91) but not for homeless persons (OR = 1.51; 95% CI, 0.71-3.21). Conclusions Although no active TB was found for caregivers, one-quarter of them had latent TB infection. In addition to homeless persons, caregivers need examinations for latent TB infection as well as active TB and careful follow-up, especially when they have spent a long time in a TB-endemic area and/or have been exposed to TB patients. PMID:21255421
Measuring the foundations of school readiness: Introducing a new questionnaire for teachers - The Brief Early Skills and Support Index (BESSI).

PubMed

Hughes, Claire; Daly, Irenee; Foley, Sarah; White, Naomi; Devine, Rory T

2015-09-01

Early work on school readiness focused on academic skills. Recent research highlights the value of also including both children's social and behavioural competencies and family support. Reflecting this broader approach, this study aimed to develop a new and brief questionnaire for teachers: The Brief Early Skills and Support Index (BESSI). The main sample, recruited from the north-west of England, included 1,456 children (49% male), aged 2.5 to 5.5 years. A second sample consisting of 258 children (44% male) aged 3 to 5.5 years was recruited to assess the test-retest reliability of the BESSI across a 1-month interval. Following development and pilot work with early years teachers, a streamlined (30 items) version of the BESSI was sent to 98 teachers and nursery staff, who rated the children in their class. The best-fitting model included four latent factors: Three child factors (Behavioural Adjustment, Language and Cognition, and Daily Living Skills) and one Family Support factor. The three child factors exhibited measurement invariance across gender. All four factors showed good internal consistency and test-retest reliability. Structural equation modelling showed that (1) boys had more problems than girls on all three child factors; (2) older children showed better Language and Cognition and Daily Living Skills than younger children; and (3) children eligible for free school meals (an index of financial hardship) had more problems on all four latent factors. Family Support latent scores predicted all three child latent factors and accounted for their correlation with financial hardship. The BESSI is a promising brief teacher-report screening tool that appears suitable for children aged 2.5 to 5.5 and provides a broader perspective upon school readiness than previous measures. © 2015 The British Psychological Society.
A general class of multinomial mixture models for anuran calling survey data

USGS Publications Warehouse

Royle, J. Andrew; Link, W.A.

2005-01-01

We propose a general framework for modeling anuran abundance using data collected from commonly used calling surveys. The data generated from calling surveys are indices of calling intensity (vocalization of males) that do not have a precise link to actual population size and are sensitive to factors that influence anuran behavior. We formulate a model for calling-index data in terms of the maximum potential calling index that could be observed at a site (the 'latent abundance class'), given its underlying breeding population, and we focus attention on estimating the distribution of this latent abundance class. A critical consideration in estimating the latent structure is imperfect detection, which causes the observed abundance index to be less than or equal to the latent abundance class. We specify a multinomial sampling model for the observed abundance index that is conditional on the latent abundance class. Estimation of the latent abundance class distribution is based on the marginal likelihood of the index data, having integrated over the latent class distribution. We apply the proposed modeling framework to data collected as part of the North American Amphibian Monitoring Program (NAAMP).
Model specification in oral health-related quality of life research.

PubMed

Kieffer, Jacobien M; Verrips, Erik; Hoogstraten, Johan

2009-10-01

The aim of this study was to analyze conventional wisdom regarding the construction and analysis of oral health-related quality of life (OHRQoL) questionnaires and to outline statistical complications. Most methods used for developing and analyzing questionnaires, such as factor analysis and Cronbach's alpha, presume psychological constructs to be latent, inferring a reflective measurement model with the underlying assumption of local independence. Local independence implies that the latent variable explains why the variables observed are related. Many OHRQoL questionnaires are analyzed as if they were based on a reflective measurement model; local independence is thus assumed. This assumption requires these questionnaires to consist solely of items that reflect, instead of determine, OHRQoL. The tenability of this assumption is the main topic of the present study. It is argued that OHRQoL questionnaires are a mix of both a formative measurement model and a reflective measurement model, thus violating the assumption of local independence. The implications are discussed.
Obesogenic family types identified through latent profile analysis.

PubMed

Martinson, Brian C; VazquezBenitez, Gabriela; Patnode, Carrie D; Hearst, Mary O; Sherwood, Nancy E; Parker, Emily D; Sirard, John; Pasch, Keryn E; Lytle, Leslie

2011-10-01

Obesity may cluster in families due to shared physical and social environments. This study aims to identify family typologies of obesity risk based on family environments. Using 2007-2008 data from 706 parent/youth dyads in Minnesota, we applied latent profile analysis and general linear models to evaluate associations between family typologies and body mass index (BMI) of youth and parents. Three typologies described most families with 18.8% "Unenriched/Obesogenic," 16.9% "Risky Consumer," and 64.3% "Healthy Consumer/Salutogenic." After adjustment for demographic and socioeconomic factors, parent BMI and youth BMI Z-scores were higher in unenriched/obesogenic families (BMI difference = 2.7, p < 0.01 and BMI Z-score difference = 0.51, p < 0.01, respectively) relative to the healthy consumer/salutogenic typology. In contrast, parent BMI and youth BMI Z-scores were similar in the risky consumer families relative to those in healthy consumer/salutogenic type. We can identify family types differing in obesity risks with implications for public health interventions.
The development of socio-motivational dependency from early to middle adolescence

PubMed Central

Jagenow, Danilo; Raufelder, Diana; Eid, Michael

2015-01-01

Research on students’ motivation has shown that motivation can be enhanced or undermined by social factors. However, when interpreting such findings, interindividual differences, and intraindividual changes underlying students’ perception of peers and teachers as a source of motivation are often neglected. The aim of the present study was to complement our understanding of socio-motivational dependency by investigating differences in the development of students’ socio-motivational dependency from early to middle adolescence. Data from 1088 students on their perceptions of peers and teachers as positive motivators when students were in seventh and eighth grade were compared with data of the same sample 2 years later. Latent class analysis supported four different motivation types (MT): (1) teacher-dependent MT, (2) peer-dependent MT, (3) teacher-and-peer-dependent MT, and (4) teacher-and-peer-independent MT. Latent transition analysis revealed substantial changes between the groups. The perceived teacher influence on students’ academic motivation increased from early to middle adolescence. Divergent roles of peers and teachers on students’ academic motivation are discussed. PMID:25762966
The construct of sexual openness for females in steady intimate relationships.

PubMed

Rausch, Diana; Dekker, Arne; Rettenberger, Martin

2017-01-01

The analysis of open-minded attitudes towards sexuality in general requires a construct based on attitudinal dimensions. Although several existing studies involve sexual attitudes, they differ substantially and standardized conceptual work is missing. Thus, the authors introduce the latent variable sexual openness to develop a construct based on self-oriented attitudes towards different sexual topics. Available survey data of female German students in a steady relationship allowed providing a first empirical test for the applicability of this construct. Five subdimensions are acknowledged central for sexual openness: sexual practices, masturbation, bisexuality, permissiveness, and pornography consumption. Confirmatory factor analysis and correlations confirmed the idea of an underlying mechanism with an impact on all five variables. Though further validation of the construct of sexual openness is required, the findings strongly support the notion of an overarching latent attitude variable, which influences the individual relation to everything sexual. The results were compared to other studies and potential approaches for future analyses were proposed.
The construct of sexual openness for females in steady intimate relationships

PubMed Central

Rausch, Diana; Dekker, Arne; Rettenberger, Martin

2017-01-01

The analysis of open-minded attitudes towards sexuality in general requires a construct based on attitudinal dimensions. Although several existing studies involve sexual attitudes, they differ substantially and standardized conceptual work is missing. Thus, the authors introduce the latent variable sexual openness to develop a construct based on self-oriented attitudes towards different sexual topics. Available survey data of female German students in a steady relationship allowed providing a first empirical test for the applicability of this construct. Five subdimensions are acknowledged central for sexual openness: sexual practices, masturbation, bisexuality, permissiveness, and pornography consumption. Confirmatory factor analysis and correlations confirmed the idea of an underlying mechanism with an impact on all five variables. Though further validation of the construct of sexual openness is required, the findings strongly support the notion of an overarching latent attitude variable, which influences the individual relation to everything sexual. The results were compared to other studies and potential approaches for future analyses were proposed. PMID:28636608
Latent Profile and Cluster Analysis of Infant Temperament: Comparisons across Person-Centered Approaches

ERIC Educational Resources Information Center

Gartstein, Maria A.; Prokasky, Amanda; Bell, Martha Ann; Calkins, Susan; Bridgett, David J.; Braungart-Rieker, Julia; Leerkes, Esther; Cheatham, Carol L.; Eiden, Rina D.; Mize, Krystal D.; Jones, Nancy Aaron; Mireault, Gina; Seamon, Erich

2017-01-01

There is renewed interest in person-centered approaches to understanding the structure of temperament. However, questions concerning temperament types are not frequently framed in a developmental context, especially during infancy. In addition, the most common person-centered techniques, cluster analysis (CA) and latent profile analysis (LPA),…
Development of Fraction Comparison Strategies: A Latent Transition Analysis

ERIC Educational Resources Information Center

Rinne, Luke F.; Ye, Ai; Jordan, Nancy C.

2017-01-01

The present study investigated the development of fraction comparison strategies through a longitudinal analysis of children's responses to a fraction comparison task in 4th through 6th grades (N = 394). Participants were asked to choose the larger value for 24 fraction pairs blocked by fraction type. Latent class analysis of performance over item…
Public perception and attitude towards chemical industry park in Dalian, Bohai Rim.

PubMed

He, Guizhen; Chen, Chunci; Zhang, Lei; Lu, Yonglong

2018-04-01

Recent decade has witnessed accelerating expansion of chemical industry and increasing conflicts between the local citizens, governmental authorities and project developers, especially in some coastal and port cities in China. Development and transformation of chemical industrial parks has been adopted as a national initiative recently. However, there is a paucity of research examining public perspectives on chemical industrial parks and their risks. Aiming to understand public perception, attitude, and response and the factors underlying the support/acceptance of chemical industry park, this paper investigated 418 residents neighboring to two chemical industrial parks, Dalian in Bohai Rim through face-to-face questionnaire survey. The results showed the knowledge of the respondents on the chemical industrial parks development was very limited. The respondents had complex perceptions on the environmental impacts, risks control, social-economic benefits, and problem awareness. The current levels of information disclosure and public participation were very low. The central governmental official (44.3%) was the most trustworthy group by the respondents. Only 5.5% and 23.2% of the respondents supported the construction of a new CIP nearby and far away their homes, whilst 13% thought new CIP project as acceptable. The spearman correlation analysis results showed a strong NIMBY effect (Not In My Backyard). Factor analysis results demonstrated five latent factors: knowledge, benefit, information, trust, and participation. Multiple linear regression analysis indicated how socio-demographic differences and five latent factors might impact on the support/acceptance of the chemical industrial parks. Education level, trust, information, and participation were significant predictors of public support/acceptance level. This study contributes to our limited knowledge and understanding of public sentiments to the chemical industry parks in China. Copyright © 2017 Elsevier Ltd. All rights reserved.
Familial psychosocial risk classes and preschooler body mass index: The moderating effect of caregiver feeding style.

PubMed

Horodynski, Mildred A; Brophy-Herb, Holly E; Martoccio, Tiffany L; Contreras, Dawn; Peterson, Karen; Shattuck, Mackenzie; Senehi, Neda; Favreau, Zachary; Miller, Alison L; Sturza, Julie; Kaciroti, Niko; Lumeng, Julie C

2018-04-01

Early child weight gain predicts adolescent and adult obesity, underscoring the need to determine early risk factors affecting weight status and how risk factors might be mitigated. Socioeconomic status, food insecurity, caregiver depressive symptomology, single parenthood, and dysfunctional parenting each have been linked to early childhood weight status. However, the associations between these risk factors and children's weight status may be moderated by caregiver feeding styles (CFS). Examining modifiable factors buffering risk could provide key information to guide early obesity intervention efforts. This analysis used baseline data from the Growing Healthy project that recruited caregivers/child dyads (N = 626) from Michigan Head Start programs. Caregivers were primarily non-Hispanic white (62%) and African American (30%). After using latent class analysis to identify classes of familial psychosocial risk, CFS was tested as a moderator of the association between familial psychosocial risk class and child body mass index (BMI) z-score. Latent class analysis identified three familial psychosocial risk classes: (1) poor, food insecure and depressed families; (2) poor, single parent families; and (3) low risk families. Interactive effects for uninvolved feeding styles and risk group indicated that children in poor, food insecure, and depressed families had higher BMI z-scores compared to children in the low risk group. Authoritative feeding styles in low risk and poor, food insecure, and depressed families showed lower child BMI z-scores relative to poor, single parent families with authoritative feeding styles. Uninvolved feeding styles intensified the risk and an authoritative feeding style muted the risk conferred by living in a poor, food-insecure, and depressed family. Interventions that promote responsive feeding practices could help decrease the associations of familial psychosocial risks with early child weight outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development and preliminary validation of a post-fistula repair reintegration instrument among Ugandan women.

PubMed

El Ayadi, Alison; Nalubwama, Hadija; Barageine, Justus; Neilands, Torsten B; Obore, Susan; Byamugisha, Josaphat; Kakaire, Othman; Mwanje, Haruna; Korn, Abner; Lester, Felicia; Miller, Suellen

2017-09-02

Obstetric fistula is a debilitating and traumatic birth injury affecting 2-3 million women globally, mostly in sub-Saharan Africa and Asia. Affected women suffer physically, psychologically and socioeconomically. International efforts have increased access to surgical treatment, yet attention to a holistic outcome of post-surgical rehabilitation is nascent. We sought to develop and pilot test a measurement instrument to assess post-surgical family and community reintegration. We conducted an exploratory sequential mixed-methods study, beginning with 16 in-depth interviews and four focus group discussions with 17 women who underwent fistula surgery within two previous years to inform measure development. The draft instrument was validated in a longitudinal cohort of 60 women recovering from fistula surgery. Qualitative data were analyzed through thematic analysis. Socio-demographic characteristics were described using one-way frequency tables. We used exploratory factor analysis to determine the latent structure of the scale, then tested the fit of a single higher-order latent factor. We evaluated internal consistency and temporal stability reliability through Raykov's ρ and Pearson's correlation coefficient, respectively. We estimated a series of linear regression models to explore associations between the standardized reintegration measure and validated scales representing theoretically related constructs. Themes central to women's experiences following surgery included resuming mobility, increasing social interaction, improved self-esteem, reduction of internalized stigma, resuming work, meeting their own needs and the needs of dependents, meeting other expected and desired roles, and negotiating larger life issues. We expanded the Return to Normal Living Index to reflect these themes. Exploratory factor analysis suggested a four-factor structure, titled 'Mobility and social engagement', 'Meeting family needs', 'Comfort with relationships', and 'General life satisfaction', and goodness of fit statistics supported a higher-order latent variable of 'Reintegration.' Reintegration score correlated significantly with quality of life, depression, self-esteem, stigma, and social support in theoretically expected directions. As more women undergo surgical treatment for obstetric fistula, attention to the post-repair period is imperative. This preliminary validation of a reintegration instrument represents a first step toward improving measurement of post-surgical reintegration and has important implications for the evidence base of post-surgical reintegration epidemiology and the development and evaluation of fistula programming.
Latent Semantic Analysis.

ERIC Educational Resources Information Center

Dumais, Susan T.

2004-01-01

Presents a literature review that covers the following topics related to Latent Semantic Analysis (LSA): (1) LSA overview; (2) applications of LSA, including information retrieval (IR), information filtering, cross-language retrieval, and other IR-related LSA applications; (3) modeling human memory, including the relationship of LSA to other…
Differential factors associated with challenge-proven food allergy phenotypes in a population cohort of infants: a latent class analysis.

PubMed

Peters, R L; Allen, K J; Dharmage, S C; Lodge, C J; Koplin, J J; Ponsonby, A-L; Wake, M; Lowe, A J; Tang, M L K; Matheson, M C; Gurrin, L C

2015-05-01

Food allergy, eczema and wheeze are early manifestations of allergic disease and commonly co-occur in infancy although their interrelationship is not well understood. Data from population studies are essential to determine whether there are differential drivers of multi-allergy phenotypes. We aimed to define phenotypes and risk factors of allergic disease using latent class analysis (LCA). The HealthNuts study is a prospective, population-based cohort of 5276 12-month-old infants in Melbourne, Australia. LCA was performed using the following baseline data collected at age 12 months: food sensitization (skin prick test ≥ 2 mm) and allergy (oral food challenge) to egg, peanut and sesame; early (< 4 months) and late-onset eczema; and wheeze in the first year of life. Risk factors were modelled using multinomial logistic regression. Five distinct phenotypes were identified: no allergic disease (70%), non-food-sensitized eczema (16%), single egg allergy (9%), multiple food allergies (predominantly peanut) (3%) and multiple food allergies (predominantly egg) (2%). Compared to the baseline group of no allergic disease, shared risk factors for all allergic phenotypes were parents born overseas (particularly Asia), delayed introduction of egg, male gender (except for single egg allergy) and family history of allergic disease, whilst exposure to pet dogs was protective for all phenotypes. Other factors including filaggrin mutations, vitamin D and the presence of older siblings differed by phenotype. Multiple outcomes in infancy can be used to determine five distinct allergy phenotypes at the population level, which have both shared and separate risk factors suggesting differential mechanisms of disease. © 2014 John Wiley & Sons Ltd.
Assessing measurement error in surveys using latent class analysis: application to self-reported illicit drug use in data from the Iranian Mental Health Survey.

PubMed

Khalagi, Kazem; Mansournia, Mohammad Ali; Rahimi-Movaghar, Afarin; Nourijelyani, Keramat; Amin-Esmaeili, Masoumeh; Hajebi, Ahmad; Sharif, Vandad; Radgoodarzi, Reza; Hefazi, Mitra; Motevalian, Abbas

2016-01-01

Latent class analysis (LCA) is a method of assessing and correcting measurement error in surveys. The local independence assumption in LCA assumes that indicators are independent from each other condition on the latent variable. Violation of this assumption leads to unreliable results. We explored this issue by using LCA to estimate the prevalence of illicit drug use in the Iranian Mental Health Survey. The following three indicators were included in the LCA models: five or more instances of using any illicit drug in the past 12 months (indicator A), any use of any illicit drug in the past 12 months (indicator B), and the self-perceived need of treatment services or having received treatment for a substance use disorder in the past 12 months (indicator C). Gender was also used in all LCA models as a grouping variable. One LCA model using indicators A and B, as well as 10 different LCA models using indicators A, B, and C, were fitted to the data. The three models that had the best fit to the data included the following correlations between indicators: (AC and AB), (AC), and (AC, BC, and AB). The estimated prevalence of illicit drug use based on these three models was 28.9%, 6.2% and 42.2%, respectively. None of these models completely controlled for violation of the local independence assumption. In order to perform unbiased estimations using the LCA approach, the factors violating the local independence assumption (behaviorally correlated error, bivocality, and latent heterogeneity) should be completely taken into account in all models using well-known methods.
Are depression and frailty overlapping syndromes in mid- and late-life? A latent variable analysis.

PubMed

Mezuk, Briana; Lohman, Matthew; Dumenci, Levent; Lapane, Kate L

2013-06-01

Depression and frailty both predict disability and morbidity in later life. However, it is unclear to what extent these common geriatric syndromes represent overlapping constructs. To examine the joint relationship between the constructs of depression and frailty. Data come from 2004-2005 wave of the Baltimore Epidemiologic Catchment Area Study, and the analysis is limited to participants 40 years and older, with complete data on frailty and depression indicators (N = 683). Depression was measured using the Diagnostic Interview Schedule, and frailty was indexed by modified Fried criteria. A series of confirmatory latent class analyses were used to assess the degree to which depression and frailty syndromes identify the same populations. A latent kappa coefficient (κl) was also estimated between the constructs. Confirmatory latent class analyses indicated that depression and frailty represent distinct syndromes rather than a single construct. The joint modeling of the two constructs supported a three-class solution for depression and two-class solution for frailty, with 2.9% categorized as severely depressed, 19.4% as mildly depressed, and 77.7% as not depressed, and 21.1% categorized as frail and 78.9% as not frail. The chance-corrected agreement statistic indicated moderate correspondence between the depression and frailty constructs (κl: 66, 95% confidence interval: 0.58-0.74). Results suggest that depression and frailty are interrelated concepts, yet their operational criteria identify substantively overlapping subpopulations. These findings have implications for understanding factors that contribute to the etiology and prognosis of depression and frailty in later life. Copyright © 2013 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.
Application of Latent Class Analysis to Identify Behavioral Patterns of Response to Behavioral Lifestyle Interventions in Overweight and Obese Adults

PubMed Central

Fitzpatrick, Stephanie L.; Coughlin, Janelle W.; Appel, Lawrence J.; Tyson, Crystal; Stevens, Victor J.; Jerome, Gerald J.; Dalcin, Arlene; Brantley, Phillip J.; Hill-Briggs, Felicia

2016-01-01

Background Examining responders and non-responders to behavioral lifestyle interventions among overweight/obese adults with additional comorbidities may aid in refining and tailoring obesity treatment. Purpose The purpose of this study is to demonstrate the use of latent class analysis to identify patterns of response to behavioral lifestyle interventions based on adherence to diet and exercise recommendations. Method Repeated measures latent class analysis was applied to two clinical trial datasets, combination of two active interventions in the PREMIER Trial (n=501) and phase 1 of the Weight Loss Maintenance Trial (WLM; n=1685), to identify patterns of response to behavioral lifestyle interventions. Treatment response was based on adherence to daily recommendations for fruit/vegetable, fat, saturated fat, sodium, and exercise at baseline and 6 months. Results In PREMIER, three distinct latent classes emerged: responders (45.9 %), non-responders (23.6 %), and early adherers (30.5 %). Responders and Early Adherers had greater weight loss at 6 and 18 months and were more likely to meet behavioral recommendations at 18 months than Non-responders. For WLM, there were four latent classes: partial responders (16 %), non-responders (40 %), early adherers (2 %), and fruit/veggie only responders (41 %). Non-responders in WLM had significantly less weight loss at 6 months compared to that of the other three latent classes. Conclusion Latent class analysis is a useful method to apply to clinical trial data to identify distinct patterns of response to behavioral interventions. Overweight/ obese participants who respond to behavioral lifestyle treatment (i.e., meet behavioral recommendations) have significantly greater weight loss than that of participants who do not make behavioral changes. PMID:25331853
Application of Latent Class Analysis to Identify Behavioral Patterns of Response to Behavioral Lifestyle Interventions in Overweight and Obese Adults.

PubMed

Fitzpatrick, Stephanie L; Coughlin, Janelle W; Appel, Lawrence J; Tyson, Crystal; Stevens, Victor J; Jerome, Gerald J; Dalcin, Arlene; Brantley, Phillip J; Hill-Briggs, Felicia

2015-08-01

Examining responders and non-responders to behavioral lifestyle interventions among overweight/obese adults with additional comorbidities may aid in refining and tailoring obesity treatment. The purpose of this study is to demonstrate the use of latent class analysis to identify patterns of response to behavioral lifestyle interventions based on adherence to diet and exercise recommendations. Repeated measures latent class analysis was applied to two clinical trial datasets, combination of two active interventions in the PREMIER Trial (n = 501) and phase 1 of the Weight Loss Maintenance Trial (WLM; n = 1685), to identify patterns of response to behavioral lifestyle interventions. Treatment response was based on adherence to daily recommendations for fruit/vegetable, fat, saturated fat, sodium, and exercise at baseline and 6 months. In PREMIER, three distinct latent classes emerged: responders (45.9%), non-responders (23.6%), and early adherers (30.5%). Responders and Early Adherers had greater weight loss at 6 and 18 months and were more likely to meet behavioral recommendations at 18 months than Non-responders. For WLM, there were four latent classes: partial responders (16%), non-responders (40%), early adherers (2%), and fruit/veggie only responders (41%). Non-responders in WLM had significantly less weight loss at 6 months compared to that of the other three latent classes. Latent class analysis is a useful method to apply to clinical trial data to identify distinct patterns of response to behavioral interventions. Overweight/ obese participants who respond to behavioral lifestyle treatment (i.e., meet behavioral recommendations) have significantly greater weight loss than that of participants who do not make behavioral changes.
A Latent Class Regression Analysis of Men's Conformity to Masculine Norms and Psychological Distress

ERIC Educational Resources Information Center

Wong, Y. Joel; Owen, Jesse; Shea, Munyi

2012-01-01

How are specific dimensions of masculinity related to psychological distress in specific groups of men? To address this question, the authors used latent class regression to assess the optimal number of latent classes that explained differential relationships between conformity to masculine norms and psychological distress in a racially diverse…
Visualizing Confidence Bands for Semiparametrically Estimated Nonlinear Relations among Latent Variables

ERIC Educational Resources Information Center

Pek, Jolynn; Chalmers, R. Philip; Kok, Bethany E.; Losardo, Diane

2015-01-01

Structural equation mixture models (SEMMs), when applied as a semiparametric model (SPM), can adequately recover potentially nonlinear latent relationships without their specification. This SPM is useful for exploratory analysis when the form of the latent regression is unknown. The purpose of this article is to help users familiar with structural…
Mixture Distribution Latent State-Trait Analysis: Basic Ideas and Applications

ERIC Educational Resources Information Center

Courvoisier, Delphine S.; Eid, Michael; Nussbeck, Fridtjof W.

2007-01-01

Extensions of latent state-trait models for continuous observed variables to mixture latent state-trait models with and without covariates of change are presented that can separate individuals differing in their occasion-specific variability. An empirical application to the repeated measurement of mood states (N = 501) revealed that a model with 2…
Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

PubMed

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity. Copyright © 2017 Elsevier Inc. All rights reserved.
Cellular Transcription Factors Induced in Trigeminal Ganglia during Dexamethasone-Induced Reactivation from Latency Stimulate Bovine Herpesvirus 1 Productive Infection and Certain Viral Promoters

PubMed Central

Workman, Aspen; Eudy, James; Smith, Lynette; Frizzo da Silva, Leticia; Sinani, Devis; Bricker, Halie; Cook, Emily; Doster, Alan

2012-01-01

Bovine herpesvirus 1 (BHV-1), an alphaherpesvirinae subfamily member, establishes latency in sensory neurons. Elevated corticosteroid levels, due to stress, reproducibly triggers reactivation from latency in the field. A single intravenous injection of the synthetic corticosteroid dexamethasone (DEX) to latently infected calves consistently induces reactivation from latency. Lytic cycle viral gene expression is detected in sensory neurons within 6 h after DEX treatment of latently infected calves. These observations suggested that DEX stimulated expression of cellular genes leads to lytic cycle viral gene expression and productive infection. In this study, a commercially available assay—Bovine Gene Chip—was used to compare cellular gene expression in the trigeminal ganglia (TG) of calves latently infected with BHV-1 versus DEX-treated animals. Relative to TG prepared from latently infected calves, 11 cellular genes were induced more than 10-fold 3 h after DEX treatment. Pentraxin three, a regulator of innate immunity and neurodegeneration, was stimulated 35- to 63-fold after 3 or 6 h of DEX treatment. Two transcription factors, promyelocytic leukemia zinc finger (PLZF) and Slug were induced more than 15-fold 3 h after DEX treatment. PLZF or Slug stimulated productive infection 20- or 5-fold, respectively, and Slug stimulated the late glycoprotein C promoter more than 10-fold. Additional DEX-induced transcription factors also stimulated productive infection and certain viral promoters. These studies suggest that DEX-inducible cellular transcription factors and/or signaling pathways stimulate lytic cycle viral gene expression, which subsequently leads to successful reactivation from latency in a small subset of latently infected neurons. PMID:22190728
Predicting language outcomes for children learning AAC: Child and environmental factors

PubMed Central

Brady, Nancy C.; Thiemann-Bourque, Kathy; Fleming, Kandace; Matthews, Kris

2014-01-01

Purpose To investigate a model of language development for nonverbal preschool age children learning to communicate with AAC. Method Ninety-three preschool children with intellectual disabilities were assessed at Time 1, and 82 of these children were assessed one year later at Time 2. The outcome variable was the number of different words the children produced (with speech, sign or SGD). Children’s intrinsic predictor for language was modeled as a latent variable consisting of cognitive development, comprehension, play, and nonverbal communication complexity. Adult input at school and home, and amount of AAC instruction were proposed mediators of vocabulary acquisition. Results A confirmatory factor analysis revealed that measures converged as a coherent construct and an SEM model indicated that the intrinsic child predictor construct predicted different words children produced. The amount of input received at home but not at school was a significant mediator. Conclusions Our hypothesized model accurately reflected a latent construct of Intrinsic Symbolic Factor (ISF). Children who evidenced higher initial levels of ISF and more adult input at home produced more words one year later. Findings support the need to assess multiple child variables, and suggest interventions directed to the indicators of ISF and input. PMID:23785187
Utility of an interferon-gamma release assay for latent tuberculosis diagnosis in a case of bullous pemphigoid.

PubMed

Goodfellow, Alfred; Keeling, Douglas N; Hayes, Robert C; Webster, Duncan

2009-01-01

With increasing use of immunosuppressive therapy, including tumor necrosis factor alpha inhibitors, there is concern about infectious complications, including reactivation of latent Mycobacterium tuberculosis infection. Routine testing prior to administration of systemic immunosuppression includes the tuberculin skin test, which lacks sensitivity and specificity and may be difficult to interpret in the presence of extensive cutaneous disease. Treatment of individuals with latent tuberculosis infection is recommended when immunosuppressive medications are to be employed. We report a case in which a diagnosis of latent tuberculosis infection in a patient with extensive bullous pemphigoid was clarified by the use of an interferon-gamma release assay after equivocal tuberculin skin test results. Interferon-gamma release assays are useful adjuncts to the tuberculin skin test in the diagnosis of latent tuberculosis infection in the setting of extensive cutaneous disease.
Investigating Subtypes of Child Development: A Comparison of Cluster Analysis and Latent Class Cluster Analysis in Typology Creation

ERIC Educational Resources Information Center

DiStefano, Christine; Kamphaus, R. W.

2006-01-01

Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures…
Elevated fetal steroidogenic activity in autism.

PubMed

Baron-Cohen, S; Auyeung, B; Nørgaard-Pedersen, B; Hougaard, D M; Abdallah, M W; Melgaard, L; Cohen, A S; Chakrabarti, B; Ruta, L; Lombardo, M V

2015-03-01

Autism affects males more than females, giving rise to the idea that the influence of steroid hormones on early fetal brain development may be one important early biological risk factor. Utilizing the Danish Historic Birth Cohort and Danish Psychiatric Central Register, we identified all amniotic fluid samples of males born between 1993 and 1999 who later received ICD-10 (International Classification of Diseases, 10th Revision) diagnoses of autism, Asperger syndrome or PDD-NOS (pervasive developmental disorder not otherwise specified) (n=128) compared with matched typically developing controls. Concentration levels of Δ4 sex steroids (progesterone, 17α-hydroxy-progesterone, androstenedione and testosterone) and cortisol were measured with liquid chromatography tandem mass spectrometry. All hormones were positively associated with each other and principal component analysis confirmed that one generalized latent steroidogenic factor was driving much of the variation in the data. The autism group showed elevations across all hormones on this latent generalized steroidogenic factor (Cohen's d=0.37, P=0.0009) and this elevation was uniform across ICD-10 diagnostic label. These results provide the first direct evidence of elevated fetal steroidogenic activity in autism. Such elevations may be important as epigenetic fetal programming mechanisms and may interact with other important pathophysiological factors in autism.
Elevated fetal steroidogenic activity in autism

PubMed Central

Baron-Cohen, S; Auyeung, B; Nørgaard-Pedersen, B; Hougaard, D M; Abdallah, M W; Melgaard, L; Cohen, A S; Chakrabarti, B; Ruta, L; Lombardo, M V

2015-01-01

Autism affects males more than females, giving rise to the idea that the influence of steroid hormones on early fetal brain development may be one important early biological risk factor. Utilizing the Danish Historic Birth Cohort and Danish Psychiatric Central Register, we identified all amniotic fluid samples of males born between 1993 and 1999 who later received ICD-10 (International Classification of Diseases, 10th Revision) diagnoses of autism, Asperger syndrome or PDD-NOS (pervasive developmental disorder not otherwise specified) (n=128) compared with matched typically developing controls. Concentration levels of Δ4 sex steroids (progesterone, 17α-hydroxy-progesterone, androstenedione and testosterone) and cortisol were measured with liquid chromatography tandem mass spectrometry. All hormones were positively associated with each other and principal component analysis confirmed that one generalized latent steroidogenic factor was driving much of the variation in the data. The autism group showed elevations across all hormones on this latent generalized steroidogenic factor (Cohen's d=0.37, P=0.0009) and this elevation was uniform across ICD-10 diagnostic label. These results provide the first direct evidence of elevated fetal steroidogenic activity in autism. Such elevations may be important as epigenetic fetal programming mechanisms and may interact with other important pathophysiological factors in autism. PMID:24888361
Tenascin-X promotes epithelial-to-mesenchymal transition by activating latent TGF-β

PubMed Central

Alcaraz, Lindsay B.; Exposito, Jean-Yves; Chuvin, Nicolas; Pommier, Roxane M.; Cluzel, Caroline; Martel, Sylvie; Sentis, Stéphanie; Bartholin, Laurent; Lethias, Claire

2014-01-01

Transforming growth factor β (TGF-β) isoforms are secreted as inactive complexes formed through noncovalent interactions between the bioactive TGF-β entity and its N-terminal latency-associated peptide prodomain. Extracellular activation of the latent TGF-β complex is a crucial step in the regulation of TGF-β function for tissue homeostasis. We show that the fibrinogen-like (FBG) domain of the matrix glycoprotein tenascin-X (TNX) interacts physically with the small latent TGF-β complex in vitro and in vivo, thus regulating the bioavailability of mature TGF-β to cells by activating the latent cytokine into an active molecule. Activation by the FBG domain most likely occurs through a conformational change in the latent complex and involves a novel cell adhesion–dependent mechanism. We identify α11β1 integrin as a cell surface receptor for TNX and show that this integrin is crucial to elicit FBG-mediated activation of latent TGF-β and subsequent epithelial-to-mesenchymal transition in mammary epithelial cells. PMID:24821840
A Framework for Estimating Causal Effects in Latent Class Analysis: Is There a Causal Link Between Early Sex and Subsequent Profiles of Delinquency?

PubMed Central

Lanza, Stephanie T.; Coffman, Donna L.

2013-01-01

Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p=0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p=0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work. PMID:23839479
A framework for estimating causal effects in latent class analysis: is there a causal link between early sex and subsequent profiles of delinquency?

PubMed

Butera, Nicole M; Lanza, Stephanie T; Coffman, Donna L

2014-06-01

Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p = 0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p = 0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work.

Defect-Repairable Latent Feature Extraction of Driving Behavior via a Deep Sparse Autoencoder

PubMed Central

Taniguchi, Tadahiro; Takenaka, Kazuhito; Bando, Takashi

2018-01-01

Data representing driving behavior, as measured by various sensors installed in a vehicle, are collected as multi-dimensional sensor time-series data. These data often include redundant information, e.g., both the speed of wheels and the engine speed represent the velocity of the vehicle. Redundant information can be expected to complicate the data analysis, e.g., more factors need to be analyzed; even varying the levels of redundancy can influence the results of the analysis. We assume that the measured multi-dimensional sensor time-series data of driving behavior are generated from low-dimensional data shared by the many types of one-dimensional data of which multi-dimensional time-series data are composed. Meanwhile, sensor time-series data may be defective because of sensor failure. Therefore, another important function is to reduce the negative effect of defective data when extracting low-dimensional time-series data. This study proposes a defect-repairable feature extraction method based on a deep sparse autoencoder (DSAE) to extract low-dimensional time-series data. In the experiments, we show that DSAE provides high-performance latent feature extraction for driving behavior, even for defective sensor time-series data. In addition, we show that the negative effect of defects on the driving behavior segmentation task could be reduced using the latent features extracted by DSAE. PMID:29462931
Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

PubMed

Han, Fang; Liu, Han

2017-02-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.
A Three-Step Latent Class Analysis to Identify How Different Patterns of Teen Dating Violence and Psychosocial Factors Influence Mental Health.

PubMed

Choi, Hye Jeong; Weston, Rebecca; Temple, Jeff R

2017-04-01

Although multiple forms (i.e., physical, threatening, psychological, sexual, and relational abuse) and patterns (i.e., perpetration and victimization) of violence can co-occur, most existing research examines these experiences individually. Thus, the purpose of this study is to investigate: (1) homogenous subgroups based on victimization and perpetration of multiple forms of teen dating violence; (2) predictors of membership in these subgroups; and (3) mental health consequences associated with membership in each subgroup. Nine hundred eighteen adolescents in the 9 th or 10 th grade at seven public high schools in Texas participated in the survey (56 % female, White: 30 %, Hispanic: 32 %, African American: 29 %, others: 9 %). A three-step latent class analysis was employed. Five latent teen dating violence classes were identified: (1) nonviolence; (2) emotional/verbal abuse; (3) forced sexual contact; (4) psychological + physical violence; and (5) psychological abuse. Females, African Americans, and youth who had higher acceptance of couple violence scores and whose parents had less education were more likely to members of dating violence classes compared with the nonviolence class. Adolescents who experienced multiple types of dating violence reported greater mental health concerns. Prevention programs may benefit by identifying the homogenous subgroups of teen dating violence and targeting adolescent teen dating violence accordingly.
Evaluating Mixture Modeling for Clustering: Recommendations and Cautions

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2011-01-01

This article provides a large-scale investigation into several of the properties of mixture-model clustering techniques (also referred to as latent class cluster analysis, latent profile analysis, model-based clustering, probabilistic clustering, Bayesian classification, unsupervised learning, and finite mixture models; see Vermunt & Magdison,…
The Role of Religiousness/Spirituality in Health-Related Quality of Life Among Adolescents with HIV: A Latent Profile Analysis

PubMed Central

Kimmel, Allison L.; Cheng, Yao Iris; Wang, Jichuan

2016-01-01

The purpose of this study was to determine whether distinct latent profiles of religiousness/spirituality exist for ALWH, and if so, are latent profile memberships associated with health-related quality of life (HRQoL). Latent profile analysis of religiosity identified four profiles/groups. Compared to the other three groups, higher levels of emotional well-being were found among young perinatally infected adolescents who attended religious services, but who did not pray privately, feel God's presence or identify as religious or spiritual. Social HRQoL was significantly higher among the highest overall religious/spiritual group. Understanding adolescent profiles of religiousness/spirituality on HRQoL could inform faith-based interventions. PMID:27071797
The Role of Religiousness/Spirituality in Health-Related Quality of Life Among Adolescents with HIV: A Latent Profile Analysis.

PubMed

Lyon, Maureen E; Kimmel, Allison L; Cheng, Yao Iris; Wang, Jichuan

2016-10-01

The purpose of this study was to determine whether distinct latent profiles of religiousness/spirituality exist for ALWH, and if so, are latent profile memberships associated with health-related quality of life (HRQoL). Latent profile analysis of religiosity identified four profiles/groups. Compared to the other three groups, higher levels of emotional well-being were found among young perinatally infected adolescents who attended religious services, but who did not pray privately, feel God's presence or identify as religious or spiritual. Social HRQoL was significantly higher among the highest overall religious/spiritual group. Understanding adolescent profiles of religiousness/spirituality on HRQoL could inform faith-based interventions. Trial registration NCT01289444.
Students' proficiency scores within multitrait item response theory

NASA Astrophysics Data System (ADS)

Scott, Terry F.; Schumayer, Daniel

2015-12-01

In this paper we present a series of item response models of data collected using the Force Concept Inventory. The Force Concept Inventory (FCI) was designed to poll the Newtonian conception of force viewed as a multidimensional concept, that is, as a complex of distinguishable conceptual dimensions. Several previous studies have developed single-trait item response models of FCI data; however, we feel that multidimensional models are also appropriate given the explicitly multidimensional design of the inventory. The models employed in the research reported here vary in both the number of fitting parameters and the number of underlying latent traits assumed. We calculate several model information statistics to ensure adequate model fit and to determine which of the models provides the optimal balance of information and parsimony. Our analysis indicates that all item response models tested, from the single-trait Rasch model through to a model with ten latent traits, satisfy the standard requirements of fit. However, analysis of model information criteria indicates that the five-trait model is optimal. We note that an earlier factor analysis of the same FCI data also led to a five-factor model. Furthermore the factors in our previous study and the traits identified in the current work match each other well. The optimal five-trait model assigns proficiency scores to all respondents for each of the five traits. We construct a correlation matrix between the proficiencies in each of these traits. This correlation matrix shows strong correlations between some proficiencies, and strong anticorrelations between others. We present an interpretation of this correlation matrix.
Working Memory Tasks Differ in Factor Structure across Age Cohorts: Implications for Dedifferentiation

ERIC Educational Resources Information Center

Johnson, Wendy; Logie, Robert H.; Brockmole, James R.

2010-01-01

Researchers interested in working memory have debated whether it should be considered a single latent cognitive ability or a set of essentially independent latent abilities distinguished by domain-specific memory and/or processing resources. Simultaneously, researchers interested in cognitive aging have established that there are substantial…
Examining the integrity of measurement of cognitive abilities in the prediction of achievement: Comparisons and contrasts across variables from higher-order and bifactor models.

PubMed

Benson, Nicholas F; Kranzler, John H; Floyd, Randy G

2016-10-01

Prior research examining cognitive ability and academic achievement relations have been based on different theoretical models, have employed both latent variables as well as observed variables, and have used a variety of analytic methods. Not surprisingly, results have been inconsistent across studies. The aims of this study were to (a) examine how relations between psychometric g, Cattell-Horn-Carroll (CHC) broad abilities, and academic achievement differ across higher-order and bifactor models; (b) examine how well various types of observed scores corresponded with latent variables; and (c) compare two types of observed scores (i.e., refined and non-refined factor scores) as predictors of academic achievement. Results suggest that cognitive-achievement relations vary across theoretical models and that both types of factor scores tend to correspond well with the models on which they are based. However, orthogonal refined factor scores (derived from a bifactor model) have the advantage of controlling for multicollinearity arising from the measurement of psychometric g across all measures of cognitive abilities. Results indicate that the refined factor scores provide more precise representations of their targeted constructs than non-refined factor scores and maintain close correspondence with the cognitive-achievement relations observed for latent variables. Thus, we argue that orthogonal refined factor scores provide more accurate representations of the relations between CHC broad abilities and achievement outcomes than non-refined scores do. Further, the use of refined factor scores addresses calls for the application of scores based on latent variable models. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
Latent myostatin has significant activity and this activity is controlled more efficiently by WFIKKN1 than by WFIKKN2

PubMed Central

Szláma, György; Trexler, Mária; Patthy, László

2013-01-01

Myostatin, a negative regulator of skeletal muscle growth, is produced from myostatin precursor by multiple steps of proteolytic processing. After cleavage by a furin-type protease, the propeptide and growth factor domains remain associated, forming a noncovalent complex, the latent myostatin complex. Mature myostatin is liberated from latent myostatin by bone morphogenetic protein 1/tolloid proteases. Here, we show that, in reporter assays, latent myostatin preparations have significant myostatin activity, as the noncovalent complex dissociates at an appreciable rate, and both mature and semilatent myostatin (a complex in which the dimeric growth factor domain interacts with only one molecule of myostatin propeptide) bind to myostatin receptor. The interaction of myostatin receptor with semilatent myostatin is efficiently blocked by WAP, Kazal, immunoglobulin, Kunitz and NTR domain-containing protein 1 or growth and differentiation factor-associated serum protein 2 (WFIKKN1), a large extracellular multidomain protein that binds both mature myostatin and myostatin propeptide [Kondás et al. (2008) J Biol Chem 283, 23677–23684]. Interestingly, the paralogous protein WAP, Kazal, immunoglobulin, Kunitz and NTR domain-containing protein 2 or growth and differentiation factor-associated serum protein 1 (WFIKKN2) was less efficient than WFIKKN1 as an antagonist of the interactions of myostatin receptor with semilatent myostatin. Our studies have shown that this difference is attributable to the fact that only WFIKKN1 has affinity for the propeptide domain, and this interaction increases its potency in suppressing the receptor-binding activity of semilatent myostatin. As the interaction of WFIKKN1 with various forms of myostatin permits tighter control of myostatin activity until myostatin is liberated from latent myostatin by bone morphogenetic protein 1/tolloid proteases, WFIKKN1 may have greater potential as an antimyostatic agent than WFIKKN2. Structured digital abstract Furin cleaves Promyostatin by protease assay (View interaction) myostatin binds to PRO by surface plasmon resonance (View interaction) BMP-1 cleaves Promyostatin by protease assay (View interaction) ACR IIB physically interacts with Latent Myostatin by surface plasmon resonance (View interaction) Promyostatin and Promyostatin bind by comigration in gel electrophoresis (View interaction) WFIKKN1 binds to Latent Myostatin by pull down (View interaction) ACR IIB binds to Mature Myostatin by surface plasmon resonance (View Interaction: 1, 2, 3) WFIKKN1 binds to Myostatin Prodomain by surface plasmon resonance (View Interaction: 1, 2, 3) PMID:23829672
Examining Combinations of Social Physique Anxiety and Motivation Regulations Using Latent Profile Analysis

ERIC Educational Resources Information Center

Ullrich-French, Sarah; Cox, Anne E.; Cooper, Brittany Rhoades

2016-01-01

Previous research has used cluster analysis to examine how social physique anxiety (SPA) combines with motivation in physical education. This study utilized a more advanced analytic approach, latent profile analysis (LPA), to identify profiles of SPA and motivation regulations. Students in grades 9-12 (N = 298) completed questionnaires at two time…
Community violence, protective factors, and adolescent mental health: a profile analysis.

PubMed

Copeland-Linder, Nikeea; Lambert, Sharon F; Ialongo, Nicholas S

2010-01-01

This study examined interrelationships among community violence exposure, protective factors, and mental health in a sample of urban, predominantly African American adolescents (N = 504). Latent Profile Analysis was conducted to identify profiles of adolescents based on a combination of community violence exposure, self-worth, parental monitoring, and parental involvement and to examine whether these profiles differentially predict adolescents' depressive symptoms and aggressive behavior. Three classes were identified-a vulnerable class, a moderate risk/medium protection class, and a moderate risk/high protection class. The classes differentially predicted depressive symptoms but not aggressive behavior for boys and girls. The class with the highest community violence exposure also had the lowest self-worth.
Bayesian latent structure modeling of walking behavior in a physical activity intervention

PubMed Central

Lawson, Andrew B; Ellerbe, Caitlyn; Carroll, Rachel; Alia, Kassandra; Coulon, Sandra; Wilson, Dawn K; VanHorn, M Lee; St George, Sara M

2017-01-01

The analysis of walking behavior in a physical activity intervention is considered. A Bayesian latent structure modeling approach is proposed whereby the ability and willingness of participants is modeled via latent effects. The dropout process is jointly modeled via a linked survival model. Computational issues are addressed via posterior sampling and a simulated evaluation of the longitudinal model’s ability to recover latent structure and predictor effects is considered. We evaluate the effect of a variety of socio-psychological and spatial neighborhood predictors on the propensity to walk and the estimation of latent ability and willingness in the full study. PMID:24741000
Brief Report: Development of the Family Perceptions Scale; a Novel Instrument for Evaluating Subjective Functioning in the Families of Adolescents

ERIC Educational Resources Information Center

Tiffin, Paul A.; Kaplan, Carole; Place, Maurice

2011-01-01

A pool of 75 items relating to family functioning was created and piloted in a sample of 12-18 year olds (N = 673). The responses were subjected to an exploratory factor analysis which indicated the presence of three significant latent traits. The results were then used to inform the development of a rating instrument with five subscales labelled…
A latent class analysis of substance use and culture among gay, bisexual and other men who have sex with men.

PubMed

Card, Kiffer G; Armstrong, Heather L; Carter, Allison; Cui, Zishan; Wang, Lu; Zhu, Julia; Lachowsky, Nathan J; Moore, David M; Hogg, Robert S; Roth, Eric A

2018-03-28

Assessments of gay and bisexual men's substance use often obscures salient sociocultural and identity-related experiences related to how they use drugs. Latent class analysis was used to examine how patterns of substance use represent the social, economic and identity-related experiences of this population. Participants were sexually active gay and bisexual men (including other men who have sex with men), aged ≥ 16 years, living in Metro Vancouver (n = 774). LCA indicators included all substances used in the past six months self-reported by more than 30 men. Model selection was made with consideration to model parsimony, interpretability and optimisation of statistical criteria. Multinomial regression identified factors associated with class membership. A six-class solution was identified representing: 'assorted drug use' (4.5%); 'club drug use' (9.5%); 'street drug use' (12.1%); 'sex drug use' (11.4%); 'conventional drug use' (i.e. tobacco, alcohol, marijuana; 25.9%); and 'limited drug use' (36.7%). Factors associated with class membership included age, sexual orientation, annual income, occupation, income from drug sales, housing stability, group sex event participation, gay bars/clubs attendance, sensation seeking and escape motivation. These results highlight the need for programmes and policies that seek to lessen social disparities and account for social distinctions among this population.
Dual skin tests with Mycobacterium avium sensitin and PPD to detect misdiagnosis of latent tuberculosis infection.

PubMed

Larson, E M; O'Donnell, M; Chamblee, S; Horsburgh, C R; Marsh, B J; Moreland, J D; Johnson, L S; von Reyn, C Fordham

2011-11-01

A positive tuberculin skin test (TST) may indicate cross-reacting immunity to non-tuberculous mycobacteria (NTM) and not latent tuberculosis infection (LTBI). To assess misclassification of LTBI, as assessed by skin testing with Mycobacterium avium sensitin (MaS), and to determine how this misclassification affects the analysis of risk factors for LTBI. In a population-based survey, participants underwent skin testing with M. tuberculosis purified protein derivative (PPD) and MaS. A PPD-dominant skin test was a reaction that was ≥ 3 mm larger than the MaS reaction; a MaS-dominant skin test was a reaction that was ≥ 3 mm larger than the PPD reaction. Of 447 randomly selected persons, 135 (30%) had a positive PPD test. Of these, 21 (16%) were MaS- dominant, and were therefore attributable to NTM and misclassified as LTBI. PPD reactions of 5-14 mm were more likely to be misclassified than those ≥ 15 mm (OR = 5.0, 95%CI 1.9-13.2). Adjusting for misclassification had only a small impact on the analysis of risk factors for LTBI. A substantial number of individuals who are diagnosed with LTBI are actually sensitized to NTM. Using dual skin testing would reduce misdiagnosis and prevent unnecessary treatment.
Do Specific Transitional Patterns of Antisocial Behavior during Adolescence Increase Risk for Problems in Young Adulthood?

PubMed Central

Cook, Emily C.; Pflieger, Jacqueline C.; Connell, Arin M.; Connell, Christian M.

2014-01-01

Latent transition analysis was used to identify patterns and trajectories of antisocial behavior (ASB) and their association with young adult outcomes in a nationally representative sample of adolescents (N = 5,422; 53.9% female). Participants were on average 13.96 years of age (SD= 1.06) at wave 1 of the study. Latent class analysis identified four classes of ASB including a non-ASB class, an aggressive class, a petty theft class, and a serious ASB class. In general, youth who were classified as serious stable ASB were the most at risk for problematic functioning in young adulthood. Youth who escalated to more serious patterns of ASB or reduced involvement also were at greater risk of negative outcomes in young adulthood compared to stable non-ASB youth, although they generally fared better than youth involved in stable patterns of more serious ASB. Gender differences indicated that involvement in ASB was a greater risk factor for alcohol use among boys and a greater risk factor for depression among girls in young adulthood. Results are discussed in terms of the predictive validity of classes of ASB to functioning in young adulthood and the implications of this research for prevention efforts. PMID:24893667
Role of resilient personality on lower achieving first grade students' current and future achievement

PubMed Central

Kwok, Oi-man; Hughes, Jan N.; Luo, Wen

2007-01-01

This study investigated a measurement model of personality resilience and the contribution of personality resilience to lower achieving first grade students' academic achievement. Participants were 445 ethnically diverse children who at entrance to first grade scored below their school district median on a test of literacy. Participants were administered an individual achievement test in first grade and 1 year later. Confirmatory factor analysis confirmed a second-order latent construct of resilient personality defined by teacher-rated conscientiousness, agreeableness, and ego-resiliency that was distinct from measures of externalizing behaviors and IQ. Using latent structural equation modeling and controlling for baseline economic adversity, IQ, and externalizing symptoms, resilient personality predicted children's concurrent and future achievement (controlling also for baseline achievement in the prospective analyses). Model fit was invariant across gender. PMID:18084626
Measurement invariance across Genders on the Childhood Illness Attitude Scales (CIAS).

PubMed

Thorisdottir, Audur S; Villadsen, Anna; LeBouthillier, Daniel M; Rask, Charlotte Ulrikka; Wright, Kristi D; Walker, John R; Feldgaier, Steven; Asmundson, Gordon J G

2017-07-01

The Childhood Illness Attitude Scales (CIAS) were created as a developmentally appropriate measure for symptoms of health anxiety (HA) in school-aged children. Despite overall sound psychometric properties reported in previous studies, more comprehensive examination of the latent structure and potential response bias in the CIAS is needed. The purpose of the present study was to cross-validate the latent structure of the CIAS across genders and to examine gender-specific variations in CIAS scores. The sample comprised data from 602 Canadian and Danish school-aged children (M age =10.54, SD=0.99; 52.5% girls). Confirmatory factor analyses were conducted to test 3-, modified 3-, and 4-factor models in both samples. Multigroup confirmatory factor analysis was performed to test factor structure invariance across boys and girls in a combined sample. Differential Item Functioning (DIF) was assessed using test characteristic curves. A modified 3-factor solution (i.e., fears=11 items, help-seeking=6 items, and symptom effects=4 items) provided the best fit to the data (χ 2 (364, N=602)=681.7, p<0.001; χ 2 /df=1.803; RMSEA=0.037; CFI=0.926). The factor structure was stable, well-fitting, and indicated measurement invariance across groups. DIF analyses revealed no gender-based response bias at the scale level. Results support a revised 3-factor version of the CIAS that can be used with confidence to assess symptoms of HA in school-aged boys and girls. Copyright © 2017 Elsevier Inc. All rights reserved.
A Multidimensional Item Response Model: Constrained Latent Class Analysis Using the Gibbs Sampler and Posterior Predictive Checks.

ERIC Educational Resources Information Center

Hoijtink, Herbert; Molenaar, Ivo W.

1997-01-01

This paper shows that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. Parameters of this latent class model are estimated using an application of the Gibbs sampler, and model fit is investigated using posterior predictive checks. (SLD)

A Vernacular for Linear Latent Growth Models

ERIC Educational Resources Information Center

Hancock, Gregory R.; Choi, Jaehwa

2006-01-01

In its most basic form, latent growth modeling (latent curve analysis) allows an assessment of individuals' change in a measured variable X over time. For simple linear models, as with other growth models, parameter estimates associated with the a construct (amount of X at a chosen temporal reference point) and b construct (growth in X per unit…
An Overview of Markov Chain Methods for the Study of Stage-Sequential Developmental Processes

ERIC Educational Resources Information Center

Kapland, David

2008-01-01

This article presents an overview of quantitative methodologies for the study of stage-sequential development based on extensions of Markov chain modeling. Four methods are presented that exemplify the flexibility of this approach: the manifest Markov model, the latent Markov model, latent transition analysis, and the mixture latent Markov model.…
A Latent Transition Analysis of Academic Intrinsic Motivation from Childhood through Adolescence

ERIC Educational Resources Information Center

Marcoulides, George A.; Gottfried, Adele Eskeles; Gottfried, Allen W.; Oliver, Pamella H.

2008-01-01

A longitudinal modeling approach was utilized to determine the existence of latent classes with regard to academic intrinsic motivation and the points of stability and transition of individuals between and within classes. A special type of latent Markov Chain model using "Mplus" was fit to data from the Fullerton Longitudinal Study, with…
Combined Patterns of Risk for Problem and Obesogenic Behaviors in Adolescents: A Latent Class Analysis Approach

ERIC Educational Resources Information Center

Fleary, Sasha A.

2017-01-01

Background: Several studies have used latent class analyses to explore obesogenic behaviors and substance use in adolescents independently. We explored a variety of health risks jointly to identify distinct patterns of risk behaviors among adolescents. Methods: Latent class models were estimated using Youth Risk Behavior Surveillance System…
A Latent Profile Analysis of University Students' Self-Regulated Learning Strategies

ERIC Educational Resources Information Center

Ning, Hoi Kwan; Downing, Kevin

2015-01-01

Based on self-reported cognitive, metacognitive, and behavioural strategy measures obtained from 828 final-year students from a university in Hong Kong, latent profile analysis (LPA) identified four distinct types of students with differential self-regulated learning strategy orientations: "competent self-regulated learners",…
Reactivation of Latent Tuberculosis in Cynomolgus Macaques Infected with SIV Is Associated with Early Peripheral T Cell Depletion and Not Virus Load

PubMed Central

Klein, Edwin; Janssen, Chris; Phuah, Jiayao; Sturgeon, Timothy J.; Montelaro, Ronald C.; Lin, Philana Ling; Flynn, JoAnne L.

2010-01-01

HIV-infected individuals with latent Mycobacterium tuberculosis (Mtb) infection are at significantly greater risk of reactivation tuberculosis (TB) than HIV-negative individuals with latent TB, even while CD4 T cell numbers are well preserved. Factors underlying high rates of reactivation are poorly understood and investigative tools are limited. We used cynomolgus macaques with latent TB co-infected with SIVmac251 to develop the first animal model of reactivated TB in HIV-infected humans to better explore these factors. All latent animals developed reactivated TB following SIV infection, with a variable time to reactivation (up to 11 months post-SIV). Reactivation was independent of virus load but correlated with depletion of peripheral T cells during acute SIV infection. Animals experiencing reactivation early after SIV infection (<17 weeks) had fewer CD4 T cells in the periphery and airways than animals reactivating in later phases of SIV infection. Co-infected animals had fewer T cells in involved lungs than SIV-negative animals with active TB despite similar T cell numbers in draining lymph nodes. Granulomas from these animals demonstrated histopathologic characteristics consistent with a chronically active disease process. These results suggest initial T cell depletion may strongly influence outcomes of HIV-Mtb co-infection. PMID:20224771
Organizational citizenship behavior in schools: validation of a questionnaire.

PubMed

Neves, Paula C; Paixão, Rui; Alarcão, Madalena; Gomes, A Duarte

2014-01-01

The present study examines the psychometric properties (including factorial validity) of an organizational citizenship behavior (OCB) scale in a school context. A total of 321 middle and high school teachers from 59 schools in urban and rural areas of central Portugal completed the OCB scale at their schools. The confirmatory factor analysis validated a hierarchical model with four latent factors on the first level (altruism, conscientiousness, civic participation and courtesy) and a second order factor (OCB). The revised model fit with the data, χ 2 /gl = 1.97; CFI = .962; GFI = .952, RMSEA = .05. The proposed scale (comportamentos de cidadania organizacional em escolas- Revista CCOE-R)- is a valid instrument to assess teacher's perceptions of OCB in their schools, allowing investigation at the organizational level of analysis.
Assets as a Socioeconomic Status Index: Categorical Principal Components Analysis vs. Latent Class Analysis.

PubMed

Sartipi, Majid; Nedjat, Saharnaz; Mansournia, Mohammad Ali; Baigi, Vali; Fotouhi, Akbar

2016-11-01

Some variables like Socioeconomic Status (SES) cannot be directly measured, instead, so-called 'latent variables' are measured indirectly through calculating tangible items. There are different methods for measuring latent variables such as data reduction methods e.g. Principal Components Analysis (PCA) and Latent Class Analysis (LCA). The purpose of our study was to measure assets index- as a representative of SES- through two methods of Non-Linear PCA (NLPCA) and LCA, and to compare them for choosing the most appropriate model. This was a cross sectional study in which 1995 respondents filled the questionnaires about their assets in Tehran. The data were analyzed by SPSS 19 (CATPCA command) and SAS 9.2 (PROC LCA command) to estimate their socioeconomic status. The results were compared based on the Intra-class Correlation Coefficient (ICC). The 6 derived classes from LCA based on BIC, were highly consistent with the 6 classes from CATPCA (Categorical PCA) (ICC = 0.87, 95%CI: 0.86 - 0.88). There is no gold standard to measure SES. Therefore, it is not possible to definitely say that a specific method is better than another one. LCA is a complicated method that presents detailed information about latent variables and required one assumption (local independency), while NLPCA is a simple method, which requires more assumptions. Generally, NLPCA seems to be an acceptable method of analysis because of its simplicity and high agreement with LCA.
Changes in latent fingerprint examiners' markup between analysis and comparison.

PubMed

Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn

2015-02-01

After the initial analysis of a latent print, an examiner will sometimes revise the assessment during comparison with an exemplar. Changes between analysis and comparison may indicate that the initial analysis of the latent was inadequate, or that confirmation bias may have affected the comparison. 170 volunteer latent print examiners, each randomly assigned 22 pairs of prints from a pool of 320 total pairs, provided detailed markup documenting their interpretations of the prints and the bases for their comparison conclusions. We describe changes in value assessments and markup of features and clarity. When examiners individualized, they almost always added or deleted minutiae (90.3% of individualizations); every examiner revised at least some markups. For inconclusive and exclusion determinations, changes were less common, and features were added more frequently when the image pair was mated (same source). Even when individualizations were based on eight or fewer corresponding minutiae, in most cases some of those minutiae had been added during comparison. One erroneous individualization was observed: the markup changes were notably extreme, and almost all of the corresponding minutiae had been added during comparison. Latents assessed to be of value for exclusion only (VEO) during analysis were often individualized when compared to a mated exemplar (26%); in our previous work, where examiners were not required to provide markup of features, VEO individualizations were much less common (1.8%). Published by Elsevier Ireland Ltd.
Factor Analysis of Therapist-Identified Treatment Targets in Community-Based Children's Mental Health.

PubMed

Love, Allison R; Okado, Izumi; Orimoto, Trina E; Mueller, Charles W

2018-01-01

The present study used exploratory and confirmatory factor analyses to identify underlying latent factors affecting variation in community therapists' endorsement of treatment targets. As part of a statewide practice management program, therapist completed monthly reports of treatment targets (up to 10 per month) for a sample of youth (n = 790) receiving intensive in-home therapy. Nearly 75 % of youth were diagnosed with multiple co-occurring disorders. Five factors emerged: Disinhibition, Societal Rules Evasion, Social Engagement Deficits, Emotional Distress, and Management of Biodevelopmental Outcomes. Using logistic regression, primary diagnosis predicted therapist selection of Disinhibition and Emotional Distress targets. Client age predicted endorsement of Societal Rules Evasion targets. Practice-to-research implications are discussed.
Space-time latent component modeling of geo-referenced health data.

PubMed

Lawson, Andrew B; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun

2010-08-30

Latent structure models have been proposed in many applications. For space-time health data it is often important to be able to find the underlying trends in time, which are supported by subsets of small areas. Latent structure modeling is one such approach to this analysis. This paper presents a mixture-based approach that can be applied to component selection. The analysis of a Georgia ambulatory asthma county-level data set is presented and a simulation-based evaluation is made. Copyright (c) 2010 John Wiley & Sons, Ltd.
The use of cognitive ability measures as explanatory variables in regression analysis.

PubMed

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2012-12-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual's wage, or a decision such as an individual's education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score , constructed via standard psychometric practice from individuals' responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a "mixed effects structural equations" (MESE) model, may be more appropriate in many circumstances.
Substance Use Profiles of Urban American Indian Adolescents: A Latent Class Analysis.

PubMed

Kulis, Stephen S; Jager, Justin; Ayers, Stephanie L; Lateef, Husain; Kiehne, Elizabeth

2016-07-28

A growing majority of American Indian adolescents now live in cities and are at high risk of early and problematic substance use and its negative health effects. This study used latent class analysis to empirically derive heterogeneous patterns of substance use among urban American Indian adolescents, examined demographic correlates of the resulting latent classes, and tested for differences among the latent classes in other risk behavior and prosocial outcomes. The study employed a representative sample of 8th, 10th, and 12th grade American Indian adolescents (n = 2,407) in public or charter schools in metropolitan areas of Arizona in 2012. Latent class analysis examined eight types of last 30 day substance use. Four latent classes emerged: a large group of "nonusers" (69%); a substantial minority using alcohol, tobacco, and/or marijuana [ATM] (17%); a smaller group of polysubstance users consuming, alcohol, tobacco, marijuana, other illicit drugs, and prescription or OTC drugs in combination (6%); and a "not alcohol" group reporting combinations of tobacco, marijuana, and prescription drug use, but rarely alcohol use (4%). The latent classes varied by age and grade level, but not by other demographic characteristics, and aligned in highly consistent patterns on other non-substance use outcomes. Polysubstance users reported the most problematic and nonusers the least problematic outcomes, with ATM and "not alcohol" users in the middle. Urban AI adolescent substance use occurs in three somewhat distinctive patterns of combinations of recent alcohol and drug consumption, covarying in systematic ways with other problematic risk behaviors and attitudes.
[Path analysis of lifestyle habits to the metabolic syndrome].

PubMed

Zhu, Zhen-xin; Zhang, Cheng-qi; Tang, Fang; Song, Xin-hong; Xue, Fu-zhong

2013-04-01

To evaluate the relationship between lifestyle habits and the components of metabolic syndrome (MS). Based on the routine health check-up system in a certain Center for Health Management of Shandong Province, a longitudinal surveillance health check-up cohort from 2005 to 2010 was set up. There were 13 225 urban workers in Jinan included in the analysis. The content of the survey included demographic information, medical history, lifestyle habits, body mass index (BMI) and the level of blood pressure, fasting blood-glucose, and blood lipid, etc. The distribution of BMI, blood pressure, fasting blood-glucose, blood lipid and lifestyle habits between MS patients and non-MS population was compared, latent variables were extracted by exploratory factor analysis to determine the structure model, and then a partial least squares path model was constructed between lifestyle habits and the components of MS. Participants'age was (46.62 ± 12.16) years old. The overall prevalence of the MS was 22.43% (2967/13 225), 26.49% (2535/9570) in males and 11.82% (432/3655) in females. The prevalence of the MS was statistically different between males and females (χ(2) = 327.08, P < 0.01). Between MS patients and non-MS population, the difference of dietary habits was statistically significant (χ(2) = 166.31, P < 0.01) in MS patients, the rate of vegetarian, mixed and animal food was 23.39% (694/2967), 42.50% (1261/2967) and 34.11% (1012/2967) respectively, while in non-MS population was 30.80% (3159/10 258), 46.37% (4757/10 258), 22.83% (2342/10 258) respectively. Their alcohol consumption has statistical difference (χ(2) = 374.22, P < 0.01) in MS patients, the rate of never or past, occasional and regular drinking was 27.37% (812/2967), 24.71% (733/2967), 47.93% (1422/2967) respectively, and in non-MS population was 39.60% (4062/10 258), 31.36% (3217/10 258), 29.04% (2979/10 258) respectively. The difference of their smoking status was statistically significant (χ(2) = 115.86, P < 0.01) in MS patients, the rate of never or past, occasional and regular smoking was 59.72% (1772/2967), 6.24% (185/2967), 34.04% (1010/2967) respectively, while in non-MS population was 70.03% (7184/10 258), 5.35% (549/10 258), 24.61% (2525/10 258) respectively. Both lifestyle habits and the components of MS were attributable to only one latent variable. After adjustment for age and gender, the path coefficient between the latent component of lifestyle habits and the latent component of MS was 0.22 with statistical significance (t = 6.46, P < 0.01) through bootstrap test. Reliability and validity of the model:the lifestyle latent variable: average variance extracted was 0.53, composite reliability was 0.77 and Cronbach's a was 0.57. The MS latent variable: average variance extracted was 0.45, composite reliability was 0.76 and Cronbach's a was 0.59. Unhealthy lifestyle habits are closely related to MS. Meat diet, excessive drinking and smoking are risk factors for MS.
Short-term memory development: differences in serial position curves between age groups and latent classes.

PubMed

Koppenol-Gonzalez, Gabriela V; Bouwmeester, Samantha; Vermunt, Jeroen K

2014-10-01

In studies on the development of cognitive processes, children are often grouped based on their ages before analyzing the data. After the analysis, the differences between age groups are interpreted as developmental differences. We argue that this approach is problematic because the variance in cognitive performance within an age group is considered to be measurement error. However, if a part of this variance is systematic, it can provide very useful information about the cognitive processes used by some children of a certain age but not others. In the current study, we presented 210 children aged 5 to 12 years with serial order short-term memory tasks. First we analyze our data according to the approach using age groups, and then we apply latent class analysis to form latent classes of children based on their performance instead of their ages. We display the results of the age groups and the latent classes in terms of serial position curves, and we discuss the differences in results. Our findings show that there are considerable differences in performance between the age groups and the latent classes. We interpret our findings as indicating that the latent class analysis yielded a much more meaningful way of grouping children in terms of cognitive processes than the a priori grouping of children based on their ages. Copyright © 2014 Elsevier Inc. All rights reserved.
Prediction of incidence and stability of alcohol use disorders by latent internalizing psychopathology risk profiles in adolescence and young adulthood.

PubMed

Behrendt, Silke; Bühringer, Gerhard; Höfler, Michael; Lieb, Roselind; Beesdo-Baum, Katja

2017-10-01

Comorbid internalizing mental disorders in alcohol use disorders (AUD) can be understood as putative independent risk factors for AUD or as expressions of underlying shared psychopathology vulnerabilities. However, it remains unclear whether: 1) specific latent internalizing psychopathology risk-profiles predict AUD-incidence and 2) specific latent internalizing comorbidity-profiles in AUD predict AUD-stability. To investigate baseline latent internalizing psychopathology risk profiles as predictors of subsequent AUD-incidence and -stability in adolescents and young adults. Data from the prospective-longitudinal EDSP study (baseline age 14-24 years) were used. The study-design included up to three follow-up assessments in up to ten years. DSM-IV mental disorders were assessed with the DIA-X/M-CIDI. To investigate risk-profiles and their associations with AUD-outcomes, latent class analysis with auxiliary outcome variables was applied. AUD-incidence: a 4-class model (N=1683) was identified (classes: normative-male [45.9%], normative-female [44.2%], internalizing [5.3%], nicotine dependence [4.5%]). Compared to the normative-female class, all other classes were associated with a higher risk of subsequent incident alcohol dependence (p<0.05). AUD-stability: a 3-class model (N=1940) was identified with only one class (11.6%) with high probabilities for baseline AUD. This class was further characterized by elevated substance use disorder (SUD) probabilities and predicted any subsequent AUD (OR 8.5, 95% CI 5.4-13.3). An internalizing vulnerability may constitute a pathway to AUD incidence in adolescence and young adulthood. In contrast, no indication for a role of internalizing comorbidity profiles in AUD-stability was found, which may indicate a limited importance of such profiles - in contrast to SUD-related profiles - in AUD stability. Copyright © 2017 Elsevier B.V. All rights reserved.
CLUSTERING SOUTH AFRICAN HOUSEHOLDS BASED ON THEIR ASSET STATUS USING LATENT VARIABLE MODELS

PubMed Central

McParland, Damien; Gormley, Isobel Claire; McCormick, Tyler H.; Clark, Samuel J.; Kabudula, Chodziwadziwa Whiteson; Collinson, Mark A.

2014-01-01

The Agincourt Health and Demographic Surveillance System has since 2001 conducted a biannual household asset survey in order to quantify household socio-economic status (SES) in a rural population living in northeast South Africa. The survey contains binary, ordinal and nominal items. In the absence of income or expenditure data, the SES landscape in the study population is explored and described by clustering the households into homogeneous groups based on their asset status. A model-based approach to clustering the Agincourt households, based on latent variable models, is proposed. In the case of modeling binary or ordinal items, item response theory models are employed. For nominal survey items, a factor analysis model, similar in nature to a multinomial probit model, is used. Both model types have an underlying latent variable structure—this similarity is exploited and the models are combined to produce a hybrid model capable of handling mixed data types. Further, a mixture of the hybrid models is considered to provide clustering capabilities within the context of mixed binary, ordinal and nominal response data. The proposed model is termed a mixture of factor analyzers for mixed data (MFA-MD). The MFA-MD model is applied to the survey data to cluster the Agincourt households into homogeneous groups. The model is estimated within the Bayesian paradigm, using a Markov chain Monte Carlo algorithm. Intuitive groupings result, providing insight to the different socio-economic strata within the Agincourt region. PMID:25485026
Cognitive factors affecting children's nonsymbolic and symbolic magnitude judgment abilities: A latent profile analysis.

PubMed

Chew, Cindy S; Forte, Jason D; Reeve, Robert A

2016-12-01

Early math abilities are claimed to be linked to magnitude representation ability. Some claim that nonsymbolic magnitude abilities scaffold the acquisition of symbolic (Arabic number) magnitude abilities and influence math ability. Others claim that symbolic magnitude abilities, and ipso facto math abilities, are independent of nonsymbolic abilities and instead depend on the ability to process number symbols (e.g., 2, 7). Currently, the issue of whether symbolic abilities are or are not related to nonsymbolic abilities, and the cognitive factors associated with nonsymbolic-symbolic relationships, remains unresolved. We suggest that different nonsymbolic-symbolic relationships reside within the general magnitude ability distribution and that different cognitive abilities are likely associated with these different relationships. We further suggest that the different nonsymbolic-symbolic relationships and cognitive abilities in combination differentially predict math abilities. To test these claims, we used latent profile analysis to identify nonsymbolic-symbolic judgment patterns of 124, 5- to 7-year-olds. We also assessed four cognitive factors (visuospatial working memory [VSWM], naming numbers, nonverbal IQ, and basic reaction time [RT]) and two math abilities (number transcoding and single-digit addition abilities). Four nonsymbolic-symbolic ability profiles were identified. Naming numbers, VSWM, and basic RT abilities were differentially associated with the different ability profiles and in combination differentially predicted math abilities. Findings show that different patterns of nonsymbolic-symbolic magnitude abilities can be identified and suggest that an adequate account of math development should specify the inter-relationship between cognitive factors and nonsymbolic-symbolic ability patterns. Copyright © 2016 Elsevier Inc. All rights reserved.
Time course of neck-shoulder pain among workers: A longitudinal latent class growth analysis.

PubMed

Hallman, David M; Rasmussen, Charlotte D Nørregaard; Jørgensen, Marie Birk; Holtermann, Andreas

2018-01-01

Objectives The aims of this study were to (i) identify trajectories of neck-shoulder pain (NSP) over one year in an occupational population and (ii) determine whether these trajectories are predicted by NSP characteristics as well as personal and occupational factors at baseline. Methods This longitudinal study was conducted among Danish workers (N=748) from 2012-2014. Text messages were used to collect frequent data on NSP over one year (14 waves in total). Peak NSP intensity in the past month was rated on a 0-10 numeric scale. A baseline questionnaire covered NSP characteristics (pain intensity, duration, comorbidity, pain medication, and pain interference) as well as personal (age, gender, body mass index) and occupational (seniority, work type, physical strain at work) factors. Latent class growth analysis was used to distinguish trajectories of NSP. Multivariate regression models with odds ratios (OR) were constructed to predict trajectories of NSP. Results Six distinct trajectories of NSP were identified (asymptomatic 11%, very low NSP 10%, low recovering NSP 18%, moderate recovering NSP 28%, strong fluctuating NSP 24% and severe persistent NSP 9% of the workers). Female gender, age, physical strain at work, NSP intensity and duration, pain medication, and pain interference in daily work at baseline were positively associated with severe persistent NSP and strong fluctuating NSP (all P<0.05). Altogether, personal and occupational factors accounted for 14% of the variance, while NSP characteristics accounted for 54%. Conclusions In an occupational sample, six distinct trajectories of NSP were identified. Physical strain at work appears to be a pertinent occupational factor predicting strong fluctuating and severe persistent NSP.
Latent factor structure of a behavioral economic cigarette demand curve in adolescent smokers

PubMed Central

Bidwell, L. Cinnamon; MacKillop, James; Murphy, James G.; Tidey, Jennifer W.; Colby, Suzanne M.

2012-01-01

Behavioral economic demand curves, or quantitative representations of drug consumption across a range of prices, have been used to assess motivation for a variety of drugs. Such curves generate multiple measures of drug demand that are associated with cigarette consumption and nicotine dependence. However, little is known about the relationships among these facets of demand. The aim of the study was to quantify these relationships in adolescent smokers by using exploratory factor analysis to examine the underlying structure of the facets of nicotine incentive value generated from a demand curve measure. Participants were 138 adolescent smokers who completed a hypothetical cigarette purchase task, which assessed estimated cigarette consumption at escalating levels of price/cigarette. Demand curves and five facets of demand were generated from the measure: Elasticity (i.e., 1/α or proportionate price sensitivity); Intensity (i.e., consumption at zero price); Omax (i.e., maximum financial expenditure on cigarettes); Pmax (i.e., price at which expenditure is maximized); and Breakpoint (i.e., the price that suppresses consumption to zero). Principal components analysis was used to examine the latent structure among the variables. The results revealed a two-factor solution, which were interpreted as “Persistence,” reflecting insensitivity to escalating price, and “Amplitude,” reflecting the absolute levels of consumption and price. These findings suggest a two factor structure of nicotine incentive value as measured via a demand curve. If supported, these findings have implications for understanding the relationships among individual demand indices in future behavioral economic studies and may further contribute to understanding of the nature of cigarette reinforcement. PMID:22727784

Evaluation of the Gratitude Questionnaire in a Chinese Sample of Adults: Factorial Validity, Criterion-Related Validity, and Measurement Invariance Across Sex

PubMed Central

Kong, Feng; You, Xuqun; Zhao, Jingjing

2017-01-01

The Gratitude Questionnaire (GQ; McCullough et al., 2002) is one of the most widely used instruments to assess dispositional gratitude. The purpose of this study was to validate a Chinese version of the GQ by examining internal consistency, factor structure, convergent validity, and measurement invariance across sex. A total of 1151 Chinese adults were recruited to complete the GQ, Positive Affect and Negative Affect Scales, and Satisfaction with Life Scale. Confirmatory factor analysis indicated that the original unidimensional model fitted well, which is in accordance with the findings in Western populations. Furthermore, the GQ had satisfactory composite reliability and criterion-related validity with measures of life satisfaction and affective well-being. Evidence of configural, metric and scalar invariance across sex was obtained. Tests of the latent mean differences found females had higher latent mean scores than males. These findings suggest that the Chinese version of GQ is a reliable and valid tool for measuring dispositional gratitude and can generally be utilized across sex in the Chinese context. PMID:28919873
Evaluation of the Gratitude Questionnaire in a Chinese Sample of Adults: Factorial Validity, Criterion-Related Validity, and Measurement Invariance Across Sex.

PubMed

Kong, Feng; You, Xuqun; Zhao, Jingjing

2017-01-01

The Gratitude Questionnaire (GQ; McCullough et al., 2002) is one of the most widely used instruments to assess dispositional gratitude. The purpose of this study was to validate a Chinese version of the GQ by examining internal consistency, factor structure, convergent validity, and measurement invariance across sex. A total of 1151 Chinese adults were recruited to complete the GQ, Positive Affect and Negative Affect Scales, and Satisfaction with Life Scale. Confirmatory factor analysis indicated that the original unidimensional model fitted well, which is in accordance with the findings in Western populations. Furthermore, the GQ had satisfactory composite reliability and criterion-related validity with measures of life satisfaction and affective well-being. Evidence of configural, metric and scalar invariance across sex was obtained. Tests of the latent mean differences found females had higher latent mean scores than males. These findings suggest that the Chinese version of GQ is a reliable and valid tool for measuring dispositional gratitude and can generally be utilized across sex in the Chinese context.
An Evaluation of the Texas Functional Living Scale's Latent Structure and Subscales.

PubMed

González, David Andrés; Soble, Jason R; Marceaux, Janice C; McCoy, Karin J M

2017-02-01

Performance-based functional assessment is a critical component of neuropsychological practice. The Texas Functional Living Scale (TFLS) has promise given its brevity, nationally representative norms, and co-norming with Wechsler scales. However, its subscale structure has not been evaluated. The purpose of this study was to evaluate the TFLS in a mixed clinical sample (n = 197). Reliability and convergent and discriminant validity coefficients were calculated with neurocognitive testing and collateral reports and factor analysis was performed. The Money and Calculation subscale had the best psychometric properties of the subscales. The evidence did not support solitary interpretation of the Time subscale. A three-factor latent structure emerged representing memory and semantic retrieval, performance and visual scanning, and financial calculation. This study added psychometric support for interpretation of the TFLS total score and some of its subscales. Study limitations included sample characteristics (e.g., gender ratio) and low power for collateral report analyses. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Generalized Structured Component Analysis with Latent Interactions

ERIC Educational Resources Information Center

Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan

2010-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…
Meta-Analysis of Scale Reliability Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2013-01-01

A latent variable modeling approach is outlined that can be used for meta-analysis of reliability coefficients of multicomponent measuring instruments. Important limitations of efforts to combine composite reliability findings across multiple studies are initially pointed out. A reliability synthesis procedure is discussed that is based on…
Comparisons of Mathematics Intervention Effects in Resource and Inclusive Classrooms

ERIC Educational Resources Information Center

Bottge, Brian A.; Cohen, Allan S.; Choi, Hye-Jeong

2018-01-01

In this article, we describe results of a reanalysis of two randomized studies that tested the effects of enhanced anchored instruction (EAI) on the fractions computation performance of students in special education resource rooms and inclusive mathematics classrooms. Latent class analysis and latent transition analysis classified students…
A Latent Class Analysis of Dyadic Perfectionism in a College Sample

ERIC Educational Resources Information Center

Lopez, Frederick G.; Fons-Scheyd, Alia; Bush-King, Imelda; McDermott, Ryon C.

2011-01-01

A latent class analysis of dyadic perfectionism scores within a college sample (N = 369) identified four classes of participants. Controlling for gender and current dating status, class membership was associated with significant differences on several measures of relationship attitudes. Gender and class membership also significantly interacted in…
Adolescent cigarette smoking: health-related behavior or normative transgression?

PubMed

Turbin, M S; Jessor, R; Costa, F M

2000-09-01

Relations among measures of adolescent behavior were examined to determine whether cigarette smoking fits into a structure of problem behaviors-behaviors that involve normative transgression-or a structure of health-related behaviors, or both. In an ethnically and socioeconomically diverse sample of 1782 male and female high school adolescents, four first-order problem behavior latent variables-sexual intercourse experience, alcohol abuse, illicit drug use, and delinquency-were established and together were shown to reflect a second-order latent variable of problem behavior. Four first-order latent variables of health-related behaviors-unhealthy dietary habits, sedentary behavior, unsafe behavior, and poor dental hygiene-were also established and together were shown to reflect a second-order latent variable of health-compromising behavior. The structure of relations among those latent variables was modeled. Cigarette smoking had a significant and substantial loading only on the problem-behavior latent variable; its loading on the health-compromising behavior latent variable was essentially zero. Adolescent cigarette smoking relates strongly and directly to problem behaviors and only indirectly, if at all, to health-compromising behaviors. Interventions to prevent or reduce adolescent smoking should attend more to factors that influence problem behaviors.
Induction of reactivation of herpes simplex virus in murine sensory ganglia in vivo by cadmium.

PubMed Central

Fawl, R L; Roizman, B

1993-01-01

Herpes simplex viruses maintained in a latent state in sensory neurons in mice do not reactivate spontaneously, and therefore the factors or procedures which cause the virus to reactivate serve as a clue to the mechanisms by which the virus is maintained in a latent state. We report that cadmium sulfate induces latent virus to reactivate in 75 to 100% of mice tested. The following specific findings are reported. (i) The highest frequency of induction was observed after two to four daily administrations of 100 micrograms of cadmium sulfate. (ii) Zinc, copper, manganese, or nickel sulfate administered in equimolar amounts under the same regimen did not induce viral reactivation; however, zinc sulfate in molar ratios 25-fold greater than those of cadmium induced viral replication in 2 of 16 ganglia tested. (iii) Administration of zinc, nickel, or manganese prior to the cadmium sulfate reduced the incidence of ganglia containing infectious virus. (iv) Administration of cadmium daily during the first week after infection and at 2-day intervals to 13 days after infection resulted in the recovery from ganglia of infectious virus in titers 10- to 100-fold higher than those obtained from animals given saline. Moreover, infectious virus was recovered as late as 11 days after infection compared with 6 days in mice administered saline. (v) Administration of cadmium immediately after infection or repeatedly after establishment of latency did not exhaust the latent virus harbored by sensory neurons, inasmuch as the fraction of ganglia of mice administered cadmium and yielding infectious virus was similar to that observed in mice treated with saline. We conclude that induction of cadmium tolerance precludes reactivation of latent virus. If the induction of metallothionein genes was the sole factor required to cause reactivation of latent virus, it would have been expected that all metals which induce metallothioneins would also induce reactivation, which was not observed. The results therefore raise the possibility that in addition to inducing the metallothionein genes, cadmium inactivates the factors which maintain the virus in latent state. PMID:8230427
Studying Psychosocial Barriers to Drug Treatment Among Chinese Methamphetamine Users Using A 3-Step Latent Class Analysis.

PubMed

Wang, Jichuan; Kelly, Brian C; Liu, Tieqiao; Hao, Wei

2016-03-01

Given the growth in methamphetamine use in China during the 21st century, we assessed perceived psychosocial barriers to drug treatment among this population. Using a sample of 303 methamphetamine users recruited via Respondent Driven Sampling, we use Latent Class Analysis (LCA) to identify possible distinct latent groups among Chinese methamphetamine users on the basis of their perceptions of psychosocial barriers to drug treatment. After covariates were included to predict latent class membership, the 3-step modeling approach was applied. Our findings indicate that the Chinese methamphetamine using population was heterogeneous on perceptions of drug treatment barriers; four distinct latent classes (subpopulations) were identified--Unsupported Deniers, Deniers, Privacy Anxious, and Low Barriers--and individual characteristics shaped the probability of class membership. Efforts to link Chinese methamphetamine users to treatment may require a multi-faceted approach that attends to differing perceptions about impediments to drug treatment. Copyright © 2015. Published by Elsevier Inc.
Blind image quality assessment via probabilistic latent semantic analysis.

PubMed

Yang, Xichen; Sun, Quansen; Wang, Tianshu

2016-01-01

We propose a blind image quality assessment that is highly unsupervised and training free. The new method is based on the hypothesis that the effect caused by distortion can be expressed by certain latent characteristics. Combined with probabilistic latent semantic analysis, the latent characteristics can be discovered by applying a topic model over a visual word dictionary. Four distortion-affected features are extracted to form the visual words in the dictionary: (1) the block-based local histogram; (2) the block-based local mean value; (3) the mean value of contrast within a block; (4) the variance of contrast within a block. Based on the dictionary, the latent topics in the images can be discovered. The discrepancy between the frequency of the topics in an unfamiliar image and a large number of pristine images is applied to measure the image quality. Experimental results for four open databases show that the newly proposed method correlates well with human subjective judgments of diversely distorted images.
Developable images produced by X-rays using the nickel-hypophosphite system. 3: The latent image and trapped hydrogen

NASA Technical Reports Server (NTRS)

May, C. E.; Philipp, W. H.; Marsik, S. J.

1974-01-01

The hydrogen trapped in X-irradiated hypophosphites, phosphites, formates, oxalates, a phosphate, and some organic compounds was vacuum extracted and measured quantitatively with a mass spectrometer. After extraction, normally developable salts were found to be still developable. Thus, the latent image is not the trapped hydrogen but a species of the type HPO(-)2. The amplification factor for irradiated hypophosphites is about 100. A narrow range of wavelengths (at about 0.07 nm, 0.7 A) is responsible for the formation of the latent image.
A Typology of Child School Behavior: Investigation Using Latent Profile Analysis and Cluster Analysis

ERIC Educational Resources Information Center

Mindrila, Diana L.

2016-01-01

To describe and facilitate the identification of child school behavior patterns, we developed a typology of child school behavior (ages 6-11 years) using the norming data (N = 2,338) for the second edition of the Behavior Assessment System for Children Teacher Rating-Child form). Latent profile analysis was conducted with the entire data set,…
Chronic Disease Risk Typologies among Young Adults in Community College.

PubMed

Jeffries, Jayne K; Lytle, Leslie; Sotres-Alvarez, Daniela; Golden, Shelley; Aiello, Allison E; Linnan, Laura

2018-03-01

To address chronic disease risk holistically from a behavioral perspective, insights are needed to refine understanding of the covariance of key health behaviors. This study aims to identify distinct typologies of young adults based on 4 modifiable risk factors of chronic disease using a latent class analysis approach, and to describe patterns of class membership based on demographic characteristics, living arrangements, and weight. Overall, 441 young adults aged 18-35 attending community colleges in the Minnesota Twin Cities area completed a baseline questionnaire for the Choosing Healthy Options in College Environments and Settings study, a RCT. Behavioral items were used to create indicators for latent classes, and individuals were classified using maximum-probability assignment. Three latent classes were identified: 'active, binge-drinkers with a healthy dietary intake' (13.1%); 'non-active, moderate-smokers and non-drinkers with poor dietary intake' (38.2%); 'moderately active, non-smokers and non-drinkers with moderately healthy dietary intake' (48.7%). Classes exhibited unique demographic and weight-related profiles. This study may contribute to the literature on health behaviors among young adults and provides evidence that there are weight and age differences among subgroups. Understanding how behaviors cluster is important for identifying groups for targeted interventions in community colleges.
Childhood personality types: vulnerability and adaptation over time.

PubMed

De Clercq, Barbara; Rettew, David; Althoff, Robert R; De Bolle, Marleen

2012-06-01

Substantial evidence suggests that a Five-Factor Model personality assessment generates a valid description of childhood individual differences and relates to a range of psychological outcomes. Less is known, however, about naturally occurring profiles of personality and their links to psychopathology. The current study explores whether childhood personality characteristics tend to cluster in particular personality profiles that show unique associations with psychopathology and quality of life across time. Latent class analysis was conducted on maternal rated general personality of a Flemish childhood community sample (N = 477; mean age 10.6 years). The associations of latent class membership probability with psychopathology and quality of life 2 years later were examined, using a multi-informant perspective. Four distinguishable latent classes were found, representing a Moderate, a Protected, an Undercontrolled and a Vulnerable childhood personality type. Each of these types showed unique associations with childhood outcomes across raters. Four different personality types can be delineated at young age and have a significant value in understanding vulnerability and adaptation over time. © 2011 The Authors. Journal of Child Psychology and Psychiatry © 2011 Association for Child and Adolescent Mental Health.
A Taxometric Study of the Latent Structure of Disgust Sensitivity: Converging Evidence for Dimensionality

ERIC Educational Resources Information Center

Olatunji, Bunmi O.; Broman-Fulks, Joshua J.

2007-01-01

Disgust sensitivity has recently been implicated as a specific vulnerability factor for several anxiety-related disorders. However, it is not clear whether disgust sensitivity is a dimensional or categorical phenomenon. The present study examined the latent structure of disgust by applying three taxometric procedures (maximum eigenvalue, mean…
Trajectories of Substance Use Disorders in Youth: Identifying and Predicting Group Memberships

ERIC Educational Resources Information Center

Lee, Chih-Yuan S.; Winters, Ken C.; Wall, Melanie M.

2010-01-01

This study used latent class regression to identify latent trajectory classes based on individuals' diagnostic course of substance use disorders (SUDs) from late adolescence to early adulthood as well as to examine whether several psychosocial risk factors predicted the trajectory class membership. The study sample consisted of 310 individuals…
Measurement Invariance for Latent Constructs in Multiple Populations: A Critical View and Refocus

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.; Li, Cheng-Hsien

2012-01-01

Popular measurement invariance testing procedures for latent constructs evaluated by multiple indicators in distinct populations are revisited and discussed. A frequently used test of factor loading invariance is shown to possess serious limitations that in general preclude it from accomplishing its goal of ascertaining this invariance. A process…
Some Factor Analytic Approximations to Latent Class Structure.

ERIC Educational Resources Information Center

Dziuban, Charles D.; Denton, William T.

Three procedures, alpha, image, and uniqueness rescaling, were applied to a joint occurrence probability matrix. That matrix was the basis of a well-known latent class structure. The values of the recurring subscript elements were varied as follows: Case 1 - The known elements were input; Case 2 - The upper bounds to the recurring subscript…
Examining occupational stress, sources of stress and stress management strategies through the eyes of management consultants: a multiple correspondence analysis for latent constructs.

PubMed

von Humboldt, Sofia; Leal, Isabel; Laneiro, Tito; Tavares, Patrícia

2013-12-01

To date, little research has yet focused in broad assessment for management consultancy professionals. This investigation aims to analyse management consultants' self-perceptions of occupational stress (SPoOS), sources of stress (SoS) and stress management strategies (SMS) and to find latent constructs that can work as major determinants in consultants' conceptualization of SPoOS, SoS and SMS. Measures were completed, including demographics and interviews. Complete data were available for 39 management consultants, 53.8% male and aged between 23 and 56 years (M = 38.0; SD = 9.2). The data were subjected to content analysis. Representation of the associations and latent constructs were analysed by a multiple correspondence analysis. Results indicated that 'intellectual disturber' (31.4%) was the most referred SPoOS, 'high workload' (15.1%) was identified as the most prevalent perceived SoS and 'coaching' (19.0%) was the most mentioned SMS. No significant differences between the two gender groups were found regarding the three total scores. SPoOS was explained by a two-factor model: 'organization-oriented' and 'person-oriented'. A three-dimension model formed by 'job concerns', 'organizational constraints' and 'career expectations' was indicated as a best-fit solution for SoS, and SMS was best explained in a three-dimension model by 'group dynamics strategies', 'organizational culture strategies' and 'individual support strategies'. This research makes a unique contribution for a better understanding of what defines SPoOS, SoS and SMS for management consultants. Copyright © 2013 John Wiley & Sons, Ltd.

DNA-PK/Ku complex binds to latency-associated nuclear antigen and negatively regulates Kaposi's sarcoma-associated herpesvirus latent replication

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cha, Seho; Lim, Chunghun; Lee, Jae Young

2010-04-16

During latent infection, latency-associated nuclear antigen (LANA) of Kaposi's sarcoma-associated herpesvirus (KSHV) plays important roles in episomal persistence and replication. Several host factors are associated with KSHV latent replication. Here, we show that the catalytic subunit of DNA protein kinase (DNA-PKcs), Ku70, and Ku86 bind the N-terminal region of LANA. LANA was phosphorylated by DNA-PK and overexpression of Ku70, but not Ku86, impaired transient replication. The efficiency of transient replication was significantly increased in the HCT116 (Ku86 +/-) cell line, compared to the HCT116 (Ku86 +/+) cell line, suggesting that the DNA-PK/Ku complex negatively regulates KSHV latent replication.
A Unified Latent Curve, Latent State-Trait Analysis of the Developmental Trajectories and Correlates of Positive Orientation

ERIC Educational Resources Information Center

Alessandri, Guido; Caprara, Gian Vittorio; Tisak, John

2012-01-01

Literature documents that the judgments people hold about themselves, their life, and their future are important ingredients of their psychological functioning and well-being and are commonly related to each other. In this article, results from a longitudinal study (N = 298, 45% males) are presented. Using an integrative Latent Curve, Latent…
Longitudinal Physical Activity Patterns Among Older Adults: A Latent Transition Analysis.

PubMed

Mooney, Stephen J; Joshi, Spruha; Cerdá, Magdalena; Kennedy, Gary J; Beard, John R; Rundle, Andrew G

2018-05-14

Most epidemiologic studies of physical activity measure either total energy expenditure or engagement in a single activity type, such as walking. These approaches may gloss over important nuances in activity patterns. We performed a latent transition analysis to identify patterns of activity types as well as neighborhood and individual determinants of changes in those activity patterns over two years in a cohort of 2,023 older adult residents of New York City, NY, surveyed between 2011 and 2013. We identified seven latent classes: 1) Mostly Inactive, 2) Walking, 3) Exercise, 4) Household Activities and Walking, 5) Household Activities and Exercise, 6) Gardening and Household Activities, and 7) Gardening, Household Activities, and Exercise. The majority of subjects retained the same activity patterns between waves (54% unchanged between waves 1 and 2, 66% unchanged between waves 2 and 3).Most latent class transitions were between classes distinguished only by one form of activity, and only neighborhood unemployment was consistently associated with changing between activity latent classes. Future latent transition analyses of physical activity would benefit from larger cohorts and longer follow-up periods to assess predictors of and long-term impacts of changes in activity patterns.
Accuracy of latent-variable estimation in Bayesian semi-supervised learning.

PubMed

Yamazaki, Keisuke

2015-09-01

Hierarchical probabilistic models, such as Gaussian mixture models, are widely used for unsupervised learning tasks. These models consist of observable and latent variables, which represent the observable data and the underlying data-generation process, respectively. Unsupervised learning tasks, such as cluster analysis, are regarded as estimations of latent variables based on the observable ones. The estimation of latent variables in semi-supervised learning, where some labels are observed, will be more precise than that in unsupervised, and one of the concerns is to clarify the effect of the labeled data. However, there has not been sufficient theoretical analysis of the accuracy of the estimation of latent variables. In a previous study, a distribution-based error function was formulated, and its asymptotic form was calculated for unsupervised learning with generative models. It has been shown that, for the estimation of latent variables, the Bayes method is more accurate than the maximum-likelihood method. The present paper reveals the asymptotic forms of the error function in Bayesian semi-supervised learning for both discriminative and generative models. The results show that the generative model, which uses all of the given data, performs better when the model is well specified. Copyright © 2015 Elsevier Ltd. All rights reserved.
Assessing factors related to waist circumference and obesity: application of a latent variable model.

PubMed

Dalvand, Sahar; Koohpayehzadeh, Jalil; Karimlou, Masoud; Asgari, Fereshteh; Rafei, Ali; Seifi, Behjat; Niksima, Seyed Hassan; Bakhshi, Enayatollah

2015-01-01

Because the use of BMI (Body Mass Index) alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome) and obesity (binary outcome) among Iranian adults. Data included 18,990 Iranian individuals aged 20-65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variable model, we estimated the relation of two correlated responses (waist circumference and obesity) with independent variables including age, gender, PR (Place of Residence), PA (physical activity), smoking status, SBP (Systolic Blood Pressure), DBP (Diastolic Blood Pressure), CHOL (cholesterol), FBG (Fasting Blood Glucose), diabetes, and FHD (family history of diabetes). All variables were related to both obesity and waist circumference (WC). Older age, female sex, being an urban resident, physical inactivity, nonsmoking, hypertension, hypercholesterolemia, hyperglycemia, diabetes, and having family history of diabetes were significant risk factors that increased WC and obesity. Findings from this study of Iranian adult settings offer more insights into factors associated with high WC and high prevalence of obesity in this population.
Patterns of Gambling Activities and Gambling Problems Among Italian High School Students: Results from a Latent Class Analysis.

PubMed

De Luigi, Nicola; Gibertoni, Dino; Randon, Emanuela; Scorcu, Antonello E

2018-06-01

This study aims to provide an estimate of the prevalence of gambling among Italian adolescents and a description of their patterns of gambling activities (PGAs) using a latent class analysis on 13 different types of games. A nationwide sample of 10,959 Italian high school students was recruited in 2013. We assessed problem gambling using the South Oaks Gambling Screen: Revisited for Adolescent (SOGS-RA) scale. Approximately half (50.6%) of students reported gambling at least once in the previous year; 5.0% of them were problem gamblers and 9.1% were at-risk gamblers according to their SOGS-RA scores. Eight PGAs were identified, among which heavy players (1.7% of students) could be classified as problem gamblers and broad skill players (2.0%) and lotteries & sports players (2.4%) as "at-risk" players. These high-risk classes were consistently associated with risky behaviours in terms of substance use, school performance, money spent on gambling and family environment; the other five classes identified low-risk players associated with safe behaviours. To the best of our knowledge, this is the first study to identify PGAs among Italian adolescents. Problem gamblers are not a homogeneous group in terms of patterns of gambling activities and are associated with different risk factors, among which environmental factors, such as parents' gambling attitude and behaviour, deserve special attention. The acknowledgment of such patterns and risk factors could be useful in developing sensible public policies addressing prevention strategies and regulatory instruments.
Mental Health and Educational Experiences Among Black Youth: A Latent Class Analysis.

PubMed

Rose, Theda; Lindsey, Michael A; Xiao, Yunyu; Finigan-Carr, Nadine M; Joe, Sean

2017-11-01

Disproportionately lower educational achievement, coupled with higher grade retention, suspensions, expulsions, and lower school bonding make educational success among Black adolescents a major public health concern. Mental health is a key developmental factor related to educational outcomes among adolescents; however, traditional models of mental health focus on absence of dysfunction as a way to conceptualize mental health. The dual-factor model of mental health incorporates indicators of both subjective wellbeing and psychopathology, supporting more recent research that both are needed to comprehensively assess mental health. This study applied the dual-factor model to measure mental health using the National Survey of American Life-Adolescent Supplement (NSAL-A), a representative cross-sectional survey. The sample included 1170 Black adolescents (52% female; mean age 15). Latent class analysis was conducted with positive indicators of subjective wellbeing (emotional, psychological, and social) as well as measures of psychopathology. Four mental health groups were identified, based on having high or low subjective wellbeing and high or low psychopathology. Accordingly, associations between mental health groups and educational outcomes were investigated. Significant associations were observed in school bonding, suspensions, and grade retention, with the positive mental health group (high subjective wellbeing, low psychopathology) experiencing more beneficial outcomes. The results support a strong association between school bonding and better mental health and have implications for a more comprehensive view of mental health in interventions targeting improved educational experiences and mental health among Black adolescents.
Behavioral Pediatrics Feeding Assessment Scale in Young Children With Autism Spectrum Disorder: Psychometrics and Associations With Child and Parent Variables

PubMed Central

Allen, Stephanie L.; Duku, Eric; Vaillancourt, Tracy; Szatmari, Peter; Bryson, Susan; Fombonne, Eric; Volden, Joanne; Waddell, Charlotte; Zwaigenbaum, Lonnie; Roberts, Wendy; Mirenda, Pat; Bennett, Teresa; Elsabbagh, Mayada; Georgiades, Stelios

2015-01-01

Objective The factor structure and validity of the Behavioral Pediatrics Feeding Assessment Scale (BPFAS; Crist & Napier-Phillips, 2001) were examined in preschoolers with autism spectrum disorder (ASD). Methods Confirmatory factor analysis was used to examine the original BPFAS five-factor model, the fit of each latent variable, and a rival one-factor model. None of the models was adequate, thus a categorical exploratory factor analysis (CEFA) was conducted. Correlations were used to examine relations between the BPFAS and concurrent variables of interest. Results The CEFA identified an acceptable three-factor model. Correlational analyses indicated that feeding problems were positively related to parent-reported autism symptoms, behavior problems, sleep problems, and parenting stress, but largely unrelated to performance-based indices of autism symptom severity, language, and cognitive abilities, as well as child age. Conclusion These results provide evidence supporting the use of the identified BPFAS three-factor model for samples of young children with ASD. PMID:25725217
A multilevel model for comorbid outcomes: obesity and diabetes in the US.

PubMed

Congdon, Peter

2010-02-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk.
Neuroticism explains unwanted variance in Implicit Association Tests of personality: possible evidence for an affective valence confound.

PubMed

Fleischhauer, Monika; Enge, Sören; Miller, Robert; Strobel, Alexander; Strobel, Anja

2013-01-01

Meta-analytic data highlight the value of the Implicit Association Test (IAT) as an indirect measure of personality. Based on evidence suggesting that confounding factors such as cognitive abilities contribute to the IAT effect, this study provides a first investigation of whether basic personality traits explain unwanted variance in the IAT. In a gender-balanced sample of 204 volunteers, the Big-Five dimensions were assessed via self-report, peer-report, and IAT. By means of structural equation modeling (SEM), latent Big-Five personality factors (based on self- and peer-report) were estimated and their predictive value for unwanted variance in the IAT was examined. In a first analysis, unwanted variance was defined in the sense of method-specific variance which may result from differences in task demands between the two IAT block conditions and which can be mirrored by the absolute size of the IAT effects. In a second analysis, unwanted variance was examined in a broader sense defined as those systematic variance components in the raw IAT scores that are not explained by the latent implicit personality factors. In contrast to the absolute IAT scores, this also considers biases associated with the direction of IAT effects (i.e., whether they are positive or negative in sign), biases that might result, for example, from the IAT's stimulus or category features. None of the explicit Big-Five factors was predictive for method-specific variance in the IATs (first analysis). However, when considering unwanted variance that goes beyond pure method-specific variance (second analysis), a substantial effect of neuroticism occurred that may have been driven by the affective valence of IAT attribute categories and the facilitated processing of negative stimuli, typically associated with neuroticism. The findings thus point to the necessity of using attribute category labels and stimuli of similar affective valence in personality IATs to avoid confounding due to recoding.
Research on the application of a decoupling algorithm for structure analysis

NASA Technical Reports Server (NTRS)

Denman, E. D.

1980-01-01

The mathematical theory for decoupling mth-order matrix differential equations is presented. It is shown that the decoupling precedure can be developed from the algebraic theory of matrix polynomials. The role of eigenprojectors and latent projectors in the decoupling process is discussed and the mathematical relationships between eigenvalues, eigenvectors, latent roots, and latent vectors are developed. It is shown that the eigenvectors of the companion form of a matrix contains the latent vectors as a subset. The spectral decomposition of a matrix and the application to differential equations is given.
Spatiotemporal Pattern of PM2.5 Concentrations in Mainland China and Analysis of Its Influencing Factors using Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Luo, Jieqiong; Du, Peijun; Samat, Alim; Xia, Junshi; Che, Meiqin; Xue, Zhaohui

2017-01-01

Based on annual average PM2.5 gridded dataset, this study first analyzed the spatiotemporal pattern of PM2.5 across Mainland China during 1998-2012. Then facilitated with meteorological site data, land cover data, population and Gross Domestic Product (GDP) data, etc., the contributions of latent geographic factors, including socioeconomic factors (e.g., road, agriculture, population, industry) and natural geographical factors (e.g., topography, climate, vegetation) to PM2.5 were explored through Geographically Weighted Regression (GWR) model. The results revealed that PM2.5 concentrations increased while the spatial pattern remained stable, and the proportion of areas with PM2.5 concentrations greater than 35 μg/m3 significantly increased from 23.08% to 29.89%. Moreover, road, agriculture, population and vegetation showed the most significant impacts on PM2.5. Additionally, the Moran’s I for the residuals of GWR was 0.025 (not significant at a 0.01 level), indicating that the GWR model was properly specified. The local coefficient estimates of GDP in some cities were negative, suggesting the existence of the inverted-U shaped Environmental Kuznets Curve (EKC) for PM2.5 in Mainland China. The effects of each latent factor on PM2.5 in various regions were different. Therefore, regional measures and strategies for controlling PM2.5 should be formulated in terms of the local impacts of specific factors.
Spatiotemporal Pattern of PM2.5 Concentrations in Mainland China and Analysis of Its Influencing Factors using Geographically Weighted Regression

PubMed Central

Luo, Jieqiong; Du, Peijun; Samat, Alim; Xia, Junshi; Che, Meiqin; Xue, Zhaohui

2017-01-01

Based on annual average PM2.5 gridded dataset, this study first analyzed the spatiotemporal pattern of PM2.5 across Mainland China during 1998–2012. Then facilitated with meteorological site data, land cover data, population and Gross Domestic Product (GDP) data, etc., the contributions of latent geographic factors, including socioeconomic factors (e.g., road, agriculture, population, industry) and natural geographical factors (e.g., topography, climate, vegetation) to PM2.5 were explored through Geographically Weighted Regression (GWR) model. The results revealed that PM2.5 concentrations increased while the spatial pattern remained stable, and the proportion of areas with PM2.5 concentrations greater than 35 μg/m3 significantly increased from 23.08% to 29.89%. Moreover, road, agriculture, population and vegetation showed the most significant impacts on PM2.5. Additionally, the Moran’s I for the residuals of GWR was 0.025 (not significant at a 0.01 level), indicating that the GWR model was properly specified. The local coefficient estimates of GDP in some cities were negative, suggesting the existence of the inverted-U shaped Environmental Kuznets Curve (EKC) for PM2.5 in Mainland China. The effects of each latent factor on PM2.5 in various regions were different. Therefore, regional measures and strategies for controlling PM2.5 should be formulated in terms of the local impacts of specific factors. PMID:28079138
Spatiotemporal Pattern of PM2.5 Concentrations in Mainland China and Analysis of Its Influencing Factors using Geographically Weighted Regression.

PubMed

Luo, Jieqiong; Du, Peijun; Samat, Alim; Xia, Junshi; Che, Meiqin; Xue, Zhaohui

2017-01-12

Based on annual average PM 2.5 gridded dataset, this study first analyzed the spatiotemporal pattern of PM 2.5 across Mainland China during 1998-2012. Then facilitated with meteorological site data, land cover data, population and Gross Domestic Product (GDP) data, etc., the contributions of latent geographic factors, including socioeconomic factors (e.g., road, agriculture, population, industry) and natural geographical factors (e.g., topography, climate, vegetation) to PM 2.5 were explored through Geographically Weighted Regression (GWR) model. The results revealed that PM 2.5 concentrations increased while the spatial pattern remained stable, and the proportion of areas with PM 2.5 concentrations greater than 35 μg/m 3 significantly increased from 23.08% to 29.89%. Moreover, road, agriculture, population and vegetation showed the most significant impacts on PM 2.5 . Additionally, the Moran's I for the residuals of GWR was 0.025 (not significant at a 0.01 level), indicating that the GWR model was properly specified. The local coefficient estimates of GDP in some cities were negative, suggesting the existence of the inverted-U shaped Environmental Kuznets Curve (EKC) for PM 2.5 in Mainland China. The effects of each latent factor on PM 2.5 in various regions were different. Therefore, regional measures and strategies for controlling PM 2.5 should be formulated in terms of the local impacts of specific factors.
Associations between Patterns of Objectively Measured Physical Activity and Risk Factors for the Metabolic Syndrome

PubMed Central

Metzger, Jesse S.; Catellier, Diane J.; Evenson, Kelly R.; Treuth, Margarita S.; Rosamond, Wayne D.; Siega-Riz, Anna Maria

2017-01-01

Purpose Determine whether certain patterns of objectively measured physical activity (PA) are associated with the risk factors for or the diagnosis of the metabolic syndrome (MS). Design Latent class analysis, including the assessment of the associations between latent PA classes and the risk factors for MS. Setting Random sample from throughout the United States (US) using data from 2003–2004 National Health and Nutrition Examination Survey. Subjects A total of 3,458 adult, civilian, non-institutionalized US citizens. Measures Daily minutes of moderate-to-vigorous PA across a 7-day week, based on accelerometer measurements, as well ashigh blood pressure, blood glucose levels, triglyceride levels, and body mass index, along with low levels of high density lipoproteins, using clinical cut points. Results Membership in the more active PA classes was consistently associated with lower odds of all of the risk factors for the MS. However, when participants were categorized into quartiles of the coefficient of variation of PA across 7 days, few differences were seen in any of the risk factors. Conclusion Accumulating the total recommended amount of PA for a week is consistently associated with positive health profiles, and more PA than the recommended amounts may suggest. However, the manner in which this activity is accumulated, either spread over most days of the week or compressed into just a couple of days, may have similar associations with the risk factors for the MS. PMID:20073381
Development of a scale to measure adherence to self-monitoring of blood glucose with latent variable measurement.

PubMed

Wagner, J A; Schnoll, R A; Gipson, M T

1998-07-01

Adherence to self-monitoring of blood glucose (SMBG) is problematic for many people with diabetes. Self-reports of adherence have been found to be unreliable, and existing paper-and-pencil measures have limitations. This study developed a brief measure of SMBG adherence with good psychometric properties and a useful factor structure that can be used in research and in practice. A total of 216 adults with diabetes responded to 30 items rated on a 9-point Likert scale that asked about blood monitoring habits. In part I of the study, items were evaluated and retained based on their psychometric properties. The sample was divided into exploratory and confirmatory halves. Using the exploratory half, items with acceptable psychometric properties were subjected to a principal components analysis. In part II of the study, structural equation modeling was used to confirm the component solution with the entire sample. Structural modeling was also used to test the relationship between these components. It was hypothesized that the scale would produce four correlated factors. Principal components analysis suggested a two-component solution, and confirmatory factor analysis confirmed this solution. The first factor measures the degree to which patients rely on others to help them test and thus was named "social influence." The second component measures the degree to which patients use physical symptoms of blood glucose levels to help them test and thus was named "physical influence." Results of the structural model show that the components are correlated and make up the higher-order latent variable adherence. The resulting 15-item scale provides a short, reliable way to assess patient adherence to SMBG. Despite the existence of several aspects of adherence, this study indicates that the construct consists of only two components. This scale is an improvement on previous measures of adherence because of its good psychometric properties, its interpretable factor structure, and its rigorous empirical development.
GARP regulates the bioavailability and activation of TGFβ.

PubMed

Wang, Rui; Zhu, Jianghai; Dong, Xianchi; Shi, Minlong; Lu, Chafen; Springer, Timothy A

2012-03-01

Glycoprotein-A repetitions predominant protein (GARP) associates with latent transforming growth factor-β (proTGFβ) on the surface of T regulatory cells and platelets; however, whether GARP functions in latent TGFβ activation and the structural basis of coassociation remain unknown. We find that Cys-192 and Cys-331 of GARP disulfide link to the TGFβ1 prodomain and that GARP with C192A and C331A mutations can also noncovalently associate with proTGFβ1. Noncovalent association is sufficiently strong for GARP to outcompete latent TGFβ-binding protein for binding to proTGFβ1. Association between GARP and proTGFβ1 prevents the secretion of TGFβ1. Integrin α(V)β(6) and to a lesser extent α(V)β(8) are able to activate TGFβ from the GARP-proTGFβ1 complex. Activation requires the RGD motif of latent TGFβ, disulfide linkage between GARP and latent TGFβ, and membrane association of GARP. Our results show that GARP is a latent TGFβ-binding protein that functions in regulating the bioavailability and activation of TGFβ.
Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination.

PubMed

Zhao, Qibin; Zhang, Liqing; Cichocki, Andrzej

2015-09-01

CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existing CP algorithms require the tensor rank to be manually specified, however, the determination of tensor rank remains a challenging problem especially for CP rank . In addition, existing approaches do not take into account uncertainty information of latent factors, as well as missing entries. To address these issues, we formulate CP factorization using a hierarchical probabilistic model and employ a fully Bayesian treatment by incorporating a sparsity-inducing prior over multiple latent factors and the appropriate hyperpriors over all hyperparameters, resulting in automatic rank determination. To learn the model, we develop an efficient deterministic Bayesian inference algorithm, which scales linearly with data size. Our method is characterized as a tuning parameter-free approach, which can effectively infer underlying multilinear factors with a low-rank constraint, while also providing predictive distributions over missing entries. Extensive simulations on synthetic data illustrate the intrinsic capability of our method to recover the ground-truth of CP rank and prevent the overfitting problem, even when a large amount of entries are missing. Moreover, the results from real-world applications, including image inpainting and facial image synthesis, demonstrate that our method outperforms state-of-the-art approaches for both tensor factorization and tensor completion in terms of predictive performance.
Interrelationships of Physical Activity and Sleep with Cardiovascular Risk Factors: a Person-Oriented Approach.

PubMed

Wennman, Heini; Kronholm, Erkki; Partonen, Timo; Tolvanen, Asko; Peltonen, Markku; Vasankari, Tommi; Borodulin, Katja

2015-12-01

Associations of behaviorally modifiable factors like physical activity (PA), sedentary behaviors, and sleep with cardiovascular diseases (CVDs) are complicated. We examined whether membership in latent classes (LCs) differentiated by PA and sleep profiles (real-life clustering of behaviors in population subgroups) associate with metabolic risk factors and CVD risk. The National FINRISK 2012 Study comprise a cross-sectional sample of 10,000 Finns aged 25 to 74 years. Analyses included participants with complete data on a health questionnaire, a health examination, who had no prevalent CVD (n = 4031). LCs with PA and sleep profiles were previously defined using latent class analysis. Ten metabolic risk factors and the Framingham 10-year CVD risk score were compared between the LCs. PA and sleep class profiles were substantially similar for genders. Compared to LC-1, with a profile including high PA and sufficient sleep, membership in LC-4, with a profile including sedentariness and insufficient sleep was associated with high metabolic risk factors in women but not in men. In women, also membership in LC-2, with a profile including light PA, sufficient sleep, and high sedentariness was associated with high metabolic risk factors. The Framingham 10-year CVD risk score was highest in LCs 2 and 4 in both genders. Membership in LCs differentiated by PA and sleep profiles was associated with metabolic risk factors merely in women, suggesting gender differences in the interrelationships of health behaviors and metabolic risk factors. Total CVD risk differed between the LCs despite of gender; however, the effect was small.
Psychometrically Improved, Abbreviated Versions of Three Classic Measures of Impulsivity and Self-Control

PubMed Central

Morean, Meghan E.; DeMartini, Kelly S.; Leeman, Robert F.; Pearlson, Godfrey D.; Anticevic, Alan; Krishnan-Sarin, Suchitra; Krystal, John H.; O’Malley, Stephanie S.

2014-01-01

Self-reported impulsivity confers risk factor for substance abuse. However, the psychometric properties of many self-report impulsivity measures have been questioned, thereby undermining the interpretability of study findings using these measures. To better understand these measurement limitations and to suggest a path to assessing self-reported impulsivity with greater psychometric stability, we conducted a comprehensive psychometric evaluation of the Barratt Impulsiveness Scale-11 (BIS-11), the Behavioral Inhibition and Activation Scales (BIS/BAS), and the Brief Self Control Scale (BSCS) using data from 1,449 individuals who participated in substance use research. For each measure, we evaluated: 1) latent factor structure, 2) measurement invariance, 3) test-criterion relationships between the measures, and 4) test-criterion relations with drinking and smoking outcomes. Notably, we could not replicate the originally published latent structure for the BIS, BIS/BAS, or BSCS or any previously published alternative factor structures (English language). Using exploratory and confirmatory factor analysis, we identified psychometrically improved, abbreviated versions of each measure (i.e., 8-item, 2 factor BIS-11 [RMSEA = .06, CFI = .95]; 13-item, 4 factor BIS/BAS [RMSEA = .04, CFI = .96]; 7-item, 2 factor BSCS [RMSEA = .05, CFI = .96]). These versions evidenced: 1) stable, replicable factor structures, 2) scalar measurement invariance, ensuring our ability to make statistically interpretable comparisons across subgroups of interest (e.g., sex, race, drinking/smoking status), and 3) test-criterion relationships with each other and with drinking/smoking. This study provides strong support for using these psychometrically improved impulsivity measures, which improve data quality directly through better scale properties and indirectly through reducing response burden. PMID:24885848

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