Examining Factor Score Distributions to Determine the Nature of Latent Spaces
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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…
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
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.
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
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.
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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…
Heterogeneity in the Latent Structure of PTSD Symptoms among Canadian Veterans
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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…
Latent factor structure of a behavioral economic marijuana demand curve.
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.
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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…
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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…
Investigating the Latent Structure of the Teacher Efficacy Scale
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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…
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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…
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).
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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…
Do gender and directness of trauma exposure moderate PTSD's latent structure?
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.
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
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.
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.
Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters
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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…
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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…
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).
Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.
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.
The Impact of Noninvariant Intercepts in Latent Means Models
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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…
The latent structure of the functional dyspepsia symptom complex: a taxometric analysis.
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.
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
Use of Latent Profile Analysis in Studies of Gifted Students
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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…
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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…
Some Factor Analytic Approximations to Latent Class Structure.
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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…
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.
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
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
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.
Latent Variable Modeling of Brain Gray Matter Volume and Psychopathy in Incarcerated Offenders
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
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…
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.
Adolescent cigarette smoking: health-related behavior or normative transgression?
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.
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.
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…
ERIC Educational Resources Information Center
Volkan, Kevin; Simon, Steven R.; Baker, Harley; Todres, I. David
2004-01-01
Problem Statement and Background: While the psychometric properties of Objective Structured Clinical Examinations (OSCEs) have been studied, their latent structures have not been well characterized. This study examines a factor analytic model of a comprehensive OSCE and addresses implications for measurement of clinical performance. Methods: An…
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
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.
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…
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…
Yu, Sen-Chi; Yu, Min-Ning
2007-08-01
This study examines whether the Internet-based questionnaire is psychometrically equivalent to the paper-based questionnaire. A random sample of 2,400 teachers in Taiwan was divided into experimental and control groups. The experimental group was invited to complete the electronic form of the Chinese version of Center for Epidemiologic Studies Depression Scale (CES-D) placed on the Internet, whereas the control group was invited to complete the paper-based CES-D, which they received by mail. The multisample invariance approach, derived from structural equation modeling (SEM), was applied to analyze the collected data. The analytical results show that the two groups have equivalent factor structures in the CES-D. That is, the items in CES-D function equivalently in the two groups. Then the equality of latent mean test was performed. The latent means of "depressed mood," "positive affect," and "interpersonal problems" in CES-D are not significantly different between these two groups. However, the difference in the "somatic symptoms" latent means between these two groups is statistically significant at alpha = 0.01. But the Cohen's d statistics indicates that such differences in latent means do not apparently lead to a meaningful effect size in practice. Both CES-D questionnaires exhibit equal validity, reliability, and factor structures and exhibit a little difference in latent means. Therefore, the Internet-based questionnaire represents a promising alternative to the paper-based questionnaire.
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.
Do gamblers eat more salt? Testing a latent trait model of covariance in consumption
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.
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.
ERIC Educational Resources Information Center
Huang, Francis L.; Ford, Karen L.; Invernizzi, Marcia; Fan, Xitao
2013-01-01
We investigated the latent factor structure of the "Phonological Awareness Literacy Screening for Kindergarteners" in Spanish ("PALS español K"). Participants included 590 Spanish-speaking, public-school kindergarteners from five states. Three theoretically-guided factor structures were measured and tested with one half of our…
Rosellini, Anthony J; Brown, Timothy A
2011-03-01
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 [MDD]) in a large sample of outpatients (N = 1,980). Exploratory structural equation modeling (ESEM) was used to show that a five-factor solution provided acceptable model fit, albeit with some poorly functioning items. Neuroticism demonstrated significant positive associations with all but one of the disorder constructs whereas Extraversion was inversely related to SOC and MDD. Conscientiousness was inversely related to MDD but demonstrated a positive relationship with GAD. Results are discussed in regard to potential revisions to the NEO FFI, the evaluation of other NEO instruments using ESEM, and clinical implications of structural paths between FFM domains and specific emotional disorders.
Rosellini, Anthony J.; Brown, Timothy A.
2017-01-01
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 [MDD]) in a large sample of outpatients (N = 1,980). Exploratory structural equation modeling (ESEM) was used to show that a five-factor solution provided acceptable model fit, albeit with some poorly functioning items. Neuroticism demonstrated significant positive associations with all but one of the disorder constructs whereas Extraversion was inversely related to SOC and MDD. Conscientiousness was inversely related to MDD but demonstrated a positive relationship with GAD. Results are discussed in regard to potential revisions to the NEO FFI, the evaluation of other NEO instruments using ESEM, and clinical implications of structural paths between FFM domains and specific emotional disorders. PMID:20881102
High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
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
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 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…
1995-01-01
The role of the latent TGF-beta binding protein (LTBP) is unclear. In cultures of fetal rat calvarial cells, which form mineralized bonelike nodules, both LTBP and the TGF-beta 1 precursor localized to large fibrillar structures in the extracellular matrix. The appearance of these fibrillar structures preceded the appearance of type I collagen fibers. Plasmin treatment abolished the fibrillar staining pattern for LTBP and released a complex containing both LTBP and TGF-beta. Antibodies and antisense oligonucleotides against LTBP inhibited the formation of mineralized bonelike nodules in long-term fetal rat calvarial cultures. Immunohistochemistry of fetal and adult rat bone confirmed a fibrillar staining pattern for LTBP in vivo. These findings, together with the known homology of LTBP to the fibrillin family of proteins, suggest a novel function for LTBP, in addition to its role in matrix storage of latent TGF-beta, as a structural matrix protein that may play a role in bone formation. PMID:7593177
Bayes Factor Covariance Testing in Item Response Models.
Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip
2017-12-01
Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.
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.
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
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.
Fitzgerald, Joseph M; Broadbridge, Carissa L
2013-01-01
Many researchers employ single-item scales of subjective experiences such as imagery and confidence to assess autobiographical memory. We tested the hypothesis that four latent constructs, recollection, belief, impact, and rehearsal, account for the variance in commonly used scales across four different types of autobiographical memory: earliest childhood memory, cue word memory of personal experience, highly vivid memory, and most stressful memory. Participants rated each memory on scales hypothesised to be indicators of one of four latent constructs. Multi-group confirmatory factor analyses and structural analyses confirmed the similarity of the latent constructs of recollection, belief, impact, and rehearsal, as well as the similarity of the structural relationships among those constructs across memory type. The observed pattern of mean differences between the varieties of autobiographical experiences was consistent with prior research and theory in the study of autobiographical memory.
Toma, Luiza; Mathijs, Erik
2007-04-01
This paper aims to identify the factors underlying farmers' propensity to participate in organic farming programmes in a Romanian rural region that confronts non-point source pollution. For this, we employ structural equation modelling with latent variables using a specific data set collected through an agri-environmental farm survey in 2001. The model includes one 'behavioural intention' latent variable ('propensity to participate in organic farming programmes') and five 'attitude' and 'socio-economic' latent variables ('socio-demographic characteristics', 'economic characteristics', 'agri-environmental information access', 'environmental risk perception' and 'general environmental concern'). The results indicate that, overall, the model has an adequate fit to the data. All loadings are statistically significant, supporting the theoretical basis for assignment of indicators for each latent variable. The significance tests for the structural model parameters show 'environmental risk perception' as the strongest determinant of farmers' propensity to participate in organic farming programmes.
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
Using the SRQ–20 Factor Structure to Examine Changes in Mental Distress Following Typhoon Exposure
Stratton, Kelcey J.; Richardson, Lisa K.; Tran, Trinh Luong; Tam, Nguyen Thanh; Aggen, Steven H.; Berenz, Erin C.; Trung, Lam Tu; Tuan, Tran; Buoi, La Thi; Ha, Tran Thu; Thach, Tran Duc; Amstadter, Ananda B.
2014-01-01
Empirical research is limited regarding postdisaster assessment of distress in developing nations. This study aimed to evaluate the factor structure of the 20-item Self-Reporting Questionnaire (SRQ–20) before and after an acute trauma, Typhoon Xangsane, in order to examine changes in mental health symptoms in an epidemiologic sample of Vietnamese adults. The study examined a model estimating individual item factor loadings, thresholds, and a latent change factor for the SRQ–20's single “general distress” common factor. The covariates of sex, age, and severity of typhoon exposure were used to evaluate the disaster-induced changes in SRQ–20 scores while accounting for possible differences in the relationship between individual measurement scale items and the latent mental health construct. Evidence for measurement noninvariance was found. However, allowing sex and age effects on the pre-typhoon and post-typhoon factors accounted for much of the noninvariance in the SRQ–20 measurement structure. A test of no latent change failed, indicating that the SRQ–20 detected significant individual differences in distress between pre- and post-typhoon assessment. Conditioning on age and sex, several typhoon exposure variables differentially predicted levels of distress change, including evacuation, personal injury, and peri-event fear. On average, females and older individuals reported higher levels of distress than males and younger individuals, respectively. The SRQ–20 is a valid and reasonably stable instrument that may be used in postdisaster contexts to assess emotional distress and individual changes in mental health symptoms. PMID:24512425
Matrix completion by deep matrix factorization.
Fan, Jicong; Cheng, Jieyu
2018-02-01
Conventional methods of matrix completion are linear methods that are not effective in handling data of nonlinear structures. Recently a few researchers attempted to incorporate nonlinear techniques into matrix completion but there still exists considerable limitations. In this paper, a novel method called deep matrix factorization (DMF) is proposed for nonlinear matrix completion. Different from conventional matrix completion methods that are based on linear latent variable models, DMF is on the basis of a nonlinear latent variable model. DMF is formulated as a deep-structure neural network, in which the inputs are the low-dimensional unknown latent variables and the outputs are the partially observed variables. In DMF, the inputs and the parameters of the multilayer neural network are simultaneously optimized to minimize the reconstruction errors for the observed entries. Then the missing entries can be readily recovered by propagating the latent variables to the output layer. DMF is compared with state-of-the-art methods of linear and nonlinear matrix completion in the tasks of toy matrix completion, image inpainting and collaborative filtering. The experimental results verify that DMF is able to provide higher matrix completion accuracy than existing methods do and DMF is applicable to large matrices. Copyright © 2017 Elsevier Ltd. All rights reserved.
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…
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.
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
Hankin, Benjamin L.; Snyder, Hannah R.; Gulley, Lauren D.; Schweizer, Tina H.; Bijttebier, Patricia; Nelis, Sabine; Toh, Gim; Vasey, Michael W.
2016-01-01
It is well known that comorbidity is the rule, not the exception, for categorically defined psychiatric disorders, and this is also the case for internalizing disorders of depression and anxiety. This theoretical review paper addresses the ubiquity of comorbidity among internalizing disorders. Our central thesis is that progress in understanding this co-occurrence can be made by employing latent dimensional structural models that organize both psychopathology as well as vulnerabilities and risk mechanisms and by connecting the multiple levels of risk and psychopathology outcomes together. Different vulnerabilities and risk mechanisms are hypothesized to predict different levels of the structural model of psychopathology. We review the present state of knowledge based on concurrent and developmental sequential comorbidity patterns among common discrete psychiatric disorders in youth, and then we advocate for the use of more recent bifactor dimensional models of psychopathology (e.g., p factor, Caspi et al., 2014) that can help to explain the co-occurrence among internalizing symptoms. In support of this relatively novel conceptual perspective, we review six exemplar vulnerabilities and risk mechanisms, including executive function, information processing biases, cognitive vulnerabilities, positive and negative affectivity aspects of temperament, and autonomic dysregulation, along with the developmental occurrence of stressors in different domains, to show how these vulnerabilities can predict the general latent psychopathology factor, a unique latent internalizing dimension, as well as specific symptom syndrome manifestations. PMID:27739389
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…
Exploration and confirmation of the latent variable structure of the Jefferson scale of empathy
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
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.
Huerta, Snjezana; Zerr, Argero A.; Eisenberg, Nancy; Spinrad, Tracy L.; Valiente, Carlos; Di Giunta, Laura; Pina, Armando A.; Eggum, Natalie D.; Sallquist, Julie; Edwards, Alison; Kupfer, Anne; Lonigan, Christopher J.; Phillips, Beth M.; Wilson, Shauna B.; Clancy-Menchetti, Jeanine; Landry, Susan H.; Swank, Paul R.; Assel, Michael A.; Taylor, Heather B.
2010-01-01
Measurement invariance of a one-factor model of effortful control (EC) was tested for 853 low-income preschoolers (M age = 4.48 years). Using a teacher-report questionnaire and seven behavioral measures, configural invariance (same factor structure across groups), metric invariance (same pattern of factor loadings across groups), and partial scalar invariance (mostly the same intercepts across groups) were established across ethnicity (European Americans, African Americans and Hispanics) and across sex. These results suggest that the latent construct of EC behaved in a similar way across ethnic groups and sex, and that comparisons of mean levels of EC are valid across sex and probably valid across ethnicity, especially when larger numbers of tasks are used. The findings also support the use of diverse behavioral measures as indicators of a single latent EC construct. PMID:20593008
Armour, Cherie; Elhai, Jon D; Richardson, Don; Ractliffe, Kendra; Wang, Li; Elklit, Ask
2012-03-01
Posttraumatic stress disorder's (PTSD) latent structure has been widely debated. To date, two four-factor models (Numbing and Dysphoria) have received the majority of factor analytic support. Recently, Elhai et al. (2011) proposed and supported a revised (five-factor) Dysphoric Arousal model. Data were gathered from two separate samples; War veterans and Primary Care medical patients. The three models were compared and the resultant factors of the Dysphoric Arousal model were validated against external constructs of depression and anxiety. The Dysphoric Arousal model provided significantly better fit than the Numbing and Dysphoria models across both samples. When differentiating between factors, the current results support the idea that Dysphoric Arousal can be differentiated from Anxious Arousal but not from Emotional Numbing when correlated with depression. In conclusion, the Dysphoria model may be a more parsimonious representation of PTSD's latent structure in these trauma populations despite superior fit of the Dysphoric Arousal model. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Kun, Bernadette; Urban, Robert; Paksi, Borbala; Csobor, Lujza Vargane; Olah, Attila; Demetrovics, Zsolt
2012-01-01
Research on the psychometric characteristics, including factor structure, of measures assessing emotional intelligence improve our understanding of the manifest and latent dimensions of the construct. The factor structure of the Bar-On Emotional Quotient Inventory (Bar-On, 1997), despite the popularity of the measure, has been the subject of only…
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Ingles, Candido J.; Marzo, Juan C.; Castejon, Juan L.; Nunez, Jose Carlos; Valle, Antonio; Garcia-Fernandez, Jose M.; Delgado, Beatriz
2011-01-01
This study examined the factorial invariance and latent mean differences of scores on the Spanish version of the "Achievement Goal Tendencies Questionnaire" (AGTQ) across gender and age groups in 2022 Spanish students (51.1% boys) in grades 7 through 10. The equality of factor structures was compared using multi-group confirmatory factor…
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Maslowsky, Julie; Jager, Justin; Hemken, Douglas
2015-01-01
Latent variables are common in psychological research. Research questions involving the interaction of two variables are likewise quite common. Methods for estimating and interpreting interactions between latent variables within a structural equation modeling framework have recently become available. The latent moderated structural equations (LMS)…
A general class of multinomial mixture models for anuran calling survey data
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).
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.
Pre-clinical cognitive phenotypes for Alzheimer disease: a latent profile approach.
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.
von Oertzen, Timo; Brandmaier, Andreas M
2013-06-01
Structural equation models have become a broadly applied data-analytic framework. Among them, latent growth curve models have become a standard method in longitudinal research. However, researchers often rely solely on rules of thumb about statistical power in their study designs. The theory of power equivalence provides an analytical answer to the question of how design factors, for example, the number of observed indicators and the number of time points assessed in repeated measures, trade off against each other while holding the power for likelihood-ratio tests on the latent structure constant. In this article, we present applications of power-equivalent transformations on a model with data from a previously published study on cognitive aging, and highlight consequences of participant attrition on power. PsycINFO Database Record (c) 2013 APA, all rights reserved.
The Latent Structure of Spatial Skills and Mathematics: A Replication of the Two-Factor Model
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Mix, Kelly S.; Levine, Susan C.; Cheng, Yi-Lang; Young, Christopher J.; Hambrick, David Z.; Konstantopoulos, Spyros
2017-01-01
In a previous study, Mix et al. (2016) reported that spatial skill and mathematics were composed of 2 highly correlated, domain-specific factors, with a few cross-domain loadings. The overall structure was consistent across grade (kindergarten, 3rd grade, 6th grade), but the cross-domain loadings varied with age. The present study sought to…
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…
Structural Equation Model Trees
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
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.
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.
Mueller, Kimberly D; Koscik, Rebecca L; Clark, Lindsay R; Hermann, Bruce P; Johnson, Sterling C; Turkstra, Lyn S
2017-11-24
While it is well known that discourse-related language functions are impaired in the dementia phase of Alzheimer's Disease (AD), the presymptomatic temporal course of discourse dysfunction are not known earlier in the course of AD. To conduct discourse-related studies in this phase of AD, validated psychometric instruments are needed. This study investigates the latent structure, validity, and test-retest stability of discourse measures in a late-middle-aged normative group who are relatively free from sporadic AD risk factors. Using a normative sample of 399 participants (mean age = 61), exploratory factor analyses (EFA) and confirmatory factor analyses (CFA) were conducted on 18 measures of connected language derived from picture descriptions. Factor invariance across sex and family history and longitudinal test-retest stability measures were calculated. The EFA revealed a four-factor solution, consisting of semantic, syntax, fluency, and lexical constructs. The CFA model substantiated the structure, and factors were invariant across sex and parental history of AD status. Test-retest stability measures were within acceptable ranges. Results confirm a factor structure that is invariant across sex and parental AD history. The factor structure could be useful in similar cohorts designed to detect early language decline in investigations of preclinical or clinical AD or as outcome measures in clinical prevention trials. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
A multilevel model for comorbid outcomes: obesity and diabetes in the US.
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.
Homework Emotion Regulation Scale: Confirming the Factor Structure with High School Students
ERIC Educational Resources Information Center
Xu, Jianzhong; Fan, Xitao; Du, Jianxia
2017-01-01
The current investigation studied psychometric properties of the Homework Emotion Regulation Scale (HERS) for math homework, with 915 tenth graders from China. Confirmatory factor analyses (CFAs) supported the presence of two separate yet related subscales for the HERS: Emotion Management and Cognitive Reappraisal. The latent factor means for both…
Latent Factor Structure of DSM-5 Posttraumatic Stress Disorder
Gentes, Emily; Dennis, Paul A.; Kimbrel, Nathan A.; Kirby, Angela C.; Hair, Lauren P.; Beckham, Jean C.; Calhoun, Patrick S.
2015-01-01
The current study examined the latent factor structure of posttraumatic stress disorder (PTSD) based on DSM-5 criteria in a sample of participants (N = 374) recruited for studies on trauma and health. Confirmatory factor analyses (CFA) were used to compare the fit of the previous 3-factor DSM-IV model of PTSD to the 4-factor model specified in DSM-5 as well as to a competing 4-factor “dysphoria” model (Simms, Watson, & Doebbeling, 2002) and a 5-factor (Elhai et al., 2011) model of PTSD. Results indicated that the Elhai 5-factor model (re-experiencing, active avoidance, emotional numbing, dysphoric arousal, anxious arousal) provided the best fit to the data, although substantial support was demonstrated for the DSM-5 4-factor model. Low factor loadings were noted for two of the symptoms in the DSM-5 model (psychogenic amnesia and reckless/self-destructive behavior), which raises questions regarding the adequacy of fit of these symptoms with other core features of the disorder. Overall, the findings from the present research suggest the DSM-5 model of PTSD is a significant improvement over the previous DSM-IV model of PTSD. PMID:26366290
Recio, Guillermo; Wilhelm, Oliver; Sommer, Werner; Hildebrandt, Andrea
2017-04-01
Despite a wealth of knowledge about the neural mechanisms behind emotional facial expression processing, little is known about how they relate to individual differences in social cognition abilities. We studied individual differences in the event-related potentials (ERPs) elicited by dynamic facial expressions. First, we assessed the latent structure of the ERPs, reflecting structural face processing in the N170, and the allocation of processing resources and reflexive attention to emotionally salient stimuli, in the early posterior negativity (EPN) and the late positive complex (LPC). Then we estimated brain-behavior relationships between the ERP factors and behavioral indicators of facial identity and emotion-processing abilities. Structural models revealed that the participants who formed faster structural representations of neutral faces (i.e., shorter N170 latencies) performed better at face perception (r = -.51) and memory (r = -.42). The N170 amplitude was not related to individual differences in face cognition or emotion processing. The latent EPN factor correlated with emotion perception (r = .47) and memory (r = .32), and also with face perception abilities (r = .41). Interestingly, the latent factor representing the difference in EPN amplitudes between the two neutral control conditions (chewing and blinking movements) also correlated with emotion perception (r = .51), highlighting the importance of tracking facial changes in the perception of emotional facial expressions. The LPC factor for negative expressions correlated with the memory for emotional facial expressions. The links revealed between the latency and strength of activations of brain systems and individual differences in processing socio-emotional information provide new insights into the brain mechanisms involved in social communication.
Bayesian Semiparametric Structural Equation Models with Latent Variables
ERIC Educational Resources Information Center
Yang, Mingan; Dunson, David B.
2010-01-01
Structural equation models (SEMs) with latent variables are widely useful for sparse covariance structure modeling and for inferring relationships among latent variables. Bayesian SEMs are appealing in allowing for the incorporation of prior information and in providing exact posterior distributions of unknowns, including the latent variables. In…
Clark, Shaunna L.; Gillespie, Nathan A.; Adkins, Daniel E.; Kendler, Kenneth S.; Neale, Michael C.
2015-01-01
Aims This study explored the factor structure of DSM III-R/IV symptoms for substance abuse and dependence across six illicit substance categories in a population-based sample of males. Method DSM III-R/IV drug abuse and dependence symptoms for cannabis, sedatives, stimulants, cocaine, opioids and hallucinogens from 4179 males born 1940-1970 from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders were analyzed. Confirmatory factor analyses tested specific hypotheses regarding the latent structure of substance misuse for a comprehensive battery of 13 misuse symptoms measured across six illicit substance categories (78 items). Results Among the models fit, the latent structure of substance misuse was best represented by a combination of substance-specific factors and misuse symptom-specific factors. We found no support for a general liability factor to illicit substance misuse. Conclusions Results indicate that liability to misuse illicit substances is drug class specific, with little evidence for a general liability factor. Additionally, unique dimensions capturing propensity toward specific misuse symptoms (e.g., tolerance, withdrawal) across substances were identified. While this finding requires independent replication, the possibility of symptom-specific misuse factors, present in multiple substances, raises the prospect of genetic, neurobiological and behavioral predispositions toward distinct, narrowly defined features of drug abuse and dependence. PMID:26517709
Multivariate analysis of fears in dental phobic patients according to a reduced FSS-II scale.
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.
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.
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Park, Jungkyu; Yu, Hsiu-Ting
2016-01-01
The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…
Many-level multilevel structural equation modeling: An efficient evaluation strategy.
Pritikin, Joshua N; Hunter, Michael D; von Oertzen, Timo; Brick, Timothy R; Boker, Steven M
2017-01-01
Structural equation models are increasingly used for clustered or multilevel data in cases where mixed regression is too inflexible. However, when there are many levels of nesting, these models can become difficult to estimate. We introduce a novel evaluation strategy, Rampart, that applies an orthogonal rotation to the parts of a model that conform to commonly met requirements. This rotation dramatically simplifies fit evaluation in a way that becomes more potent as the size of the data set increases. We validate and evaluate the implementation using a 3-level latent regression simulation study. Then we analyze data from a state-wide child behavioral health measure administered by the Oklahoma Department of Human Services. We demonstrate the efficiency of Rampart compared to other similar software using a latent factor model with a 5-level decomposition of latent variance. Rampart is implemented in OpenMx, a free and open source software.
The Coach-Athlete Relationship Questionnaire (CART-Q): development and initial validation.
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).
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.
GARP regulates the bioavailability and activation of TGFβ.
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.
ERIC Educational Resources Information Center
Dombrowski, Stefan C.; Golay, Philippe; McGill, Ryan J.; Canivez, Gary L.
2018-01-01
Bayesian structural equation modeling (BSEM) was used to investigate the latent structure of the Differential Ability Scales-Second Edition core battery using the standardization sample normative data for ages 7-17. Results revealed plausibility of a three-factor model, consistent with publisher theory, expressed as either a higher-order (HO) or a…
Refining the Measurement of Distress Intolerance
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
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
Inter-Cultural Communication: A Foundation of Communicative Action
ERIC Educational Resources Information Center
Vuckovic, Aleksandra
2008-01-01
Purpose: The purpose of this paper is to present a model of inter-cultural communication that enumerates and structures latent factors affecting such communication and elaborates on the process of self-reflection as a guiding mechanism of successful communication. Design/methodology/approach: The five factors and various moderators that are…
The Concept of Adjustment: A Structural Model.
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Dodds, A.; And Others
1994-01-01
This study analyzed scores of 469 British adult clients with recent loss of sight on the Nottingham Adjustment Scale using LISREL structural modeling techniques. Results supported a theoretical model of the self in terms of two latent factors--internal self-worth and self as agent. Implications for rehabilitation and intervention with cognitive…
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…
Flexible Modeling of Latent Task Structures in Multitask Learning
2012-06-26
Flexible Modeling of Latent Task Structures in Multitask Learning Alexandre Passos† apassos@cs.umass.edu Computer Science Department, University of...of Maryland, College Park, MD USA Abstract Multitask learning algorithms are typically designed assuming some fixed, a priori known latent structure...shared by all the tasks. However, it is usually unclear what type of latent task structure is the most ap- propriate for a given multitask learning prob
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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…
The use of fault reporting of medical equipment to identify latent design flaws.
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.
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.
Measurement invariance across Genders on the Childhood Illness Attitude Scales (CIAS).
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.
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.
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)…
A Multilevel Model for Comorbid Outcomes: Obesity and Diabetes in the US
Congdon, Peter
2010-01-01
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. PMID:20616977
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)
Grove, Rachel; Baillie, Andrew; Allison, Carrie; Baron-Cohen, Simon; Hoekstra, Rosa A
2013-05-01
The search for genes involved in autism spectrum conditions (ASC) may have been hindered by the assumption that the different symptoms that define the condition can be attributed to the same causal mechanism. Instead the social and nonsocial aspects of ASC may have distinct causes at genetic, cognitive, and neural levels. It has been posited that the core features of ASC can be explained by a deficit in empathizing alongside intact or superior systemizing; the drive to understand and derive rules about a system. First-degree relatives also show some mild manifestations that parallel the defining features of ASC, termed the broader autism phenotype. Factor analyses were conducted to assess whether the latent structure of empathizing, systemizing, and autistic traits differs across samples with a high (individuals on the spectrum), medium (first-degree relatives) or low (general population controls) genetic vulnerability to autism. Results highlighted a two-factor model, confirming an empathizing and a systemizing factor. The relationship between these two factors was significantly stronger in first-degree relatives and the autism group compared with controls. The same model provided the best fit among the three groups, suggesting a similar latent structure irrespective of genetic vulnerability. However, results also suggest that although these traits are relatively independent in the general population, they are substantially correlated in individuals with ASC and their parents. This implies that there is substantially more overlap between systemizing and empathizing among individuals with an increased genetic liability to autism. This has potential implications for the genetic, environmental, and cognitive explanations of autism spectrum conditions. © 2013 American Psychological Association
Longitudinal studies of anger and attention span: context and informant effects.
Kim, Jungmeen; Mullineaux, Paula Y; Allen, Ben; Deater-Deckard, Kirby
2010-04-01
This study examined stabilities of informant and context (home vs. classroom) latent factors regarding anger and attention. Participants included children from the National Institute of Child Health and Development Study of Early Child Care and Youth Development who were measured at 54 months, first grade, and third grade. Latent factors of anger and attention span were structured using different indicators based on mothers', fathers', caregivers', teachers', and observers' reports. We used structural equation modeling to examine the autoregressive effects within a context (stability), the concurrent associations between home and classroom contexts, and informant effects. The results indicated that for both anger and attention (1) there were significant informant effects that influenced stability in a context, (2) there was higher stability in home context than nonhome context, and (3) stability within a context increased over time. The findings suggested that anger was more prone to context effects and informant effects than attention.
Determinant Factors of Attitude towards Quantitative Subjects: Differences between Sexes
ERIC Educational Resources Information Center
Mondejar-Jimenez, Jose; Vargas-Vargas, Manuel
2010-01-01
Nowadays, almost all curricula in the social sciences contain at least one course in statistics, given the importance of this discipline as an analytical tool. This work identifies the latent factors relating to students' motivation and attitude towards statistics, tests their covariance structure for samples of both sexes, and identifies the…
ERIC Educational Resources Information Center
Dickey, Wayne C.; Blumberg, Stephen J.
2004-01-01
Objective: The Strengths and Difficulties Questionnaire is a 25-item instrument developed to assess emotional and behavioral problems. The current study attempted to replicate previous European structural analyses and to describe the latent dimensions that underlie responses to the parent-reported version of the Strengths and Difficulties…
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.
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.
Medical University admission test: a confirmatory factor analysis of the results.
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.
Latent Structure of Motor Abilities in Pre-School Children
ERIC Educational Resources Information Center
Vatroslav, Horvat
2011-01-01
The theoretical and practical knowledge which have so far been acquired through work with pre-school children pointed to the conclusion that the structures of the latent dimensions of the motor abilities differ greatly from such a structure, in pre-school children and adults alike. Establishing the latent structure of the motor abilities in…
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
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.
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
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).
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
ERIC Educational Resources Information Center
Bauer, Daniel J.; Curran, Patrick J.
2004-01-01
Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…
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
Using SAS PROC CALIS to fit Level-1 error covariance structures of latent growth models.
Ding, Cherng G; Jane, Ten-Der
2012-09-01
In the present article, we demonstrates the use of SAS PROC CALIS to fit various types of Level-1 error covariance structures of latent growth models (LGM). Advantages of the SEM approach, on which PROC CALIS is based, include the capabilities of modeling the change over time for latent constructs, measured by multiple indicators; embedding LGM into a larger latent variable model; incorporating measurement models for latent predictors; and better assessing model fit and the flexibility in specifying error covariance structures. The strength of PROC CALIS is always accompanied with technical coding work, which needs to be specifically addressed. We provide a tutorial on the SAS syntax for modeling the growth of a manifest variable and the growth of a latent construct, focusing the documentation on the specification of Level-1 error covariance structures. Illustrations are conducted with the data generated from two given latent growth models. The coding provided is helpful when the growth model has been well determined and the Level-1 error covariance structure is to be identified.
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.…
Le, Minh Thi Hong; Tran, Thach Duc; Holton, Sara; Nguyen, Huong Thanh; Wolfe, Rory; Fisher, Jane
2017-01-01
To assess the internal consistency, latent structure and convergent validity of the Depression, Anxiety and Stress Scale-21 (DASS-21) among adolescents in Vietnam. An anonymous, self-completed questionnaire was conducted among 1,745 high school students in Hanoi, Vietnam between October, 2013 and January, 2014. Confirmatory factor analyses were performed to assess the latent structure of the DASS-21. Factorial invariance between girls and boys was examined. Cronbach alphas and correlation coefficients between DASS-21 factor scores and the domain scores of the Duke Health Profile Adolescent Vietnamese validated version (ADHP-V) were calculated to assess DASS-21 internal consistency and convergent validity. A total of 1,606/ 1,745 (92.6%) students returned the questionnaire. Of those, 1,387 students provided complete DASS-21 data. The scale demonstrated adequate internal consistency (Cronbach α: 0.761 to 0.906). A four-factor model showed the best fit to the data. Items loaded significantly on a common general distress factor, the depression, and the anxiety factors, but few on the stress factor (p<0.05). DASS-21 convergent validity was confirmed with moderate correlation coefficients (-0.47 to -0.66) between its factor scores and the ADHP-V mental health related domains. The DASS-21 is reliable and suitable for use to assess symptoms of common mental health problems, especially depression and anxiety among Vietnamese adolescents. However, its ability in detecting stress among these adolescents may be limited. Further research is warrant to explore these results.
The Latent Structure of Memory: A Confirmatory Factor-Analytic Study of Memory Distinctions.
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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…
Use of Item Parceling in Structural Equation Modeling with Missing Data
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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…
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Hagger, Martin S.; Biddle, Stuart J. H.; John Wang, C. K.
2005-01-01
This study tests the generalizability of the factor pattern, structural parameters, and latent mean structure of a multidimensional, hierarchical model of physical self-concept in adolescents across gender and grade. A children's version of the Physical Self-Perception Profile (C-PSPP) was administered to seventh-, eighth- and ninth-grade high…
Mixture IRT Model with a Higher-Order Structure for Latent Traits
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Huang, Hung-Yu
2017-01-01
Mixture item response theory (IRT) models have been suggested as an efficient method of detecting the different response patterns derived from latent classes when developing a test. In testing situations, multiple latent traits measured by a battery of tests can exhibit a higher-order structure, and mixtures of latent classes may occur on…
Scalable non-negative matrix tri-factorization.
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.
Bayesian latent structure modeling of walking behavior in a physical activity intervention
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
An Evaluation of the Texas Functional Living Scale's Latent Structure and Subscales.
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.
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
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
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.
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
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).
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
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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…
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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…
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Bauermeister, Jose J.; Barkley, Russell A.; Bauermeister, Jose A.; Martinez, Jose V.; McBurnett, Keith
2012-01-01
This study examined the latent structure and validity of inattention, hyperactivity-impulsivity, and sluggish cognitive tempo (SCT) symptomatology. We evaluated mother and teacher ratings of ADHD and SCT symptoms in 140 Puerto Rican children (55.7% males), ages 6 to 11 years, via factor and regression analyses. A three-factor model (inattention,…
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Holm-Denoma, Jill M.; Richey, J. Anthony; Joiner, Thomas E., Jr.
2010-01-01
Although the latent structure of various eating disorders has been explored in previous studies, no published studies have examined the latent structure of theoretically relevant variables that have been shown to cut across eating disorder diagnoses. The current study examined 3 such variables (dietary restraint, body dissatisfaction, and drive…
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Quilty, Lena C.; Zhang, K. Anne; Bagby, R. Michael
2010-01-01
The Beck Depression Inventory-II (BDI-II) is a self-report instrument frequently used in clinical and research settings to assess depression severity. Although investigators have examined the factor structure of the BDI-II, a clear consensus on the best fitting model has not yet emerged, resulting in different recommendations regarding how to best…
The Beck Depression Inventory, Second Edition (BDI-II): A Cross-Sample Structural Analysis
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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…
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Yaden, David B., Jr.; Marx, Ronald W.; Cimetta, Adriana D.; Alkhadim, Ghadah S.; Cutshaw, Christina
2017-01-01
For two decades, it has been recommended that assessment of literacy for preschool children be conducted in a child's primary language. However, only a few literacy assessments have been validated with a preschool, Spanish-speaking population. The purpose of the present study was to test the latent structure of the Phonological Awareness Literacy…
A Taxonomy of Latent Structure Assumptions for Probability Matrix Decomposition Models.
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Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven
2003-01-01
Proposed a taxonomy of latent structure assumptions for probability matrix decomposition (PMD) that includes the original PMD model and a three-way extension of the multiple classification latent class model. Simulation study results show the usefulness of the taxonomy. (SLD)
Hurlocker, Margo C; Vidaurri, Desirae N; Cuccurullo, Lisa-Ann J; Maieritsch, Kelly; Franklin, C Laurel
2018-03-15
Posttraumatic stress disorder (PTSD) is a complex psychiatric illness that can be difficult to diagnose, due in part to its comorbidity with major depressive disorder (MDD). Given that researchers have found no difference in prevalence rates of PTSD and MDD after accounting for overlapping symptoms, the latent structures of PTSD and MDD may account for the high comorbidity. In particular, the PTSD Negative Alterations in Cognition and Mood (NACM) and Hyperarousal factors have been characterized as non-specific to PTSD. Therefore, we compared the factor structures of the Diagnostic and Statistical Manual of Mental Disorders, 5 th edition (DSM-5) PTSD and MDD and examined the mediating role of the PTSD NACM and Hyperarousal factors on the relationship between MDD and PTSD symptom severity. Participants included 598 trauma-exposed veterans (M age = 48.39, 89% male) who completed symptom self-report measures of DSM-5 PTSD and MDD. Confirmatory factor analyses indicated an adequate-fitting four-factor DSM-5 PTSD model and two-factor MDD model. Compared to other PTSD factors, the PTSD NACM factor had the strongest relationship with the MDD Affective factor, and the PTSD NACM and Hyperarousal factors had the strongest association with the MDD Somatic factor. Further, the PTSD NACM factor explained the relationship between MDD factors and PTSD symptom severity. More Affective and Somatic depression was related to more NACM symptoms, which in turn were related to increased severity of PTSD. Limitations include the reliance on self-report measures and the use of a treatment-seeking, trauma-exposed veteran sample which may not generalize to other populations. Implications concerning the shared somatic complaints and psychological distress in the comorbidity of PTSD and MDD are discussed. Published by Elsevier B.V.
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
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
La Greca, Annette M; Ingles, Candido J; Lai, Betty S; Marzo, Juan C
2015-04-01
Social anxiety is a common psychological disorder that often emerges during adolescence and is associated with significant impairment. Efforts to prevent social anxiety disorder require sound assessment measures for identifying anxious youth, especially those from minority backgrounds. We examined the factorial invariance and latent mean differences of the Social Anxiety Scale for Adolescents (SAS-A) across gender and age groups in Hispanic American adolescents (N = 1,191; 56% girls; 15-18 years) using multigroup confirmatory factor analyses. Results indicated that the factorial configuration of the correlated three-factor model of the SAS-A was invariant across gender and age. Analyses of latent mean differences revealed that boys exhibited higher structured means than girls on the Social Avoidance and Distress-General (SAD-General) subscale. On all SAS-A subscales, Fear of Negative Evaluation, Social Avoidance and Distress-New, and SAD-General, estimates of the structured means decreased with adolescent age. Implications for further research and clinical practice are discussed. © The Author(s) 2014.
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.
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.
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
Tran, Thach Duc; Holton, Sara; Nguyen, Huong Thanh; Wolfe, Rory; Fisher, Jane
2017-01-01
Objectives To assess the internal consistency, latent structure and convergent validity of the Depression, Anxiety and Stress Scale-21 (DASS-21) among adolescents in Vietnam. Method An anonymous, self-completed questionnaire was conducted among 1,745 high school students in Hanoi, Vietnam between October, 2013 and January, 2014. Confirmatory factor analyses were performed to assess the latent structure of the DASS-21. Factorial invariance between girls and boys was examined. Cronbach alphas and correlation coefficients between DASS-21 factor scores and the domain scores of the Duke Health Profile Adolescent Vietnamese validated version (ADHP-V) were calculated to assess DASS-21 internal consistency and convergent validity. Results A total of 1,606/ 1,745 (92.6%) students returned the questionnaire. Of those, 1,387 students provided complete DASS-21 data. The scale demonstrated adequate internal consistency (Cronbach α: 0.761 to 0.906). A four-factor model showed the best fit to the data. Items loaded significantly on a common general distress factor, the depression, and the anxiety factors, but few on the stress factor (p<0.05). DASS-21 convergent validity was confirmed with moderate correlation coefficients (-0.47 to -0.66) between its factor scores and the ADHP-V mental health related domains. Conclusions The DASS-21 is reliable and suitable for use to assess symptoms of common mental health problems, especially depression and anxiety among Vietnamese adolescents. However, its ability in detecting stress among these adolescents may be limited. Further research is warrant to explore these results. PMID:28723909
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.
TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS
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
Test-retest reliability of the underlying latent factor structure of alcohol subjective response.
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.
Much Ado about Nothing--Or at Best, Very Little
ERIC Educational Resources Information Center
Widaman, Keith F.
2014-01-01
Latent variable structural equation modeling has become the analytic method of choice in many domains of research in psychology and allied social sciences. One important aspect of a latent variable model concerns the relations hypothesized to hold between latent variables and their indicators. The most common specification of structural equation…
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.
Chen, Chiung M; Yoon, Young-Hee; Harford, Thomas C; Grant, Bridget F
2017-06-01
Emerging confirmatory factor analytic (CFA) studies suggest that posttraumatic stress disorder (PTSD) as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) is best characterized by seven factors, including re-experiencing, avoidance, negative affect, anhedonia, externalizing behaviors, and anxious and dysphoric arousal. The seven factors, however, have been found to be highly correlated, suggesting that one general factor may exist to explain the overall correlations among symptoms. Using data from the National Epidemiologic Survey on Alcohol and Related Conditions-III, a large, national survey of 36,309 U.S. adults ages 18 and older, this study proposed and tested an exploratory bifactor hybrid model for DSM-5 PTSD symptoms. The model posited one general and seven specific latent factors, whose associations with suicide attempts and mediating psychiatric disorders were used to validate the PTSD dimensionality. The exploratory bifactor hybrid model fitted the data extremely well, outperforming the 7-factor CFA hybrid model and other competing CFA models. The general factor was found to be the single dominant latent trait that explained most of the common variance (~76%) and showed significant, positive associations with suicide attempts and mediating psychiatric disorders, offering support to the concurrent validity of the PTSD construct. The identification of the primary latent trait of PTSD confirms PTSD as an independent psychiatric disorder and helps define PTSD severity in clinical practice and for etiologic research. The accurate specification of PTSD factor structure has implications for treatment efforts and the prevention of suicidal behaviors.
The Internalizing and Externalizing Structure of Psychiatric Comorbidity in Combat Veterans
Miller, Mark W.; Fogler, Jason M.; Wolf, Erika J.; Kaloupek, Danny G.; Keane, Terence M.
2013-01-01
This study examined the latent structure of psychiatric disorders in a sample with a high prevalence of PTSD. A series of confirmatory factor analyses tested competing models for the covariation between SCID diagnoses among 1,325 Vietnam veterans. The best fitting solution was a three-factor model that included two correlated internalizing factors: anxious-misery, defined by PTSD and major depression, and fear, defined by panic disorder/agoraphobia and obsessive-compulsive disorder. The third factor, externalizing, was defined by antisocial personality disorder, alcohol abuse/dependence, and drug abuse/dependence. Both substance-related disorders also showed significant, albeit smaller, cross-loadings on the anxious-misery factor. These findings shed new light on the structure of psychiatric comorbidity in a treatment-seeking sample characterized by high rates of PTSD. PMID:18302181
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
The Rosenberg Self-Esteem Scale: a bifactor answer to a two-factor question?
McKay, Michael T; Boduszek, Daniel; Harvey, Séamus A
2014-01-01
Despite its long-standing and widespread use, disagreement remains regarding the structure of the Rosenberg Self-Esteem Scale (RSES). In particular, concern remains regarding the degree to which the scale assesses self-esteem as a unidimensional or multidimensional (positive and negative self-esteem) construct. Using a sample of 3,862 high school students in the United Kingdom, 4 models were tested: (a) a unidimensional model, (b) a correlated 2-factor model in which the 2 latent variables are represented by positive and negative self-esteem, (c) a hierarchical model, and (d) a bifactor model. The totality of results including item loadings, goodness-of-fit indexes, reliability estimates, and correlations with self-efficacy measures all supported the bifactor model, suggesting that the 2 hypothesized factors are better understood as "grouping" factors rather than as representative of latent constructs. Accordingly, this study supports the unidimensionality of the RSES and the scoring of all 10 items to produce a global self-esteem score.
The mechanisms mediating the effects of poverty on children's intellectual development.
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.
ERIC Educational Resources Information Center
Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michele
2013-01-01
We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth…
Fall Risk, Supports and Services, and Falls Following a Nursing Home Discharge.
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.
The Latent Structure of Attention Deficit/Hyperactivity Disorder in an Adult Sample
Marcus, David K.; Norris, Alyssa L.; Coccaro, Emil F.
2012-01-01
The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. PMID:22480749
The latent structure of attention deficit/hyperactivity disorder in an adult sample.
Marcus, David K; Norris, Alyssa L; Coccaro, Emil F
2012-06-01
The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. Copyright © 2012 Elsevier Ltd. All rights reserved.
Latent variable model for suicide risk in relation to social capital and socio-economic status.
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.
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…
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…
Contextual Stress and Health Risk Behaviors among African American Adolescents
ERIC Educational Resources Information Center
Copeland-Linder, Nikeea; Lambert, Sharon F.; Chen, Yi-Fu; Ialongo, Nicholas S.
2011-01-01
This study examined the longitudinal association between contextual stress and health risk behaviors and the role of protective factors in a community epidemiologically-defined sample of urban African American adolescents (N = 500; 46.4% female). Structural equation modeling was used to create a latent variable measuring contextual stress…
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…
ERIC Educational Resources Information Center
Kim-Spoon, Jungmeen; Ollendick, Thomas H.; Seligman, Laura D.
2012-01-01
This longitudinal study examined the interactive effects of depressive attributional style and multiple domains of perceived competence on depressive symptoms among 431 adolescents. Our structural equation modeling with latent factor interactions indicated that (1) for girls with a higher depressive attributional style, lower perceived competence…
Korean immigrants' knowledge of heart attack symptoms and risk factors.
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.
A Second-Order Confirmatory Factor Analysis of the Moral Distress Scale-Revised for Nurses.
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.
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…
Urzúa, Alfonso; Caqueo-Urízar, Alejandra; Bargsted, Mariana; Irarrázaval, Matías
2015-06-01
This study aimed to evaluate whether the scoring system of the General Health Questionnaire (GHQ-12) alters the instrument's factor structure. The method considered 1,972 university students from nine Ibero American countries. Modeling was performed with structural equations for 1, 2, and 3 latent factors. The mechanism for scoring the questions was analyzed within each type of structure. The results indicate that models with 2 and 3 factors show better goodness-of-fit. In relation to scoring mechanisms, procedure 0-1-1-1 for models with 2 and 3 factors showed the best fit. In conclusion, there appears to be a relationship between the response format and the number of factors identified in the instrument's structure. The model with the best fit was 3-factor 0-1-1-1-formatted, but 0-1-2-3 has acceptable and more stable indicators and provides a better format for two- and three-dimensional models.
Horiguchi, Masahito; Todorovic, Vesna; Hadjiolova, Krassimira; Weiskirchen, Ralf; Rifkin, Daniel B
2015-04-01
Latent transforming growth factor-β binding protein-1 (LTBP-1) is an extracellular protein that is structurally similar to fibrillin and has an important role in controlling transforming growth factor-β (TGF-β) signaling by storing the cytokine in the extracellular matrix and by being involved in the conversion of the latent growth factor to its active form. LTBP-1 is found as both short (LTBP-1S) and long (LTBP-1L) forms, which are derived through the use of separate promoters. There is controversy regarding the importance of LTBP-1L, as Ltbp1L knockout mice showed multiple cardiovascular defects but the complete null mice did not. Here, we describe a third line of Ltbp1 knockout mice generated utilizing a conditional knockout strategy that ablated expression of both L and S forms of LTBP-1. These mice show severe developmental cardiovascular abnormalities and die perinatally; thus these animals display a phenotype similar to previously reported Ltbp1L knockout mice. We reinvestigated the other "complete" knockout line and found that these mice express a splice variant of LTBP-1L and, therefore, are not complete Ltbp1 knockouts. Our results clarify the phenotypes of Ltbp1 null mice and re-emphasize the importance of LTBP-1 in vivo. Copyright © 2015. Published by Elsevier B.V.
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
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.
NASA Technical Reports Server (NTRS)
Guimond, Stephen R.; Bourassa, mark A.; Reasor, Paul D.
2011-01-01
The release of latent heat in clouds is an essential part of the formation and I intensification ohurricanes. The community knows very little about the intensity and structure of latent heating due largely to inadequate observations. In this paper, a new method for retrieving the latent heating field in hurricanes from airborne Dopple radar is presented and fields from rapidly intensifying Hurricane Guillermo (1997) are shown.
Teacher Burnout: A Comparison of Two Cultures Using Confirmatory Factor and Item Response Models
Denton, Ellen-ge; Chaplin, William F.; Wall, Melanie
2014-01-01
The present study addresses teacher burnout and in particular cultural differences and similarities in burnout. We used the Maslach Burnout Inventory Education Survey (MBI-ES) as the starting point for developing a latent model of burnout in two cultures; Jamaica W.I. teachers (N= 150) and New York City teachers (N= 150). We confirm a latent 3 factor structure, using a subset of the items from the MBI-ES that adequately fit both samples. We tested different degrees of measurement invariance (model fit statistics, scale reliabilities, residual variances, item thresholds, and total variance) to describe and compare cultural differences. Results indicate some differences between the samples at the structure and item levels. We found that factor variances were slightly higher in the New York City teacher sample. Emotional Exhaustion (EE) was a more informative construct for differentiating among teachers at moderate levels of burnout, as opposed to extreme high or low levels of burnout, in both cultures. In contrast, Depersonalization in the Workplace (DW) was more informative at the more extreme levels of burnout among both teacher samples. By studying the influence of culture on the experience of burnout we can further our understanding of burnout and potentially discover factors that might prevent burnout among primary and secondary school teachers. PMID:25729572
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.
ERIC Educational Resources Information Center
Yang, Chongming; Nay, Sandra; Hoyle, Rick H.
2010-01-01
Lengthy scales or testlets pose certain challenges for structural equation modeling (SEM) if all the items are included as indicators of a latent construct. Three general approaches to modeling lengthy scales in SEM (parceling, latent scoring, and shortening) have been reviewed and evaluated. A hypothetical population model is simulated containing…
ERIC Educational Resources Information Center
Bartolucci, F.; Montanari, G. E.; Pandolfi, S.
2012-01-01
With reference to a questionnaire aimed at assessing the performance of Italian nursing homes on the basis of the health conditions of their patients, we investigate two relevant issues: dimensionality of the latent structure and discriminating power of the items composing the questionnaire. The approach is based on a multidimensional item…
Schürmann, Tim; Beckerle, Philipp; Preller, Julia; Vogt, Joachim; Christ, Oliver
2016-12-19
In product development for lower limb prosthetic devices, a set of special criteria needs to be met. Prosthetic devices have a direct impact on the rehabilitation process after an amputation with both perceived technological and psychological aspects playing an important role. However, available psychometric questionnaires fail to consider the important links between these two dimensions. In this article a probabilistic latent trait model is proposed with seven technical and psychological factors which measure satisfaction with the prosthesis. The results of a first study are used to determine the basic parameters of the statistical model. These distributions represent hypotheses about factor loadings between manifest items and latent factors of the proposed psychometric questionnaire. A study was conducted and analyzed to form hypotheses for the prior distributions of the questionnaire's measurement model. An expert agreement study conducted on 22 experts was used to determine the prior distribution of item-factor loadings in the model. Model parameters that had to be specified as part of the measurement model were informed prior distributions on the item-factor loadings. For the current 70 items in the questionnaire, each factor loading was set to represent the certainty with which experts had assigned the items to their respective factors. Considering only the measurement model and not the structural model of the questionnaire, 70 out of 217 informed prior distributions on parameters were set. The use of preliminary studies to set prior distributions in latent trait models, while being a relatively new approach in psychological research, provides helpful information towards the design of a seven factor questionnaire that means to identify relations between technical and psychological factors in prosthetic product design and rehabilitation medicine.
Exploring the Factor Structure of Neurocognitive Measures in Older Individuals
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
Personality and the latent structure of PTSD comorbidity
Miller, Mark W.; Wolf, Erika J.
2012-01-01
This study examined the structure of PTSD comorbidity and its relationship to personality in a sample of 214 veterans using data from diagnostic interviews and the Multidimensional Personality Questionnaire-Brief Form (MPQ-BF; Patrick, Curtin, & Tellegen, 2002). Confirmatory factor analyses supported a three factor model composed of Externalizing, Fear and Distress factors. Analyses that examined the location of borderline personality disorder revealed significant cross-loadings for this disorder on both Externalizing and Distress. Structural equation models showed trait negative emotionality to be significantly related to all three comorbidity factors whereas positive emotionality and constraint evidenced specific associations with Distress and Externalizing, respectively. These results shed new light on the location of borderline personality disorder within the internalizing/externalizing model and clarify the relative influence of broad dimensions of personality on patterns of comorbidity. PMID:22480716
Avoiding and Correcting Bias in Score-Based Latent Variable Regression with Discrete Manifest Items
ERIC Educational Resources Information Center
Lu, Irene R. R.; Thomas, D. Roland
2008-01-01
This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…
Latent factor structure of a behavioral economic cigarette demand curve in adolescent smokers
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
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…
The Development of Verbal and Visual Working Memory Processes: A Latent Variable Approach
ERIC Educational Resources Information Center
Koppenol-Gonzalez, Gabriela V.; Bouwmeester, Samantha; Vermunt, Jeroen K.
2012-01-01
Working memory (WM) processing in children has been studied with different approaches, focusing on either the organizational structure of WM processing during development (factor analytic) or the influence of different task conditions on WM processing (experimental). The current study combined both approaches, aiming to distinguish verbal and…
Estimation and Model Selection for Finite Mixtures of Latent Interaction Models
ERIC Educational Resources Information Center
Hsu, Jui-Chen
2011-01-01
Latent interaction models and mixture models have received considerable attention in social science research recently, but little is known about how to handle if unobserved population heterogeneity exists in the endogenous latent variables of the nonlinear structural equation models. The current study estimates a mixture of latent interaction…
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
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.
Why aren’t they happy? An analysis of end-user satisfaction with Electronic health records
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
ERIC Educational Resources Information Center
McGrath, Robert E.; Walters, Glenn D.
2012-01-01
Statistical analyses investigating latent structure can be divided into those that estimate structural model parameters and those that detect the structural model type. The most basic distinction among structure types is between categorical (discrete) and dimensional (continuous) models. It is a common, and potentially misleading, practice to…
Friendship Group Composition and Juvenile Institutional Misconduct.
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.
Brunwasser, Steven M; Gebretsadik, Tebeb; Gold, Diane R; Turi, Kedir N; Stone, Cosby A; Datta, Soma; Gern, James E; Hartert, Tina V
2018-01-01
The International Study of Asthma and Allergies in Children (ISAAC) Wheezing Module is commonly used to characterize pediatric asthma in epidemiological studies, including nearly all airway cohorts participating in the Environmental Influences on Child Health Outcomes (ECHO) consortium. However, there is no consensus model for operationalizing wheezing severity with this instrument in explanatory research studies. Severity is typically measured using coarsely-defined categorical variables, reducing power and potentially underestimating etiological associations. More precise measurement approaches could improve testing of etiological theories of wheezing illness. We evaluated a continuous latent variable model of pediatric wheezing severity based on four ISAAC Wheezing Module items. Analyses included subgroups of children from three independent cohorts whose parents reported past wheezing: infants ages 0-2 in the INSPIRE birth cohort study (Cohort 1; n = 657), 6-7-year-old North American children from Phase One of the ISAAC study (Cohort 2; n = 2,765), and 5-6-year-old children in the EHAAS birth cohort study (Cohort 3; n = 102). Models were estimated using structural equation modeling. In all cohorts, covariance patterns implied by the latent variable model were consistent with the observed data, as indicated by non-significant χ2 goodness of fit tests (no evidence of model misspecification). Cohort 1 analyses showed that the latent factor structure was stable across time points and child sexes. In both cohorts 1 and 3, the latent wheezing severity variable was prospectively associated with wheeze-related clinical outcomes, including physician asthma diagnosis, acute corticosteroid use, and wheeze-related outpatient medical visits when adjusting for confounders. We developed an easily applicable continuous latent variable model of pediatric wheezing severity based on items from the well-validated ISAAC Wheezing Module. This model prospectively associates with asthma morbidity, as demonstrated in two ECHO birth cohort studies, and provides a more statistically powerful method of testing etiologic hypotheses of childhood wheezing illness and asthma.
Cosco, Theodore D; Doyle, Frank; Watson, Roger; Ward, Mark; McGee, Hannah
2012-01-01
The Hospital Anxiety and Depression Scale (HADS) is a prolifically used scale of anxiety and depression. The original bidimensional anxiety-depression latent structure of the HADS has come under significant scrutiny, with previous studies revealing one-, two-, three- and four-dimensional structures. The current study examines the latent structure of the HADS using a non-parametric item response theory method. Using data conglomerated from four independent studies of cardiovascular disease employing the HADS (n=893), Mokken scaling procedure was conducted to assess the latent structure of the HADS. A single scale consisting of 12 of 14 HADS items was revealed, indicating a unidimensional latent HADS structure. The HADS was initially intended to measure mutually exclusive levels of anxiety and depression; however, the current study indicates that a single dimension of general psychological distress is captured. Copyright © 2012 Elsevier Inc. All rights reserved.
The algebraic theory of latent projectors in lambda matrices
NASA Technical Reports Server (NTRS)
Denman, E. D.; Leyva-Ramos, J.; Jeon, G. J.
1981-01-01
Multivariable systems such as a finite-element model of vibrating structures, control systems, and large-scale systems are often formulated in terms of differential equations which give rise to lambda matrices. The present investigation is concerned with the formulation of the algebraic theory of lambda matrices and the relationship of latent roots, latent vectors, and latent projectors to the eigenvalues, eigenvectors, and eigenprojectors of the companion form. The chain rule for latent projectors and eigenprojectors for the repeated latent root or eigenvalues is given.
Cognitive Abilities Explain Wording Effects in the Rosenberg Self-Esteem Scale.
Gnambs, Timo; Schroeders, Ulrich
2017-12-01
There is consensus that the 10 items of the Rosenberg Self-Esteem Scale (RSES) reflect wording effects resulting from positively and negatively keyed items. The present study examined the effects of cognitive abilities on the factor structure of the RSES with a novel, nonparametric latent variable technique called local structural equation models. In a nationally representative German large-scale assessment including 12,437 students competing measurement models for the RSES were compared: a bifactor model with a common factor and a specific factor for all negatively worded items had an optimal fit. Local structural equation models showed that the unidimensionality of the scale increased with higher levels of reading competence and reasoning, while the proportion of variance attributed to the negatively keyed items declined. Wording effects on the factor structure of the RSES seem to represent a response style artifact associated with cognitive abilities.
Harford, Thomas C.; Chen, Chiung M.; Saha, Tulshi D.; Smith, Sharon M.; Ruan, W. June; Grant, Bridget F.
2013-01-01
Background Although associations between personality disorders and psychiatric disorders are well established in general population studies, their association with liability dimensions for externalizing and internalizing disorders has not been fully assessed. The purpose of this study is to examine associations between personality disorders (PDs) and lifetime externalizing and internalizing Axis I disorders. Methods Data were obtained from the total sample of 34,653 respondents from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Drawing on the literature, a 3-factor exploratory structural equation model was selected to simultaneously assess the measurement relations among DSM-IV Axis I substance use and mood and anxiety disorders and the structural relations between the latent internalizing-externalizing dimensions and DSM-IV PDs, adjusting for gender, age, race/ethnicity, and marital status. Results Antisocial, histrionic, and borderline PDs were strong predictors for the externalizing factor, while schizotypal, borderline, avoidant, and obsessive-compulsive PDs had significantly larger effects on the internalizing fear factor when compared to the internalizing misery factor. Paranoid, schizoid, narcissistic, and dependent PDs provided limited discrimination between and among the three factors. An overarching latent factor representing general personality dysfunction was significantly greater on the internalizing fear factor followed by the externalizing factor, and weakest for the internalizing misery factor. Conclusion Personality disorders offer important opportunities for studies on the externalizing-internalizing spectrum of common psychiatric disorders. Future studies based on panic, anxiety, and depressive symptoms may elucidate PD associations with the internalizing spectrum of disorders. PMID:23932575
Harford, Thomas C; Chen, Chiung M; Saha, Tulshi D; Smith, Sharon M; Ruan, W June; Grant, Bridget F
2013-11-01
Although associations between personality disorders and psychiatric disorders are well established in general population studies, their association with liability dimensions for externalizing and internalizing disorders has not been fully assessed. The purpose of this study is to examine associations between personality disorders (PDs) and lifetime externalizing and internalizing Axis I disorders. Data were obtained from the total sample of 34,653 respondents from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Drawing on the literature, a 3-factor exploratory structural equation model was selected to simultaneously assess the measurement relations among DSM-IV Axis I substance use and mood and anxiety disorders and the structural relations between the latent internalizing-externalizing dimensions and DSM-IV PDs, adjusting for gender, age, race/ethnicity, and marital status. Antisocial, histrionic, and borderline PDs were strong predictors for the externalizing factor, while schizotypal, borderline, avoidant, and obsessive-compulsive PDs had significantly larger effects on the internalizing fear factor when compared to the internalizing misery factor. Paranoid, schizoid, narcissistic, and dependent PDs provided limited discrimination between and among the three factors. An overarching latent factor representing general personality dysfunction was significantly greater on the internalizing fear factor followed by the externalizing factor, and weakest for the internalizing misery factor. Personality disorders offer important opportunities for studies on the externalizing-internalizing spectrum of common psychiatric disorders. Future studies based on panic, anxiety, and depressive symptoms may elucidate PD associations with the internalizing spectrum of disorders. Published by Elsevier Ltd.
ERIC Educational Resources Information Center
Lippke, Sonia; Nigg, Claudio R.; Maddock, Jay E.
2007-01-01
This is the first study to test whether the stages of change of the transtheoretical model are qualitatively different through exploring discontinuity patterns in theory of planned behavior (TPB) variables using latent multigroup structural equation modeling (MSEM) with AMOS. Discontinuity patterns in terms of latent means and prediction patterns…
Selecting the "Best" Factor Structure and Moving Measurement Validation Forward: An Illustration.
Schmitt, Thomas A; Sass, Daniel A; Chappelle, Wayne; Thompson, William
2018-04-09
Despite the broad literature base on factor analysis best practices, research seeking to evaluate a measure's psychometric properties frequently fails to consider or follow these recommendations. This leads to incorrect factor structures, numerous and often overly complex competing factor models and, perhaps most harmful, biased model results. Our goal is to demonstrate a practical and actionable process for factor analysis through (a) an overview of six statistical and psychometric issues and approaches to be aware of, investigate, and report when engaging in factor structure validation, along with a flowchart for recommended procedures to understand latent factor structures; (b) demonstrating these issues to provide a summary of the updated Posttraumatic Stress Disorder Checklist (PCL-5) factor models and a rationale for validation; and (c) conducting a comprehensive statistical and psychometric validation of the PCL-5 factor structure to demonstrate all the issues we described earlier. Considering previous research, the PCL-5 was evaluated using a sample of 1,403 U.S. Air Force remotely piloted aircraft operators with high levels of battlefield exposure. Previously proposed PCL-5 factor structures were not supported by the data, but instead a bifactor model is arguably more statistically appropriate.
NASA Technical Reports Server (NTRS)
Shepherd, J. Marshall; Einaudi, Franco (Technical Monitor)
2000-01-01
The Tropical Rainfall Measuring Mission (TRMM) as a part of NASA's Earth System Enterprise is the first mission dedicated to measuring tropical rainfall through microwave and visible sensors, and includes the first spaceborne rain radar. Tropical rainfall comprises two-thirds of global rainfall. It is also the primary distributor of heat through the atmosphere's circulation. It is this circulation that defines Earth's weather and climate. Understanding rainfall and its variability is crucial to understanding and predicting global climate change. Weather and climate models need an accurate assessment of the latent heating released as tropical rainfall occurs. Currently, cloud model-based algorithms are used to derive latent heating based on rainfall structure. Ultimately, these algorithms can be applied to actual data from TRMM. This study investigates key underlying assumptions used in developing the latent heating algorithms. For example, the standard algorithm is highly dependent on a system's rainfall amount and structure. It also depends on an a priori database of model-derived latent heating profiles based on the aforementioned rainfall characteristics. Unanswered questions remain concerning the sensitivity of latent heating profiles to environmental conditions (both thermodynamic and kinematic), regionality, and seasonality. This study investigates and quantifies such sensitivities and seeks to determine the optimal latent heating profile database based on the results. Ultimately, the study seeks to produce an optimized latent heating algorithm based not only on rainfall structure but also hydrometeor profiles.
Hildebrandt, Tom; Epstein, Elizabeth E.; Sysko, Robyn; Bux, Donald A.
2017-01-01
Background The type A/B classification model for alcohol use disorders (AUDs) has received considerable empirical support. However, few studies examine the underlying latent structure of this subtyping model, which has been challenged as a dichotomization of a single drinking severity dimension. Type B, relative to type A, alcoholics represent those with early age of onset, greater familial risk, and worse outcomes from alcohol use. Method We examined the latent structure of the type A/B model using categorical, dimensional, and factor mixture models in a mixed gender community treatment-seeking sample of adults with an AUD. Results Factor analytic models identified 2-factors (drinking severity/externalizing psychopathology and internalizing psychopathology) underlying the type A/B indicators. A factor mixture model with 2-dimensions and 3-classes emerged as the best overall fitting model. The classes reflected a type A class and two type B classes (B1 and B2) that differed on the respective level of drinking severity/externalizing pathology and internalizing pathology. Type B1 had a greater prevalence of women and more internalizing pathology and B2 had a greater prevalence of men and more drinking severity/externalizing pathology. The 2-factor, 3-class model also exhibited predictive validity by explaining significant variance in 12-month drinking and drug use outcomes. Conclusions The model identified in the current study may provide a basis for examining different sources of heterogeneity in the course and outcome of AUDs. PMID:28247423
Armour, Cherie; Elhai, Jon D; Layne, Christopher M; Shevlin, Mark; Duraković-Belko, Elvira; Djapo, Nermin; Pynoos, Robert S
2011-05-01
DSM-IV's three-factor model of posttraumatic stress disorder (PTSD) is rarely empirically supported, whereas other four-factor models (King et al., 1998; Simms, Watson, & Doebbeling, 2002) have proven to be better representations of PTSD's latent structure. To date, a clear consensus as to which model provides the best representation of PTSD's underlying dimensions has yet to be reached. The current study investigated whether gender is associated with factor structure differences using the King et al. (1998) model of reexperiencing, avoidance, numbing, and hyperarousal PTSD symptoms. Participants were war-exposed Bosnian secondary/high school boys and girls (N=1572) assessed nearly two years after the 1992-1995 Bosnian conflict. Confirmatory factor analytic tests of measurement invariance across PTSD model parameters revealed many significant sex-linked differences. Implications regarding the potential role of gender as a moderator of the King et al. (1998) model's factor structure are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.
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
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.
Residual Structures in Latent Growth Curve Modeling
ERIC Educational Resources Information Center
Grimm, Kevin J.; Widaman, Keith F.
2010-01-01
Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…
Reactivation of Latent HIV-1 Expression by Engineered TALE Transcription Factors.
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.
Convective structure of the planetary boundary layer of the ocean during gale
NASA Technical Reports Server (NTRS)
Melfi, S. H.; Boers, R.
1986-01-01
The structure of the Planetary Boundary Layer (PBL) was measured, using an airborne lidar, over the Atlantic Ocean during several intensive observation periods of the Genesis of Atlantic Lows Experiment (GALE). Primary emphasis is on the understanding of the convective structure within the PBL during cold air outbreaks. Cold outbreaks generally occur in between the development of coastal storms; and behind a cold front sweeping down from Canada out across the Atlantic. As the cold dry air moves over the relatively warm ocean, it is heated and moistened. The transfer of latent and sensible heat during these events accounts for most of the heat transfer between the ocean and atmosphere during winter. Moistening of the PBL during these eventsis believed to be an important factor in determining the strength of development of the storm system which follows. In general, the more PBL moisture available as latent heat the higher the probability the storm will intensify. The major mechanism for vertical mixing of heat and mositure within the PBL is cellular convection. Knowlede of the organization and structure of the convection is important for understanding the process.
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.
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…
Stability of Core Language Skill from Early Childhood to Adolescence: A Latent Variable Approach
ERIC Educational Resources Information Center
Bornstein, Marc H.; Hahn, Chun-Shin; Putnick, Diane L.; Suwalsky, Joan T. D.
2014-01-01
This four-wave prospective longitudinal study evaluated stability of language in 324 children from early childhood to adolescence. Structural equation modeling supported loadings of multiple age-appropriate multisource measures of child language on single-factor core language skills at 20 months and 4, 10, and 14 years. Large stability…
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…
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…
Latent factor structure of a behavioral economic cigarette demand curve in adolescent smokers.
Bidwell, L Cinnamon; MacKillop, James; Murphy, James G; Tidey, Jennifer W; Colby, Suzanne M
2012-11-01
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); O(max) (i.e., maximum financial expenditure on cigarettes); P(max) (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. Copyright © 2012 Elsevier Ltd. All rights reserved.
On the explaining-away phenomenon in multivariate latent variable models.
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.
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.
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.
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.
Marcus, David K.; Barry, Tammy D.
2010-01-01
An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667–1078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators, for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD. PMID:20973595
Marcus, David K; Barry, Tammy D
2011-05-01
An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667 and 1,078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD.
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…
Fournet, Nathalie; Roulin, Jean-Luc; Monnier, Catherine; Atzeni, Thierry; Cosnefroy, Olivier; Le Gall, Didier; Roy, Arnaud
2015-01-01
The parent and teacher forms of the French version of the Behavioral Rating Inventory of Executive Function (BRIEF) were used to evaluate executive function in everyday life in a large sample of healthy children (N = 951) aged between 5 and 18. Several psychometric methods were applied, with a view to providing clinicians with tools for score interpretation. The parent and teacher forms of the BRIEF were acceptably reliable. Demographic variables (such as age and gender) were found to influence the BRIEF scores. Confirmatory factor analysis was then used to test five competing models of the BRIEF's latent structure. Two of these models (a three-factor model and a two-factor model, both based on a nine-scale structure) had a good fit. However, structural invariance with age was only obtained with the two-factor model. The French version of the BRIEF provides a useful measure of everyday executive function and can be recommended for use in clinical research and practice.
ERIC Educational Resources Information Center
Kelava, Augustin; Nagengast, Benjamin
2012-01-01
Structural equation models with interaction and quadratic effects have become a standard tool for testing nonlinear hypotheses in the social sciences. Most of the current approaches assume normally distributed latent predictor variables. In this article, we present a Bayesian model for the estimation of latent nonlinear effects when the latent…
Farmer, Richard F; Seeley, John R; Kosty, Derek B; Lewinsohn, Peter M
2009-11-01
Research on hierarchical modeling of psychopathology has frequently identified 2 higher order latent factors, internalizing and externalizing. When based on the comorbidity of psychiatric diagnoses, the externalizing domain has usually been modeled as a single latent factor. Multivariate studies of externalizing symptom features, however, suggest multidimensionality. To address this apparent contradiction, confirmatory factor analytic methods and information-theoretic criteria were used to evaluate 4 theoretically plausible measurement models based on lifetime comorbidity patterns of 7 putative externalizing disorders. Diagnostic information was collected at 4 assessment waves from an age-based cohort of 816 persons between the ages of 14 and 33. A 2-factor model that distinguished oppositional behavior disorders (attention-deficit/hyperactivity disorder, oppositional defiant disorder) from social norm violation disorders (conduct disorder, adult antisocial behavior, alcohol use disorder, cannabis use disorder, hard drug use disorder) demonstrated consistently good fit and superior approximating abilities. Analyses of psychosocial outcomes measured at the last assessment wave supported the validity of this 2-factor model. Implications of this research for the theoretical understanding of domain-related disorders and the organization of classification systems are discussed. PsycINFO Database Record 2009 APA, all rights reserved.
Structural equation models to estimate risk of infection and tolerance to bovine mastitis.
Detilleux, Johann; Theron, Léonard; Duprez, Jean-Noël; Reding, Edouard; Humblet, Marie-France; Planchon, Viviane; Delfosse, Camille; Bertozzi, Carlo; Mainil, Jacques; Hanzen, Christian
2013-03-06
One method to improve durably animal welfare is to select, as reproducers, animals with the highest ability to resist or tolerate infection. To do so, it is necessary to distinguish direct and indirect mechanisms of resistance and tolerance because selection on these traits is believed to have different epidemiological and evolutionary consequences. We propose structural equation models with latent variables (1) to quantify the latent risk of infection and to identify, among the many potential mediators of infection, the few ones that influence it significantly and (2) to estimate direct and indirect levels of tolerance of animals infected naturally with pathogens. We applied the method to two surveys of bovine mastitis in the Walloon region of Belgium, in which we recorded herd management practices, mastitis frequency, and results of bacteriological analyses of milk samples. Structural equation models suggested that, among more than 35 surveyed herd characteristics, only nine (age, addition of urea in the rations, treatment of subclinical mastitis, presence of dirty liner, cows with hyperkeratotic teats, machine stripping, pre- and post-milking teat disinfection, and housing of milking cows in cubicles) were directly and significantly related to a latent measure of bovine mastitis, and that treatment of subclinical mastitis was involved in the pathway between post-milking teat disinfection and latent mastitis. These models also allowed the separation of direct and indirect effects of bacterial infection on milk productivity. Results suggested that infected cows were tolerant but not resistant to mastitis pathogens. We revealed the advantages of structural equation models, compared to classical models, for dissecting measurements of resistance and tolerance to infectious diseases, here bovine mastitis. Using our method, we identified nine major risk factors that were directly associated with an increased risk of mastitis and suggested that cows were tolerant but not resistant to mastitis. Selection should aim at improved resistance to infection by mastitis pathogens, although further investigations are needed due to the limitations of the data used in this study.
The Attitudes to Ageing Questionnaire: Mokken Scaling Analysis
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
Electronic effects on melting: Comparison of aluminum cluster anions and cations
NASA Astrophysics Data System (ADS)
Starace, Anne K.; Neal, Colleen M.; Cao, Baopeng; Jarrold, Martin F.; Aguado, Andrés; López, José M.
2009-07-01
Heat capacities have been measured as a function of temperature for aluminum cluster anions with 35-70 atoms. Melting temperatures and latent heats are determined from peaks in the heat capacities; cohesive energies are obtained for solid clusters from the latent heats and dissociation energies determined for liquid clusters. The melting temperatures, latent heats, and cohesive energies for the aluminum cluster anions are compared to previous measurements for the corresponding cations. Density functional theory calculations have been performed to identify the global minimum energy geometries for the cluster anions. The lowest energy geometries fall into four main families: distorted decahedral fragments, fcc fragments, fcc fragments with stacking faults, and "disordered" roughly spherical structures. The comparison of the cohesive energies for the lowest energy geometries with the measured values allows us to interpret the size variation in the latent heats. Both geometric and electronic shell closings contribute to the variations in the cohesive energies (and latent heats), but structural changes appear to be mainly responsible for the large variations in the melting temperatures with cluster size. The significant charge dependence of the latent heats found for some cluster sizes indicates that the electronic structure can change substantially when the cluster melts.
Data-driven subtypes of major depressive disorder: a systematic review
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
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.
Reactivation of Latent HIV-1 Expression by Engineered TALE Transcription Factors
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
Bayesian Analysis of Structural Equation Models with Nonlinear Covariates and Latent Variables
ERIC Educational Resources Information Center
Song, Xin-Yuan; Lee, Sik-Yum
2006-01-01
In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…
The uPA/uPAR system regulates the bioavailability of PDGF-DD: implications for tumour growth.
Ehnman, M; Li, H; Fredriksson, L; Pietras, K; Eriksson, U
2009-01-29
Members of the platelet-derived growth factor (PDGF) family are mitogens for cells of mesenchymal origin and have important functions during embryonic development, blood vessel maturation, fibrotic diseases and cancer. In contrast to the two classical PDGFs, the novel and less well-characterized members, PDGF-CC and PDGF-DD, are latent factors that need to be processed extracellularly by activating proteases, before they can mediate PDGF receptor activation. Here, we elucidate the structural requirements for urokinase plasminogen activator (uPA)-mediated activation of PDGF-DD, as well as the intricate interplay with uPA receptor (uPAR) signalling. Furthermore, we show that activated PDGF-DD, in comparison to latent, more potently transforms NIH/3T3 cells in vitro. Conversely, xenograft studies in nude mice demonstrate that cells expressing latent PDGF-DD are more tumorigenic than those expressing activated PDGF-DD. These findings imply that a fine-tuned proteolytic activation, in the local milieu, controls PDGF-DD bioavailability. Moreover, we suggest that proteolytic activation of PDGF-DD reveals a retention motif mediating interactions with pericellular components. Our proposed mechanism, where uPA not only generates active PDGF-DD, but also regulates its spatial distribution, provides novel insights into the biological function of PDGF-DD.
Separate but Correlated: The Latent Structure of Space and Mathematics across Development
ERIC Educational Resources Information Center
Mix, Kelly S.; Levine, Susan C.; Cheng, Yi-Ling; Young, Chris; Hambrick, D. Zachary; Ping, Raedy
2016-01-01
The relations among various spatial and mathematics skills were assessed in a cross-sectional study of 854 children from kindergarten, third, and sixth grades (i.e., 5 to 13 years of age). Children completed a battery of spatial mathematics tests and their scores were submitted to exploratory factor analyses both within and across domains. In the…
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…
ERIC Educational Resources Information Center
Rohaan, Ellen J.; Taconis, Ruurd; Jochems, Wim M. G.
2011-01-01
In the study described in this article, primary school teachers' pedagogical content knowledge (PCK) of technology education was measured with a multiple choice test; the Teaching of Technology Test (TTT). The aim of the study was to explore the latent factor structure of PCK, which is considered to be a crucial and distinctive domain of teacher…
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…
ERIC Educational Resources Information Center
Dever, Bridget V.; Mays, Kristen L.; Kamphaus, Randy W.; Dowdy, Erin
2012-01-01
The BASC-2 Behavioral and Emotional Screening System Teacher, Child/Adolescent Form (BESS Teacher Form C/A; Kamphaus & Reynolds, 2007) is a brief teacher-report rating scale designed to identify students who are at-risk for behavioral and emotional problems. The aim of this study was to describe the latent dimensions that underlie the…
ERIC Educational Resources Information Center
Fortin, Laurier; Marcotte, Diane; Diallo, Thierno; Potvin, Pierre; Royer, Egide
2013-01-01
This study tests an empirical multidimensional model of school dropout, using data collected in the first year of an 8-year longitudinal study, with first year high school students aged 12-13 years. Structural equation modeling analyses show that five personal, family, and school latent factors together contribute to school dropout identified at…
ERIC Educational Resources Information Center
Mottram, Lisa; Donders, Jacobus
2005-01-01
The purpose of this study was to determine the latent structure of the California Verbal Learning Test--Children's Version (CVLT-C; D. Delis, J. Kramer, E.Kaplan, & B. Ober, 1994) in a sample of 175 children with traumatic brain injury (TBI). Maximum-likelihood confirmatory factor analyses were performed to test 6 competing hypothetical models…
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…
Lin, Philana Ling; Myers, Amy; Smith, Le’Kneitah; Bigbee, Carolyn; Bigbee, Matthew; Fuhrman, Carl; Grieser, Heather; Chiosea, Ion; Voitenek, Nikolai N.; Capuano, Saverio V.; Klein, Edwin; Flynn, JoAnne L.
2010-01-01
An increased risk of tuberculosis has been documented in humans treated with tumor necrosis factor alpha (TNF) neutralizing agents. In murine models, impaired signaling by TNF caused exacerbation of both acute and chronic infection associated with aberrant granuloma formation and maintenance. The non-human primate model of tuberculosis provides an opportunity to study immune modulation in the setting of TNF neutralization during primary and latent tuberculosis. Administration of TNF neutralizing agents prior to M. tuberculosis infection resulted in fulminant and disseminated disease by 8 weeks post-infection. Neutralization of TNF in latently infected cynomolgus macaques caused reactivation in a majority of animals as determined by gross pathology and bacterial burden. A spectrum of dissemination was noted including extrapulmonary disease. Surprisingly, monkeys who developed primary and reactivation tuberculosis after TNF neutralization had similar granuloma structure and composition compared to active control monkeys. TNF neutralization was associated with increased IL-12, decreased CCL4, increased chemokine receptor expression and reduced mycobacteria-specific IFN-γ production in blood but not to the affected mediastinal lymph nodes. Finally, the first signs of reactivation often occurred in thoracic lymph nodes. These findings have important clinical implications for determining the mechanism of TNF-neutralization-related tuberculosis. PMID:20112395
Gonzálvez, Carolina; Inglés, Cándido J.; Kearney, Christopher A.; Vicent, María; Sanmartín, Ricardo; García-Fernández, José M.
2016-01-01
The aim of this study was to analyze the factorial invariance and latent means differences of the Spanish version of the School Refusal Assessment Scale-Revised for Children (SRAS-R-C) in a sample of 1,078 students (50.8% boys) aged 8–11 years (M = 9.63, SD = 1.12). The results revealed that the proposed model in this study, with a structure of 18 items divided into four factors (Negative Affective, Social Aversion and/or Evaluation, To Pursue Attention and Tangible Reinforcements), was the best-fit model with a tetra-factorial structure, remaining invariant across gender and age. Analysis of latent means differences indicated that boys and 11-year-old students scored highest on the Tangible Reinforcements subscale compared with their 8- and 9-year-old peers. On the contrary, for the subscales of Social Aversion and/or Evaluation and to Pursue Attention, the differences were significant and higher in younger age groups compared to 11-year-olds. Appropriate indexes of reliability were obtained for SRAS-R-C subscales (0.70, 0.79, 0.87, and 0.72). Finally, the founded correlation coefficients of scores of the SRAS-R-C revealed a predictable pattern between school refusal and positive/negative affect and optimism/pessimism. PMID:28082938
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.
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.
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
Latent Heating Structures Derived from TRMM
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Smith, E. A.; Adler, R.; Hou, A.; Kakar, R.; Krishnamurti, T.; Kummerow, C.; Lang, S.; Olson, W.; Satoh, S.
2004-01-01
Rainfall is the fundamental variable within the Earth's hydrological cycle because it is both the main forcing term leading to variations in continental and oceanic surface water budgets. The vertical distribution of latent heat release, which is accompanied with rain, modulates large-scale meridional and zonal circulations within the tropics as well as modifying the energetic efficiency of mid-latitude weather systems. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water.This paper focuses on the retrieval of latent heat release from satellite measurements generated by the Tropical Rainfall Measuring Mission 0. The TRMM observatory, whose development was a joint US-Japan space endeavor, was launched in November 1997. TRMM measurements provide an accurate account of rainfall over the global tropics, information which can be .used to estimate the four-dimensional structure of latent heating across the entire tropical and sub-tropical regions. Various algorithm methodologies for estimating latent heating based on rain rate measurements from TRMM observations are described. The strengths and weaknesses of these algorithms, as well as the latent heating products generated by these algorithms, are also discussed along with validation analyses of the products. The investigation paper provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, and concludes with remarks designed to stimulate further research on latent heating retrieval
Zhang, Xiuming; Mormino, Elizabeth C; Sun, Nanbo; Sperling, Reisa A; Sabuncu, Mert R; Yeo, B T Thomas
2016-10-18
We used a data-driven Bayesian model to automatically identify distinct latent factors of overlapping atrophy patterns from voxelwise structural MRIs of late-onset Alzheimer's disease (AD) dementia patients. Our approach estimated the extent to which multiple distinct atrophy patterns were expressed within each participant rather than assuming that each participant expressed a single atrophy factor. The model revealed a temporal atrophy factor (medial temporal cortex, hippocampus, and amygdala), a subcortical atrophy factor (striatum, thalamus, and cerebellum), and a cortical atrophy factor (frontal, parietal, lateral temporal, and lateral occipital cortices). To explore the influence of each factor in early AD, atrophy factor compositions were inferred in beta-amyloid-positive (Aβ+) mild cognitively impaired (MCI) and cognitively normal (CN) participants. All three factors were associated with memory decline across the entire clinical spectrum, whereas the cortical factor was associated with executive function decline in Aβ+ MCI participants and AD dementia patients. Direct comparison between factors revealed that the temporal factor showed the strongest association with memory, whereas the cortical factor showed the strongest association with executive function. The subcortical factor was associated with the slowest decline for both memory and executive function compared with temporal and cortical factors. These results suggest that distinct patterns of atrophy influence decline across different cognitive domains. Quantification of this heterogeneity may enable the computation of individual-level predictions relevant for disease monitoring and customized therapies. Factor compositions of participants and code used in this article are publicly available for future research.
The development of the Problematic Online Gaming Questionnaire (POGQ).
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.
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.
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.
A Systematic Approach for Identifying Level-1 Error Covariance Structures in Latent Growth Modeling
ERIC Educational Resources Information Center
Ding, Cherng G.; Jane, Ten-Der; Wu, Chiu-Hui; Lin, Hang-Rung; Shen, Chih-Kang
2017-01-01
It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which,…
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.
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.
Burns, G Leonard; Walsh, James A; Servera, Mateu; Lorenzo-Seva, Urbano; Cardo, Esther; Rodríguez-Fornells, Antoni
2013-01-01
Exploratory structural equation modeling (SEM) was applied to a multiple indicator (26 individual symptom ratings) by multitrait (ADHD-IN, ADHD-HI and ODD factors) by multiple source (mothers, fathers and teachers) model to test the invariance, convergent and discriminant validity of the Child and Adolescent Disruptive Behavior Inventory with 872 Thai adolescents and the ADHD Rating Scale-IV and ODD scale of the Disruptive Behavior Inventory with 1,749 Spanish children. Most of the individual ADHD/ODD symptoms showed convergent and discriminant validity with the loadings and thresholds being invariant over mothers, fathers and teachers in both samples (the three latent factor means were higher for parents than teachers). The ADHD-IN, ADHD-HI and ODD latent factors demonstrated convergent and discriminant validity between mothers and fathers within the two samples. Convergent and discriminant validity between parents and teachers for the three factors was either absent (Thai sample) or only partial (Spanish sample). The application of exploratory SEM to a multiple indicator by multitrait by multisource model should prove useful for the evaluation of the construct validity of the forthcoming DSM-V ADHD/ODD rating scales.
Multilevel Higher-Order Item Response Theory Models
ERIC Educational Resources Information Center
Huang, Hung-Yu; Wang, Wen-Chung
2014-01-01
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
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…
ERIC Educational Resources Information Center
Pek, Jolynn; Losardo, Diane; Bauer, Daniel J.
2011-01-01
Compared to parametric models, nonparametric and semiparametric approaches to modeling nonlinearity between latent variables have the advantage of recovering global relationships of unknown functional form. Bauer (2005) proposed an indirect application of finite mixtures of structural equation models where latent components are estimated in the…
ERIC Educational Resources Information Center
Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S.
2012-01-01
A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…
Wang, Li; Cao, Xing; Cao, Chengqi; Fang, Ruojiao; Yang, Haibo; Elhai, Jon D
2017-12-01
This study investigated the latent structure of DSM-5 PTSD symptoms using two-wave longitudinal data collected from a sample of adolescents exposed to an explosion accident. Two waves of surveys were conducted approximately 3 and 8 months after the accident, respectively. A total of 836 students completed the baseline survey, and 762 students completed the follow-up survey. The results of confirmatory factor analyses(CFA) indicated that a seven-factor hybrid model composed of intrusion, avoidance, negative affect, anhedonia, externalizing behaviors, anxious arousal and dysphoric arousal factors yielded significantly better data fit at both waves than the other models including the DSM-5 four-factor model, the six-factor anhedonia and externalizing behaviors models. Furthermore, the results of CFA invariance tests supported the longitudinal invariance of the model. Implications and limitations in terms of these results are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.
The Factor Structure of the Aggression Questionnaire With Violent Offenders.
Pettersen, Cathrine; Nunes, Kevin L; Cortoni, Franca
2018-05-01
The Buss-Perry Aggression Questionnaire (AQ) is a self-report measure of aggressiveness commonly employed in nonforensic and forensic settings and is included in violent offender pre- and posttreatment assessment batteries. The aim of the current study was to assess the fit of the four-factor model of the AQ with violent offenders ( N = 271), a population for which the factor structure of the English version of the AQ has not previously been examined. Confirmatory factor analyses did not yield support for the four-factor model of the original 29-item AQ. Acceptable fit was obtained with the 12-item short form, but careful examination of the relationships between the latent factors revealed that the four subscales of the AQ may not represent distinct aspects of aggressiveness. Our findings call into question whether the AQ optimally measures trait aggressiveness among violent offenders.
Dynamic Latent Trait Models with Mixed Hidden Markov Structure for Mixed Longitudinal Outcomes.
Zhang, Yue; Berhane, Kiros
2016-01-01
We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMM). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study (CHS) to jointly model questionnaire based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.
Selection of latent variables for multiple mixed-outcome models
ZHOU, LING; LIN, HUAZHEN; SONG, XINYUAN; LI, YI
2014-01-01
Latent variable models have been widely used for modeling the dependence structure of multiple outcomes data. However, the formulation of a latent variable model is often unknown a priori, the misspecification will distort the dependence structure and lead to unreliable model inference. Moreover, multiple outcomes with varying types present enormous analytical challenges. In this paper, we present a class of general latent variable models that can accommodate mixed types of outcomes. We propose a novel selection approach that simultaneously selects latent variables and estimates parameters. We show that the proposed estimator is consistent, asymptotically normal and has the oracle property. The practical utility of the methods is confirmed via simulations as well as an application to the analysis of the World Values Survey, a global research project that explores peoples’ values and beliefs and the social and personal characteristics that might influence them. PMID:27642219
Mannarini, Stefania; Boffo, Marilisa; Rossi, Alessandro; Balottin, Laura
2017-01-01
Background: Although scientific research on the etiology of mental disorders has improved the knowledge of biogenetic and psychosocial aspects related to the onset of mental illness, stigmatizing attitudes and behaviors are still very prevalent and pose a significant social problem. Aim: The aim of this study was to deepen the knowledge of how attitudes toward people with mental illness are affected by specific personal beliefs and characteristics, such as culture and religion of the perceiver. More precisely, the main purpose is the definition of a structure of variables, namely perceived dangerousness, social closeness, and avoidance of the ill person, together with the beliefs about the best treatment to be undertaken and the sick person' gender, capable of describing the complexity of the stigma construct in particular as far as schizophrenia is concerned. Method: The study involved 305 university students, 183 from the University of Padua, Italy, and 122 from the University of Haifa, Israel. For the analyses, a latent class analysis (LCA) approach was chosen to identify a latent categorical structure accounting for the covariance between the observed variables. Such a latent structure was expected to be moderated by cultural background (Italy versus Israel) and religious beliefs, whereas causal beliefs, recommended treatment, dangerousness, social closeness, and public avoidance were the manifest variables, namely the observed indicators of the latent variable. Results: Two sets of results were obtained. First, the relevance of the manifest variables as indicators of the hypothesized latent variable was highlighted. Second, a two-latent-class categorical dimension represented by prejudicial attitudes, causal beliefs, and treatments concerning schizophrenia was found. Specifically, the differential effects of the two cultures and the religious beliefs on the latent structure and their relations highlighted the relevance of the observed variables as indicators of the expected latent variable. Conclusion: The present study contributes to the improvement of the understanding of how attitudes toward people with mental illness are affected by specific personal beliefs and characteristics of the perceiver. The definition of a structure of variables capable of describing the complexity of the stigma construct in particular as far as schizophrenia is concerned was achieved from a cross-cultural perspective.
Kane, Michael J; Hambrick, David Z; Tuholski, Stephen W; Wilhelm, Oliver; Payne, Tabitha W; Engle, Randall W
2004-06-01
A latent-variable study examined whether verbal and visuospatial working memory (WM) capacity measures reflect a primarily domain-general construct by testing 236 participants in 3 span tests each of verbal WM. visuospatial WM, verbal short-term memory (STM), and visuospatial STM. as well as in tests of verbal and spatial reasoning and general fluid intelligence (Gf). Confirmatory' factor analyses and structural equation models indicated that the WM tasks largely reflected a domain-general factor, whereas STM tasks, based on the same stimuli as the WM tasks, were much more domain specific. The WM construct was a strong predictor of Gf and a weaker predictor of domain-specific reasoning, and the reverse was true for the STM construct. The findings support a domain-general view of WM capacity, in which executive-attention processes drive the broad predictive utility of WM span measures, and domain-specific storage and rehearsal processes relate more strongly to domain-specific aspects of complex cognition. ((c) 2004 APA, all rights reserved)
Cruz-Roa, Angel; Díaz, Gloria; Romero, Eduardo; González, Fabio A.
2011-01-01
Histopathological images are an important resource for clinical diagnosis and biomedical research. From an image understanding point of view, the automatic annotation of these images is a challenging problem. This paper presents a new method for automatic histopathological image annotation based on three complementary strategies, first, a part-based image representation, called the bag of features, which takes advantage of the natural redundancy of histopathological images for capturing the fundamental patterns of biological structures, second, a latent topic model, based on non-negative matrix factorization, which captures the high-level visual patterns hidden in the image, and, third, a probabilistic annotation model that links visual appearance of morphological and architectural features associated to 10 histopathological image annotations. The method was evaluated using 1,604 annotated images of skin tissues, which included normal and pathological architectural and morphological features, obtaining a recall of 74% and a precision of 50%, which improved a baseline annotation method based on support vector machines in a 64% and 24%, respectively. PMID:22811960
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…
ERIC Educational Resources Information Center
Carlson, Thomas Stone; McGeorge, Christi R.; Toomey, Russell B.
2013-01-01
This study established the validity and factor structure of the Affirmative Training Inventory (ATI; T. S. Carlson, C. R. McGeorge & M. Rock, unpublished) as a measure of lesbian, gay, and bisexual (LGB) affirmative clinical training. Additionally, this study examined the latent associations among the subscales of the ATI and the Sexual…
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
Examining the Latent Structure of the Delis-Kaplan Executive Function System.
Karr, Justin E; Hofer, Scott M; Iverson, Grant L; Garcia-Barrera, Mauricio A
2018-05-04
The current study aimed to determine whether the Delis-Kaplan Executive Function System (D-KEFS) taps into three executive function factors (inhibition, shifting, fluency) and to assess the relationship between these factors and tests of executive-related constructs less often measured in latent variable research: reasoning, abstraction, and problem solving. Participants included 425 adults from the D-KEFS standardization sample (20-49 years old; 50.1% female; 70.1% White). Eight alternative measurement models were compared based on model fit, with test scores assigned a priori to three factors: inhibition (Color-Word Interference, Tower), shifting (Trail Making, Sorting, Design Fluency), and fluency (Verbal/Design Fluency). The Twenty Questions, Word Context, and Proverb Tests were predicted in separate structural models. The three-factor model fit the data well (CFI = 0.938; RMSEA = 0.047), although a two-factor model, with shifting and fluency merged, fit similarly well (CFI = 0.929; RMSEA = 0.048). A bifactor model fit best (CFI = 0.977; RMSEA = 0.032) and explained the most variance in shifting indicators, but rarely converged among 5,000 bootstrapped samples. When the three first-order factors simultaneously predicted the criterion variables, only shifting was uniquely predictive (p < .05; R2 = 0.246-0.408). The bifactor significantly predicted all three criterion variables (p < .001; R2 = 0.141-242). Results supported a three-factor D-KEFS model (i.e., inhibition, shifting, and fluency), although shifting and fluency were highly related (r = 0.696). The bifactor showed superior fit, but converged less often than other models. Shifting best predicted tests of reasoning, abstraction, and problem solving. These findings support the validity of D-KEFS scores for measuring executive-related constructs and provide a framework through which clinicians can interpret D-KEFS results.
An investigation of PTSD's core dimensions and relations with anxiety and depression.
Byllesby, Brianna M; Durham, Tory A; Forbes, David; Armour, Cherie; Elhai, Jon D
2016-03-01
Posttraumatic stress disorder (PTSD) is highly comorbid with anxiety and depressive disorders, which is suggestive of shared variance or common underlying dimensions. The purpose of the present study was to examine the relationship between the latent factors of PTSD with the constructs of anxiety and depression in order to increase understanding of the co-occurrence of these disorders. Data were collected from a nonclinical sample of 186 trauma-exposed participants using the PTSD Checklist and Hospital Anxiety and Depression Scale. Confirmatory factor analyses were conducted to determine model fit comparing 3 PTSD factor structure models, followed by Wald tests comparing the relationships between PTSD factors and the core dimensions of anxiety and depression. In model comparisons, the 5-factor dysphoric arousal model of PTSD provided the best fit for the data, compared to the emotional numbing and dysphoria models of PTSD. Compared to anxious arousal, the dysphoric arousal and numbing factors of PTSD were more related to depression severity. Numbing, anxious arousal, and dysphoric arousal were not differentially related to the latent anxiety factor. The underlying factors of PTSD contain aspects of the core dimensions of both anxiety and depression. The heterogeneity of PTSD's associations with anxiety and depressive constructs requires additional empirical exploration because clarification regarding these relationships will impact diagnostic classification as well as clinical practice. (c) 2016 APA, all rights reserved).
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.
Perceptions of care in women sent home in latent labor.
Hosek, Claire; Faucher, Mary Ann; Lankford, Janice; Alexander, James
2014-01-01
To assess perceptions of care from woman discharged from an obstetrical (OB) triage unit or a labor and delivery unit with a diagnosis of false or latent labor in order to determine factors that may increase or decrease the woman's satisfaction with care. Descriptive, convenience sample. One hundred low-income pregnant women at term presenting for care in latent labor consented to participate in a telephone survey. The survey was based on the relevant research about care of women in early labor and the Donabedian quality improvement framework assessing structure, process, and outcomes of care. Forty-one percent of women did not want to be discharged home in latent labor. Common reasons included women stating they were in too much pain or they were living too far from the birth setting. Eating, drinking, and comfort measures were the most common measures women cited that would have made them feel better when in the hospital. A reoccurring response from women was their desire for very clear and specific written instructions about how to stay comfortable at home and when to return to the hospital. Comfort measures in the birth setting, including in triage, should include a variety of options including ambulation and oral nutrition. Detailed and specific written instructions about early labor and staying comfortable while at home have value for women in this survey regarding their perceptions of care. Results from this survey of low-income women suggest that a subset of women in latent labor just do not want to go home and this may be related to having too much pain and/or travel distance to the hospital. Hospital birth settings also have an opportunity to create a care environment that provides services and embodies attributes that women report as important for their satisfaction with care in latent labor.
Wang, Li; Long, Di; Li, Zhongquan; Armour, Cherie
2011-07-01
This present study examined the structure of posttraumatic stress disorder (PTSD) symptoms in a large sample of Chinese adolescents exposed to a deadly earthquake. A total of 2,800 middle school students aged 12 to 18 years participated in the study 6 months after the "Wenchuan Earthquake". Results of confirmatory factor analysis indicated that a five-factor intercorrelated model composed of intrusion, avoidance, numbing, dysphoric arousal, and anxious arousal, fit data significantly better than both the four-factor numbing model King et al. (Psychological Assessment 10:90-96, 1998) and the four-factor dysphoria model Simms et al. (Journal of Abnormal Psychology 111:637-647, 2002). Further examination of the external convergent and discriminant validity revealed that except for the dysphoric arousal factor, the remaining four PTSD factors yielded significantly different correlations with external measures of anxiety vs. depression. The findings add to the limited literature on the factor structure of PTSD in youths and on the five-factor PTSD model. In addition, they provide more detail into the latent psychopathological processes of PTSD, and inform the forthcoming DSM-5.
Palmieri, Patrick A; Weathers, Frank W; Difede, JoAnn; King, Dainel W
2007-05-01
Although posttraumatic stress disorder (PTSD) factor analytic research has yielded little support for the DSM-IV 3-factor model of reexperiencing, avoidance, and hyperarousal symptoms, no clear consensus regarding alternative models has emerged. One possible explanation is differential instrumentation across studies. In the present study, the authors used confirmatory factor analysis to compare a self-report measure, the PTSD Checklist (PCL), and a structured clinical interview, the Clinician-Administered PTSD Scale (CAPS), in 2,960 utility workers exposed to the World Trade Center Ground Zero site. Although two 4-factor models fit adequately for each measure, the latent structure of the PCL was slightly better represented by correlated reexperiencing, avoidance, dysphoria, and hyperarousal factors, whereas that of the CAPS was slightly better represented by correlated reexperiencing, avoidance, emotional numbing, and hyperarousal factors. After accounting for method variance, the model specifying dysphoria as a distinct factor achieved slightly better fit. Patterns of correlations with external variables provided additional support for the dysphoria model. Implications regarding the underlying structure of PTSD are discussed.
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.
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.
Maximum Likelihood Estimation of Nonlinear Structural Equation Models with Ignorable Missing Data
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Lee, Sik-Yum; Song, Xin-Yuan; Lee, John C. K.
2003-01-01
The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among latent variables with fully observed data. However, in social and behavioral sciences, nonlinear relationships among the latent variables are important for establishing more meaningful models…
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Meece, Darrell
1999-01-01
This study proposes a model of associations between young children's social cognition and their social behavior with peers. In this model, two latent structures -children's representations of peer relationships and emotion regulation -- predict children's competent, prosocial, withdrawn, and aggressive behavior. Moreover, the model proposes that…
The Latent Structure of Secure Base Script Knowledge
ERIC Educational Resources Information Center
Waters, Theodore E. A.; Fraley, R. Chris; Groh, Ashley M.; Steele, Ryan D.; Vaughn, Brian E.; Bost, Kelly K.; Veríssimo, Manuela; Coppola, Gabrielle; Roisman, Glenn I.
2015-01-01
There is increasing evidence that attachment representations abstracted from childhood experiences with primary caregivers are organized as a cognitive script describing secure base use and support (i.e., the "secure base script"). To date, however, the latent structure of secure base script knowledge has gone unexamined--this despite…
Bornstein, Marc H.; Hahn, Chun-Shin; Putnick, Diane L.; Suwalsky, Joan T. D.
2014-01-01
This four-wave prospective longitudinal study evaluated stability of language in 324 children from early childhood to adolescence. Structural equation modeling supported loadings of multiple age-appropriate multi-source measures of child language on single-factor core language skills at 20 months and 4, 10, and 14 years. Large stability coefficients (standardized indirect effect = .46) were obtained between language latent variables from early childhood to adolescence and accounting for child nonverbal intelligence and social competence and maternal verbal intelligence, education, speech, and social desirability. Stability coefficients were similar for girls and boys. Stability of core language skill was stronger from 4 to 10 to 14 years than from 20 months to 4 years, so early intervention to improve lagging language is recommended. PMID:25165797
Nonlinear Structured Growth Mixture Models in M"plus" and OpenMx
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Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne
2010-01-01
Growth mixture models (GMMs; B. O. Muthen & Muthen, 2000; B. O. Muthen & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models…
Software for the Application of Discrete Latent Structure Models to Item Response Data.
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Haertel, Edward H.
These FORTRAN programs and MATHEMATICA routines were developed in the course of a research project titled "Achievement and Assessment in School Science: Modeling and Mapping Ability and Performance." Their use is described in other publications from that project, including "Latent Traits or Latent States? The Role of Discrete Models…
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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…
Higher-Order Item Response Models for Hierarchical Latent Traits
ERIC Educational Resources Information Center
Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming
2013-01-01
Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…
Space-time latent component modeling of geo-referenced health data.
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.
Morphological and motor characteristics of Croatian first league female football players.
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.
Brooks, Billy; McBee, Matthew; Pack, Robert; Alamian, Arsham
2017-05-01
Rates of accidental overdose mortality from substance use disorder (SUD) have risen dramatically in the United States since 1990. Between 1999 and 2004 alone rates increased 62% nationwide, with rural overdose mortality increasing at a rate 3 times that seen in urban populations. Cultural differences between rural and urban populations (e.g., educational attainment, unemployment rates, social characteristics, etc.) affect the nature of SUD, leading to disparate risk of overdose across these communities. Multiple-groups latent class analysis with covariates was applied to data from the 2011 and 2012 National Survey on Drug Use and Health (n=12.140) to examine potential differences in latent classifications of SUD between rural and urban adult (aged 18years and older) populations. Nine drug categories were used to identify latent classes of SUD defined by probability of diagnosis within these categories. Once the class structures were established for rural and urban samples, posterior membership probabilities were entered into a multinomial regression analysis of socio-demographic predictors' association with the likelihood of SUD latent class membership. Latent class structures differed across the sub-groups, with the rural sample fitting a 3-class structure (Bootstrap Likelihood Ratio Test P value=0.03) and the urban fitting a 6-class model (Bootstrap Likelihood Ratio Test P value<0.0001). Overall the rural class structure exhibited less diversity in class structure and lower prevalence of SUD in multiple drug categories (e.g. cocaine, hallucinogens, and stimulants). This result supports the hypothesis that different underlying elements exist in the two populations that affect SUD patterns, and thus can inform the development of surveillance instruments, clinical services, and prevention programming tailored to specific communities. Copyright © 2017 Elsevier Ltd. All rights reserved.
Liu, Yi; Luo, Bi-Ru
2016-11-20
To analyze the factors affecting maternal physical activities at different stages among pregnant women. Self-designed questionnaires were used to investigate the physical activities of women in different stages, including 650 in the first, 650 in the second, and 750 in the third trimester of pregnancy. The factors affecting maternal physical activities were analyzed using the structural equation model that comprised 4 latent variables (attitude, norm, behavioral attention and behavior) with observed variables that matched the latent variables. The participants ranged from 18 to 35 years of age. The women and their husbands, but not their mothers or mothers-in-law, were all well educated. The caregiver during pregnancy was mostly the mother followed by the husband. For traveling, the women in the first, second and third trimesters preferred walking, bus, and personal escort, respectively; the main physical activity was walking in all trimesters, and the women in different trimester were mostly sedentary, a greater intensity of exercise was associated with less exercise time. Structural equation modeling (SEM) analysis showed that the physical activities of pregnant women was affected by behavioral intention (with standardized regression coefficient of 0.372); attitude and subjective norms affected physical activity by indirectly influencing the behavior intention (standardized regression coefficients of 0.140 and 0.669). The pregnant women in different stages have inappropriate physical activities with insufficient exercise time and intensity. The subjective norms affects the physical activities of the pregnant women by influencing their attitudes and behavior intention indirectly, suggesting the need of health education of the caregivers during pregnancy.
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.
Missing Modality Transfer Learning via Latent Low-Rank Constraint.
Ding, Zhengming; Shao, Ming; Fu, Yun
2015-11-01
Transfer learning is usually exploited to leverage previously well-learned source domain for evaluating the unknown target domain; however, it may fail if no target data are available in the training stage. This problem arises when the data are multi-modal. For example, the target domain is in one modality, while the source domain is in another. To overcome this, we first borrow an auxiliary database with complete modalities, then consider knowledge transfer across databases and across modalities within databases simultaneously in a unified framework. The contributions are threefold: 1) a latent factor is introduced to uncover the underlying structure of the missing modality from the known data; 2) transfer learning in two directions allows the data alignment between both modalities and databases, giving rise to a very promising recovery; and 3) an efficient solution with theoretical guarantees to the proposed latent low-rank transfer learning algorithm. Comprehensive experiments on multi-modal knowledge transfer with missing target modality verify that our method can successfully inherit knowledge from both auxiliary database and source modality, and therefore significantly improve the recognition performance even when test modality is inaccessible in the training stage.
Garner, Annie A.; Peugh, James; Becker, Stephen P.; Kingery, Kathleen M.; Tamm, Leanne; Vaughn, Aaron J.; Ciesielski, Heather; Simon, John O.; Loren, Richard E. A.; Epstein, Jeffery N.
2014-01-01
Objective Studies demonstrate sluggish cognitive tempo (SCT) symptoms to be distinct from inattentive and hyperactive-impulsive dimensions of Attention-Deficit/Hyperactivity Disorder (ADHD). No study has examined SCT within a bi-factor model of ADHD whereby SCT may form a specific factor distinct from inattention and hyperactivity/impulsivity while still fitting within a general ADHD factor, which was the purpose of the current study. Method 168 children were recruited from an ADHD clinic. Most (92%) met diagnostic criteria for ADHD. Parents and teachers completed measures of ADHD and SCT. Results Although SCT symptoms were strongly associated with inattention they loaded onto a factor independent of ADHD ‘g’. Results were consistent across parent and teacher ratings. Conclusions SCT is structurally distinct from inattention as well as from the general ADHD latent symptom structure. Findings support a growing body of research suggesting SCT to be distinct and separate from ADHD. PMID:25005039
Factor structure of a standards-based inventory of competencies in social work with groups.
Macgowan, Mark J; Dillon, Frank R; Spadola, Christine E
2018-01-01
This study extends previous findings on a measure of competencies based on Standards for Social Work Practice with Groups. The Inventory of Competencies in Social Work with Groups (ICSWG) measures confidence in performing the Standards. This study examines the latent structure of the Inventory, while illuminating the underlying structure of the Standards. A multinational sample of 586 persons completed the ICSWG. Exploratory factor analysis (EFA), reliability estimates, standard error of measurement estimates, and a range of validity tests were conducted. The EFA yielded a six-factor solution consisting of core values, mutuality/connectivity, collaboration, and three phases of group development (planning, beginnings/middles, endings). The alphas were .98 for the scale and ranged from .85 to .95 for the subscales. Correlations between the subscales and validators supported evidence of construct validity. The findings suggest key group work domains that should be taught and practiced in social work with groups.
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
Interexaminer variation of minutia markup on latent fingerprints.
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.
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Walters, Glenn D.; Rogers, Richard; Berry, David T. R.; Miller, Holly A.; Duncan, Scott A.; McCusker, Paul J.; Payne, Joshua W.; Granacher, Robert P., Jr.
2008-01-01
The 6 nonoverlapping primary scales of the Structured Interview of Reported Symptoms (SIRS) were subjected to taxometric analysis in a group of 1,211 criminal and civil examinees in order to investigate the latent structure of feigned psychopathology. Both taxometric procedures used in this study, mean above minus below a cut (MAMBAC) and maximum…
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…
Latent structure of the Wisconsin Card Sorting Test: a confirmatory factor analytic study.
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.
Gottlieb, Daniel H.; Capitanio, John P.
2012-01-01
The human intruder test is a testing paradigm designed to measure rhesus macaques’ behavioral responses to a stressful and threatening situation. In the test, an unfamiliar human positions him/herself in various threatening positions relative to a caged macaque. This paradigm has been utilized for over twenty years to measure a variety of behavioral constructs, including fear and anxiety, behavioral inhibition, emotionality, and aggression. To date there have been no attempts to evaluate comprehensively the structure of the behavioral responses to the test. Our first goal was to identify the underlying latent factors affecting the different responses among subjects, and our second goal was determine if rhesus reared in different environments respond differently in this testing paradigm. To accomplish this, we first performed exploratory and confirmatory factor analyses on the behavioral responses of 3–4 month-old rhesus macaques, utilizing data from over 2,000 separate tests conducted between 2001–2007. Using the resulting model, we then tested to see whether early rearing experience affected responses in the test. Our first analyses suggested that most of the variation in infant behavioral responses to the human intruder test could be explained by four latent factors: “Activity,” “Emotionality,” “Aggression,” and “Displacement.” Our second analyses revealed a significant effect of rearing condition for each factor score (P < 0.001); most notable socially-reared animals had the lowest Activity score (P < 0.001), indoor mother-reared animals had the highest Displacement score (P < 0.001), and nursery-reared animals had the highest Emotionality (P < 0.001) and lowest Aggression scores (P < 0.001). These results demonstrate that this standardized testing paradigm reveals multiple patterns of response, which are influenced by an animal’s rearing history. PMID:23229557
Gottlieb, Daniel H; Capitanio, John P
2013-04-01
The human intruder test is a testing paradigm designed to measure rhesus macaques' behavioral responses to a stressful and threatening situation. In the test, an unfamiliar human positions him/herself in various threatening positions relative to a caged macaque. This paradigm has been utilized for over 20 years to measure a variety of behavioral constructs, including fear and anxiety, behavioral inhibition, emotionality, and aggression. To date, there have been no attempts to evaluate comprehensively the structure of the behavioral responses to the test. Our first goal was to identify the underlying latent factors affecting the different responses among subjects, and our second goal was to determine if rhesus reared in different environments respond differently in this testing paradigm. To accomplish this, we first performed exploratory and confirmatory factor analyses on the behavioral responses of 3- to 4-month-old rhesus macaques, utilizing data from over 2,000 separate tests conducted between 2001-2007. Using the resulting model, we then tested to see whether early rearing experience affected responses in the test. Our first analyses suggested that most of the variation in infant behavioral responses to the human intruder test could be explained by four latent factors: "activity," "emotionality," "aggression," and "displacement." Our second analyses revealed a significant effect of rearing condition for each factor score (P < 0.001); most notable socially reared animals had the lowest activity score (P < 0.001), indoor mother-reared animals had the highest displacement score (P < 0.001), and nursery-reared animals had the highest emotionality (P < 0.001) and lowest aggression scores (P < 0.001). These results demonstrate that this standardized testing paradigm reveals multiple patterns of response, which are influenced by an animal's rearing history. © 2012 Wiley Periodicals, Inc.
Kendler, K S; Gardner, C O
2017-07-01
This study seeks to clarify the contribution of temporally stable and occasion-specific genetic and environmental influences on risk for major depression (MD). Our sample was 2153 members of female-female twin pairs from the Virginia Twin Registry. We examined four personal interview waves conducted over an 8-year period with MD in the last year defined by DSM-IV criteria. We fitted a structural equation model to the data using classic Mx. The model included genetic and environmental risk factors for a latent, stable vulnerability to MD and for episodes in each of the four waves. The best-fit model was simple and included genetic and unique environmental influences on the latent liability to MD and unique wave-specific environmental effects. The path from latent liability to MD in the last year was constant over time, moderate in magnitude (+0.65) and weaker than the impact of occasion-specific environmental effects (+0.76). Heritability of the latent stable liability to MD was much higher (78%) than that estimated for last-year MD (32%). Of the total unique environmental influences on MD, 13% reflected enduring consequences of earlier environmental insults, 17% diagnostic error and 70% wave-specific short-lived environmental stressors. Both genetic influences on MD and MD heritability are stable over middle adulthood. However, the largest influence on last-year MD is short-lived environmental effects. As predicted by genetic theory, the heritability of MD is increased substantially by measurement at multiple time points largely through the reduction of the effects of measurement error and short-term environmental risk factors.
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.
Conway, Christopher C.; Starr, Lisa R.; Espejo, Emmanuel P.; Brennan, Patricia A.; Hammen, Constance
2016-01-01
Biased stress appraisals critically relate to the origins and temporal course of many—perhaps most—forms of psychopathology. We hypothesized that aberrant stress appraisals are linked directly to latent internalizing and externalizing traits that, in turn, predispose to multiple disorders. A high-risk community sample of 815 adolescents underwent semistructured interviews to assess clinical disorders and naturalistic stressors at ages 15 and 20. Participants and blind rating teams separately evaluated the threat associated with acute stressors occurring in the past year, and an appraisal bias index (i.e., discrepancy between subjective and team-rated threat) was generated. A two-factor (Internalizing and Externalizing) latent variable model provided an excellent fit to the diagnostic correlations. After adjusting for the covariation between the factors, adolescents’ threat overestimation prospectively predicted higher standing on Internalizing, whereas threat underestimation prospectively predicted elevations on Externalizing. Cross-sectional analyses replicated this pattern in early adulthood. Appraisals were not related to the residual portions of any diagnosis in the latent variable model, suggesting that the transdiagnostic dimensions mediated the connections between stress appraisal bias and disorder entities. We discuss implications for enhancing the efficiency of emerging research on the stress response and speculate how these findings, if replicated, might guide refinements to psychological treatments for stress-linked disorders. PMID:27819469
ERIC Educational Resources Information Center
Marsh, Herbert W.; Wen, Zhonglin; Hau, Kit-Tai; Little, Todd D.; Bovaird, James A.; Widaman, Keith F.
2007-01-01
Little, Bovaird and Widaman (2006) proposed an unconstrained approach with residual centering for estimating latent interaction effects as an alternative to the mean-centered approach proposed by Marsh, Wen, and Hau (2004, 2006). Little et al. also differed from Marsh et al. in the number of indicators used to infer the latent interaction factor…
Using Structural Equation Models with Latent Variables to Study Student Growth and Development.
ERIC Educational Resources Information Center
Pike, Gary R.
1991-01-01
Analysis of data on freshman-to-senior developmental gains in 722 University of Tennessee-Knoxville students provides evidence of the advantages of structural equation modeling with latent variables and suggests that the group differences identified by traditional analysis of variance and covariance techniques may be an artifact of measurement…
The Latent Structure of Psychopathy in Youth: A Taxometric Investigation
ERIC Educational Resources Information Center
Vasey, Michael W.; Kotov, Roman; Frick, Paul J.; Loney, Bryan R.
2005-01-01
Using taxometric procedures, the latent structure of psychopathy was investigated in two studies of children and adolescents. Prior studies have identified a taxon (i.e., a natural category) associated with antisocial behavior in adults as well as children and adolescents. However, features of this taxon suggest that it is not psychopathy but…
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
Race Differences in Patterns of Risky Behavior and Associated Risk Factors in Adolescence.
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.
Kendler, Kenneth S; Myers, John; Torgersen, Svenn; Neale, Michael C; Reichborn-Kjennerud, Ted
2007-05-01
Personality disorders (PDs) as assessed by questionnaires and personal interviews are heritable. However, we know neither how much unreliability of measurement impacts on heritability estimates nor whether the genetic and environmental risk factors assessed by these two methods are the same. We wish to know whether the same set of PD vulnerability factors are assessed by these two methods. A total of 3334 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP) completed a questionnaire containing 91 PD items. One to 6 years later, 1386 of these pairs were interviewed with the Structured Interview for DSM-IV Personality (SIDP-IV). Self-report items predicting interview results were selected by regression. Measurement models were fitted using Mx. In the best-fit models, the latent liabilities to paranoid personality disorder (PPD), schizoid personality disorder (SPD) and schizotypal personality disorder (STPD) were all highly heritable with no evidence of shared environmental effects. For PPD and STPD, only unique environmental effects were specific to the interview measure whereas both environmental and genetic effects were found to be specific to the questionnaire assessment. For SPD, the best-fit model contained genetic and environmental effects specific to both forms of assessment. The latent liabilities to the cluster A PDs are highly heritable but are assessed by current methods with only moderate reliability. The personal interviews assessed the genetic risk for the latent trait with excellent specificity for PPD and STPD and good specificity for SPD. However, for all three PDs, the questionnaires were less specific, also indexing an independent set of genetic risk factors.
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Starr, David (Technical Monitor)
2002-01-01
NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in stratiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. Additional information is included in the original extended abstract.
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.
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
Exploratory structural equation modeling of personality data.
Booth, Tom; Hughes, David J
2014-06-01
The current article compares the use of exploratory structural equation modeling (ESEM) as an alternative to confirmatory factor analytic (CFA) models in personality research. We compare model fit, factor distinctiveness, and criterion associations of factors derived from ESEM and CFA models. In Sample 1 (n = 336) participants completed the NEO-FFI, the Trait Emotional Intelligence Questionnaire-Short Form, and the Creative Domains Questionnaire. In Sample 2 (n = 425) participants completed the Big Five Inventory and the depression and anxiety scales of the General Health Questionnaire. ESEM models provided better fit than CFA models, but ESEM solutions did not uniformly meet cutoff criteria for model fit. Factor scores derived from ESEM and CFA models correlated highly (.91 to .99), suggesting the additional factor loadings within the ESEM model add little in defining latent factor content. Lastly, criterion associations of each personality factor in CFA and ESEM models were near identical in both inventories. We provide an example of how ESEM and CFA might be used together in improving personality assessment. © The Author(s) 2014.
Emotional rigidity negatively impacts remission from anxiety and recovery of well-being.
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.
Dyson, Margaret W.; Olino, Thomas M.; Durbin, C. Emily; Goldsmith, H. Hill; Bufferd, Sara J.; Miller, Anna R.; Klein, Daniel N.
2015-01-01
It is generally assumed that temperament traits exhibit structural and rank-order stability over time. Most of the research on structural and rank-order stability has relied on parent-report measures. The present study used an alternative approach, a laboratory-observational measure (Laboratory Temperament Assessment Battery [Lab-TAB]), to examine the structural and rank-order stability of temperament traits in a community sample of young children (N = 447). Using structural equation modeling (SEM), we found that a similar five-factor structure consisting of the dimensions of Positive Affect/Interest, Sociability, Dysphoria, Fear/Inhibition, and Impulsivity vs. Constraint provided an adequate fit to the data at both age 3 and 6 years, suggesting good structural stability. Moreover, all five latent factors exhibited significant, albeit modest, rank-order stability from age 3 to 6. In addition, there were significant heterotypic associations of age 3 Sociability with age 6 PA/Interest, and age 3 Impulsivity vs. Constraint with age 6 Fear/Inhibition. PMID:25894709
ERIC Educational Resources Information Center
Rupp, Andre A.
2012-01-01
In the focus article of this issue, von Davier, Naemi, and Roberts essentially coupled: (1) a short methodological review of structural similarities of latent variable models with discrete and continuous latent variables; and (2) 2 short empirical case studies that show how these models can be applied to real, rather than simulated, large-scale…
ERIC Educational Resources Information Center
Olatunji, Bunmi O.; Cole, David A.
2009-01-01
In an 8-wave, 4-year longitudinal study, 787 children (Grades 3-6) completed the Revised Children's Manifest Anxiety Scale (C. R. Reynolds & B. O. Richmond, 1985), a measure of the Physiological Reactivity, Worry-Oversensitivity, and Social Alienation dimensions of anxiety. A latent variable (trait-state-occasion) model and a latent growth curve…
ERIC Educational Resources Information Center
Keith, Timothy Z.; Reynolds, Matthew R.; Patel, Puja G.; Ridley, Kristen P.
2008-01-01
Sex differences in the latent general and broad cognitive abilities underlying the Woodcock-Johnson Tests of Cognitive Abilities were investigated for children, youth, and adults ages 6 through 59. A developmental, multiple indicator-multiple cause, structural equation model was used to investigate sex differences in latent cognitive abilities as…
ERIC Educational Resources Information Center
Keith, Timothy Z.; Reynolds, Matthew R.; Roberts, Lisa G.; Winter, Amanda L.; Austin, Cynthia A.
2011-01-01
Sex differences in the latent general and broad cognitive abilities underlying the Differential Ability Scales, Second Edition were investigated for children and youth ages 5 through 17. Multi-group mean and covariance structural equation modeling was used to investigate sex differences in latent cognitive abilities as well as changes in these…
ERIC Educational Resources Information Center
von Davier, Matthias
2014-01-01
Diagnostic models combine multiple binary latent variables in an attempt to produce a latent structure that provides more information about test takers' performance than do unidimensional latent variable models. Recent developments in diagnostic modeling emphasize the possibility that multiple skills may interact in a conjunctive way within the…
Ecological Models of Sexual Satisfaction among Lesbian/Bisexual and Heterosexual Women
Henderson, Alison W.; Simoni, Jane M.
2014-01-01
Sexual satisfaction is an integral component of sexual health and well-being, yet we know little about which factors contribute to it among lesbian/bisexual women. To examine a proposed ecological model of sexual satisfaction, we conducted an internet survey of married heterosexual women and lesbian/bisexual women in committed same-sex relationships. Structural equation modeling included five final latent variables for heterosexual women and seven final latent variables for lesbian/bisexual women. Overall, results indicated that, for both groups of women, a similar constellation of factors (depressive symptoms, relationship satisfaction, sexual functioning, and social support) was related to sexual satisfaction. In lesbian/bisexual women, internalized homophobia was an additional factor. Contrary to expectations, the presence of children in the home and a history of childhood sexual abuse did not contribute significantly to the model for either group. Findings support the idea that gender socialization may influence sexual satisfaction more than socialization around sexual orientation. Additionally, given that for both groups of women relationship satisfaction explained a substantial amount of variance in sexual satisfaction, sexual concerns may be better addressed at the relationship than the individual level. PMID:18574685
The Development of the Problematic Online Gaming Questionnaire (POGQ)
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
Precipitation Processes Derived from TRMM Satellite Data, Cloud Resolving Model and Field Campaigns
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Einaudi, Franco (Technical Monitor)
2001-01-01
Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent-heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid. and solid water. Present large-scale weather and climate models can simulate cloud latent heat release only crudely thus reducing their confidence in predictions on both global and regional scales. In this paper, NASA Tropical Rainfall Measuring (TRMM) precipitation radar (PR) derived rainfall information and the Goddard Convective and Stratiform Heating (CSH) algorithm used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to October 2000. Rainfall latent heating and radar reflectively structure between ENSO (1997-1998 winter) and non-ENSO (1998-1999 winter) periods are examined and compared. The seasonal variation of heating over various geographic locations (i.e. Indian ocean vs west Pacific; Africa vs S. America) are also analyzed. In addition, the relationship between rainfall latent heating maximum heating level), radar reflectively and SST are examined.
Perceived stress latent factors and the burnout subtypes: a structural model in dental students.
Montero-Marín, Jesús; Piva Demarzo, Marcelo Marcos; Stapinski, Lexine; Gili, Margarita; García-Campayo, Javier
2014-01-01
Students of health-professions suffer high levels of stress and burnout. The aim of the present study was to evaluate the relationship between perceived stress latent factors ('tenseness' and 'frustration') and the features ('overload', 'lack of development' and 'neglect') of the three burnout subtypes ('frenetic', 'under-challenged' and 'worn-out', respectively), in a sample of Spanish dental students. The study employed a cross-sectional design. A sample of Spanish dental students (n = 314) completed the 'Perceived Stress Questionnaire' and the 'Burnout Clinical Subtype Questionnaire Student Survey'. The associations among variables were observed by means of structural equation modelling using the unweighted least squares method from polychoric correlations. Strong associations among perceived stress factors and the burnout characteristics were observed, although a distinct pattern of relations was observed for each burnout subtype. The 'overload' was moderately and positively associated with both 'tenseness' (0.45), and 'frustration' (0.38) dimensions of perceived stress; the 'lack of development' was positively associated with the 'frustration' dimension (0.72), but negatively associated with 'tenseness' (-0.69); the 'neglect' showed a weaker positive associated with 'frustration' (0.41), and a small negative association with 'tenseness' (-0.20). The model was a very good fit to the data (GFI = 0.96; RSMR = 0.07; AGFI = 0.96; NFI = 0.95; RFI = 0.95). The stress factors of 'frustration' and 'tenseness' seems to be related in a distinct way to the burnout subtypes in Spanish dental students. This finding suggests that intervention programs specifically tailored to these subtypes may be a promising future direction.
ERIC Educational Resources Information Center
Leite, Walter L.; Zuo, Youzhen
2011-01-01
Among the many methods currently available for estimating latent variable interactions, the unconstrained approach is attractive to applied researchers because of its relatively easy implementation with any structural equation modeling (SEM) software. Using a Monte Carlo simulation study, we extended and evaluated the unconstrained approach to…
ERIC Educational Resources Information Center
Hong, Song-Iee; Hasche, Leslie; Bowland, Sharon
2009-01-01
Purpose: This study examines the structural relationships between social activities and trajectories of late-life depression. Design and Methods: Latent class analysis was used with a nationally representative sample of older adults (N = 5,294) from the Longitudinal Study on Aging II to classify patterns of social activities. A latent growth curve…
Introduction to the special section on mixture modeling in personality assessment.
Wright, Aidan G C; Hallquist, Michael N
2014-01-01
Latent variable models offer a conceptual and statistical framework for evaluating the underlying structure of psychological constructs, including personality and psychopathology. Complex structures that combine or compare categorical and dimensional latent variables can be accommodated using mixture modeling approaches, which provide a powerful framework for testing nuanced theories about psychological structure. This special series includes introductory primers on cross-sectional and longitudinal mixture modeling, in addition to empirical examples applying these techniques to real-world data collected in clinical settings. This group of articles is designed to introduce personality assessment scientists and practitioners to a general latent variable framework that we hope will stimulate new research and application of mixture models to the assessment of personality and its pathology.
Vasconcelos-Raposo, José; Fernandes, Helder Miguel; Teixeira, Carla M
2013-01-01
The purpose of the present study was to assess the factor structure and reliability of the Depression, Anxiety and Stress Scales (DASS-21) in a large Portuguese community sample. Participants were 1020 adults (585 women and 435 men), with a mean age of 36.74 (SD = 11.90) years. All scales revealed good reliability, with Cronbach's alpha values between .80 (anxiety) and .84 (depression). The internal consistency of the total score was .92. Confirmatory factor analysis revealed that the best-fitting model (*CFI = .940, *RMSEA = .038) consisted of a latent component of general psychological distress (or negative affectivity) plus orthogonal depression, anxiety and stress factors. The Portuguese version of the DASS-21 showed good psychometric properties (factorial validity and reliability) and thus can be used as a reliable and valid instrument for measuring depression, anxiety and stress symptoms.
Evaluating Measurement of Dynamic Constructs: Defining a Measurement Model of Derivatives
Estabrook, Ryne
2015-01-01
While measurement evaluation has been embraced as an important step in psychological research, evaluating measurement structures with longitudinal data is fraught with limitations. This paper defines and tests a measurement model of derivatives (MMOD), which is designed to assess the measurement structure of latent constructs both for analyses of between-person differences and for the analysis of change. Simulation results indicate that MMOD outperforms existing models for multivariate analysis and provides equivalent fit to data generation models. Additional simulations show MMOD capable of detecting differences in between-person and within-person factor structures. Model features, applications and future directions are discussed. PMID:24364383
Scherer, Ronny; Nilsen, Trude; Jansen, Malte
2016-01-01
Students' perceptions of instructional quality are among the most important criteria for evaluating teaching effectiveness. The present study evaluates different latent variable modeling approaches (confirmatory factor analysis, exploratory structural equation modeling, and bifactor modeling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance, and the relations to selected educational outcomes (achievement, self-concept, and motivation in mathematics). On the basis of the Programme for International Student Assessment (PISA) 2012 large-scale data sets of Australia, Canada, and the USA (N = 26,746 students), we find support for the distinction between three factors of individual students' perceptions and full measurement invariance across countries for all modeling approaches. In this regard, bifactor exploratory structural equation modeling outperformed alternative approaches with respect to model fit. Our findings reveal significant relations to the educational outcomes. This study synthesizes different modeling approaches of individual students' perceptions of instructional quality and provides insights into the nature of these perceptions from an individual differences perspective. Implications for the measurement and modeling of individually perceived instructional quality are discussed.
Confirmatory factor analysis of the Appraisal of Self-Care Agency Scale - Revised 1
Stacciarini, Thaís Santos Guerra; Pace, Ana Emilia
2017-01-01
ABSTRACT Objective: to analyze the factor structure of the Appraisal of Self-Care Agency Scale-Revised (ASAS-R), adapted for Brazil. Method: methodological study conducted with 150 individuals with diabetes mellitus cared for by the Family Health Strategy, most of whom are elderly with low educational levels. The test of the hypothesis concerning the confirmatory factor composition of the ASAS-R was performed using latent variables structural equations. Results: the model’s goodness-of-fit indexes were satisfactory (χ2 = 259.19; χ2/g.l = 2.97, p < 0.001; GFI = 0.85; RMR = 0.07; RMSEA = 0.09); the factor loads were greater than 0.40; and most item-to-factor-correlations presented moderate to strong magnitude (0.34 to 0.58); total alpha value was 0.74, while the alpha of the three factors were 0.69, 0.38 and 0.69, respectively. Conclusion: the scale’s factor structure presented satisfactory validity and reliability results, with the exception of one factor. Application of this scale to samples of the general population is desirable in order to strengthen analyses of internal consistency and the dimensionality of the factor structure. This study is expected to contribute to further studies addressing the self-care agency construct and the development of the ASAS-R. PMID:28146182
Barbot, Baptiste; Hunter, Scott R.; Grigorenko, Elena L.; Luthar, Suniya S.
2012-01-01
This study explores longitudinally a four-factor structure of pathological personality trait dimensions (PPTDs) to examine both its structural stability and intra-individual changes among PPTDs over time. Personality Disorder (PD) scales of the Millon Clinical Multiaxial Inventory-III were administered to 361 low-income women with various psychiatric conditions (drug dependence, depression), who were followed in a two-wave study over 5-years. Cross-sectional and longitudinal factor analyses outlined a robust factorial structure of PPTDs, extrinsically invariant over time, representing Negative Emotionality, Introversion, Antagonism and Impulsivity. Despite moderate rank-order stability in the PPTDs, results also indicated substantial intra-individual variability in the degree and direction of change, consistent with trajectories of change in participants’ clinical diagnoses. Results are discussed in light of current debates on the structure and dynamic of pathological personality. PMID:23710108
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
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.
Application of Generative Autoencoder in De Novo Molecular Design.
Blaschke, Thomas; Olivecrona, Marcus; Engkvist, Ola; Bajorath, Jürgen; Chen, Hongming
2018-01-01
A major challenge in computational chemistry is the generation of novel molecular structures with desirable pharmacological and physiochemical properties. In this work, we investigate the potential use of autoencoder, a deep learning methodology, for de novo molecular design. Various generative autoencoders were used to map molecule structures into a continuous latent space and vice versa and their performance as structure generator was assessed. Our results show that the latent space preserves chemical similarity principle and thus can be used for the generation of analogue structures. Furthermore, the latent space created by autoencoders were searched systematically to generate novel compounds with predicted activity against dopamine receptor type 2 and compounds similar to known active compounds not included in the trainings set were identified. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.
The Structure of Musical Preferences: A Five-Factor Model
Rentfrow, Peter J.; Goldberg, Lewis R.; Levitin, Daniel J.
2011-01-01
Music is a cross-cultural universal, a ubiquitous activity found in every known human culture. Individuals demonstrate manifestly different preferences in music, and yet relatively little is known about the underlying structure of those preferences. Here, we introduce a model of musical preferences based on listeners’ affective reactions to excerpts of music from a wide variety of musical genres. The findings from three independent studies converged to suggest that there exists a latent five-factor structure underlying music preferences that is genre-free, and reflects primarily emotional/affective responses to music. We have interpreted and labeled these factors as: 1) a Mellow factor comprising smooth and relaxing styles; 2) an Urban factor defined largely by rhythmic and percussive music, such as is found in rap, funk, and acid jazz; 3) a Sophisticated factor that includes classical, operatic, world, and jazz; 4) an Intense factor defined by loud, forceful, and energetic music; and 5) a Campestral factor comprising a variety of different styles of direct, and rootsy music such as is often found in country and singer-songwriter genres. The findings from a fourth study suggest that preferences for the MUSIC factors are affected by both the social and auditory characteristics of the music. PMID:21299309
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.
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.
Smith, Gregory C; Palmieri, Patrick A; Hancock, Gregory R; Richardson, Rhonda A
2008-01-01
An adaptation of the Family Stress Model (FSM) with hypothesized linkages between family contextual factors, custodial grandmothers' psychological distress, parenting practices, and grandchildren's adjustment was tested with structural equation modeling. Interview data from 733 custodial grandmothers of grandchildren between ages 4-17 revealed that the effect of grandmothers' distress on grandchildren's adjustment was mediated by dysfunctional parenting, especially regarding externalizing problems. The effects of contextual factors on grandchildren's adjustment were also indirect. The model's measurement and structural components were largely invariant across grandmothers' race and age, as well as grandchildren's gender and age. Group differences were more prevalent regarding the magnitude of latent means for model constructs. We conclude that parenting models like the FSM are useful for investigating custodial grandfamilies.
Smith, Gregory C.; Palmieri, Patrick A.; Hancock, Gregory R.; Richardson, Rhonda A.
2009-01-01
An adaptation of the Family Stress Model (FSM) with hypothesized linkages between family contextual factors, custodial grandmothers' psychological distress, parenting practices, and grandchildren's adjustment was tested with structural equation modeling. Interview data from 733 custodial grandmothers of grandchildren between ages 4-17 revealed that the effect of grandmothers' distress on grandchildren's adjustment was mediated by dysfunctional parenting, especially regarding externalizing problems. The effects of contextual factors on grandchildren's adjustment were also indirect. The model's measurement and structural components were largely invariant across grandmothers' race and age, as well as grandchildren's gender and age. Group differences were more prevalent regarding the magnitude of latent means for model constructs. We conclude that parenting models like the FSM are useful for investigating custodial grandfamilies. PMID:19266869
Zimmermann, Johannes; Böhnke, Jan R; Eschstruth, Rhea; Mathews, Alessa; Wenzel, Kristin; Leising, Daniel
2015-08-01
The alternative model for the classification of personality disorders (PD) in the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) Section III comprises 2 major components: impairments in personality functioning (Criterion A) and maladaptive personality traits (Criterion B). In this study, we investigated the latent structure of Criterion A (a) within subdomains, (b) across subdomains, and (c) in conjunction with the Criterion B trait facets. Data were gathered as part of an online study that collected other-ratings by 515 laypersons and 145 therapists. Laypersons were asked to assess 1 of their personal acquaintances, whereas therapists were asked to assess 1 of their patients, using 135 items that captured features of Criteria A and B. We were able to show that (a) the structure within the Criterion A subdomains can be appropriately modeled using generalized graded unfolding models, with results suggesting that the items are indeed related to common underlying constructs but often deviate from their theoretically expected severity level; (b) the structure across subdomains is broadly in line with a model comprising 2 strongly correlated factors of self- and interpersonal functioning, with some notable deviations from the theoretical model; and (c) the joint structure of the Criterion A subdomains and the Criterion B facets broadly resembles the expected model of 2 plus 5 factors, albeit the loading pattern suggests that the distinction between Criteria A and B is somewhat blurry. Our findings provide support for several major assumptions of the alternative DSM-5 model for PD but also highlight aspects of the model that need to be further refined. (c) 2015 APA, all rights reserved).
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.
ERIC Educational Resources Information Center
Teo, Timothy; Kam, Chester
2014-01-01
Following the call to ensure the validity of instruments used to assess users' level of Internet usage, this study examined the factor structure of the Internet Addiction Test-Adolescence version (IAT-A) when applied to a sample of young children in a multicultural society and assessed whether the items in the IAT-A were invariant by gender and,…
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…
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…
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.)
A Retrieval of Tropical Latent Heating Using the 3D Structure of Precipitation Features
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ahmed, Fiaz; Schumacher, Courtney; Feng, Zhe
Traditionally, radar-based latent heating retrievals use rainfall to estimate the total column-integrated latent heating and then distribute that heating in the vertical using a model-based look-up table (LUT). In this study, we develop a new method that uses size characteristics of radar-observed precipitating echo (i.e., area and mean echo-top height) to estimate the vertical structure of latent heating. This technique (named the Convective-Stratiform Area [CSA] algorithm) builds on the fact that the shape and magnitude of latent heating profiles are dependent on the organization of convective systems and aims to avoid some of the pitfalls involved in retrieving accurate rainfallmore » amounts and microphysical information from radars and models. The CSA LUTs are based on a high-resolution Weather Research and Forecasting model (WRF) simulation whose domain spans much of the near-equatorial Indian Ocean. When applied to S-PolKa radar observations collected during the DYNAMO/CINDY2011/AMIE field campaign, the CSA retrieval compares well to heating profiles from a sounding-based budget analysis and improves upon a simple rain-based latent heating retrieval. The CSA LUTs also highlight the fact that convective latent heating increases in magnitude and height as cluster area and echo-top heights grow, with a notable congestus signature of cooling at mid levels. Stratiform latent heating is less dependent on echo-top height, but is strongly linked to area. Unrealistic latent heating profiles in the stratiform LUT, viz., a low-level heating spike, an elevated melting layer, and net column cooling were identified and corrected for. These issues highlight the need for improvement in model parameterizations, particularly in linking microphysical phase changes to larger mesoscale processes.« less
Moehring, Anne; Krause, Kristian; Guertler, Diana; Bischof, Gallus; Hapke, Ulfert; Freyer-Adam, Jennis; Baumann, Sophie; Batra, Anil; Rumpf, Hans-Juergen; Ulbricht, Sabina; John, Ulrich; Meyer, Christian
2018-05-31
The Alcohol Use Disorders Identification Test (AUDIT) is an internationally well-established screening tool for the assessment of hazardous and harmful alcohol consumption. To be valid for group comparisons, the AUDIT should measure the same latent construct with the same structure across groups. This is determined by measurement invariance. So far, measurement invariance of the AUDIT has rarely been investigated. We analyzed measurement invariance across gender and samples from different settings (i.e., inpatients from general hospital, patients from general medical practices, general population). A sample of n = 28,345 participants from general hospitals, general medical practices and the general population was provided from six studies. First, we used Confirmatory Factor Analysis (CFA) to establish the factorial structure of the AUDIT by comparing a single-factor model to a two-factor model for each group. Next, Multiple Group CFA was used to investigate measurement invariance. The two-factor structure was shown to be preferable for all groups. Furthermore, strict measurement invariance was established across all groups for the AUDIT. A two-factor structure for the AUDIT is preferred. Nevertheless, the one-factor structure also showed a good fit to the data. The findings support the AUDIT as a psychometrically valid and reliable screening instrument. Copyright © 2018 Elsevier B.V. All rights reserved.
The Use of a Context-Based Information Retrieval Technique
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.
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
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
Swami, Viren; Tudorel, Otilia; Goian, Cosmin; Barron, David; Vintila, Mona
2017-12-01
We examined the psychometric properties of a Romanian translation of the 10-item Body Appreciation Scale-2 (BAS-2). A total of 453 university students from Romania completed the BAS-2, along with measures of disordered eating, self-esteem, satisfaction with life, and subjective happiness. In addition, a separate sample of university students (N=109) completed only the BAS-2 at two time-points three weeks apart. Principal-axis factor analysis indicated that BAS-2 scores had a one-dimensional factor structure in both women and men. Confirmatory factor analysis indicated that this factor structure had adequate fit, but invariance across sex was not supported. Further analyses indicated that BAS-2 scores evidenced internal consistency, convergent validity, and test-retest reliability in both women and men. These results suggest that BAS-2 scores reduce to one dimension in Romanian adults, but the lack of sex invariance may indicate that the same latent construct is not being measured in women and men. Copyright © 2017 Elsevier Ltd. All rights reserved.
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
Students' Views on Mathematics in Single-Sex and Coed Classrooms in Ghana
ERIC Educational Resources Information Center
Bofah, Emmanuel Adu-tutu; Hannula, Markku S.
2016-01-01
In this study, we investigated students' views on themselves as learners of mathematics as a function of school-by-sex (N = 2034, MAge = 18.49, SDAge = 1.25; 12th-grade; 58.2% girls). Using latent variable Structural Equation Modeling (SEM), the measurement and structural equivalence as well as the equality of latent means of scores across…
The Information a Test Provides on an Ability Parameter. Research Report. ETS RR-07-18
ERIC Educational Resources Information Center
Haberman, Shelby J.
2007-01-01
In item-response theory, if a latent-structure model has an ability variable, then elementary information theory may be employed to provide a criterion for evaluation of the information the test provides concerning ability. This criterion may be considered even in cases in which the latent-structure model is not valid, although interpretation of…
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.
Kirby, James B.; Bollen, Kenneth A.
2009-01-01
Structural Equation Modeling with latent variables (SEM) is a powerful tool for social and behavioral scientists, combining many of the strengths of psychometrics and econometrics into a single framework. The most common estimator for SEM is the full-information maximum likelihood estimator (ML), but there is continuing interest in limited information estimators because of their distributional robustness and their greater resistance to structural specification errors. However, the literature discussing model fit for limited information estimators for latent variable models is sparse compared to that for full information estimators. We address this shortcoming by providing several specification tests based on the 2SLS estimator for latent variable structural equation models developed by Bollen (1996). We explain how these tests can be used to not only identify a misspecified model, but to help diagnose the source of misspecification within a model. We present and discuss results from a Monte Carlo experiment designed to evaluate the finite sample properties of these tests. Our findings suggest that the 2SLS tests successfully identify most misspecified models, even those with modest misspecification, and that they provide researchers with information that can help diagnose the source of misspecification. PMID:20419054
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.
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
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.
Developing a Tool for Measuring the Decision-Making Competence of Older Adults
Finucane, Melissa L.; Gullion, Christina M.
2010-01-01
The authors evaluated the reliability and validity of a tool for measuring older adults’ decision-making competence (DMC). Two-hundred-five younger adults (25-45 years), 208 young-older adults (65-74 years), and 198 old-older adults (75-97 years) made judgments and decisions related to health, finance, and nutrition. Reliable indices of comprehension, dimension weighting, and cognitive reflection were developed. Unlike previous research, the authors were able to compare old-older with young-older adults’ performance. As hypothesized, old-older adults performed more poorly than young-older adults; both groups of older adults performed more poorly than younger adults. Hierarchical regression analyses showed that a large amount of variance in decision performance across age groups (including mean trends) could be accounted for by social variables, health measures, basic cognitive skills, attitudinal measures, and numeracy. Structural equation modeling revealed significant pathways from three exogenous latent factors (crystallized intelligence, other cognitive abilities, and age) to the endogenous DMC latent factor. Further research is needed to validate the meaning of performance on these tasks for real-life decision making. PMID:20545413
Mäki-Opas, Tomi E; de Munter, Jeroen; Maas, Jolanda; den Hertog, Frank; Kunst, Anton E
2014-08-01
This study examined the effect of physical environment on cycling to and from school among boys and girls of Turkish and Moroccan origin living in Amsterdam. The LASER study (n = 697) was an interview study that included information on cycling to and from school and the perceived physical environment. Objective information on physical environment was gathered from Statistics Netherlands and the Department for Research and Statistics at the Municipality of Amsterdam. Structural equation modelling with latent variables was applied, taking into account age, gender, self-assessed health, education, country of origin, and distance to school. For every unit increase in the latent variable scale for bicycle-friendly infrastructure, we observed a 21% increase in the odds for cycling to and from school. The association was only borderline statistically significant and disappeared after controlling for distance to school. The enjoyable environment was not associated with cycling to and from school after controlling for all background factors. Bicycle-friendly infrastructure and an enjoyable environment were not important factors for cycling to and from school among those with no cultural cycling background.
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.
Armour, Cherie; O'Connor, Maja; Elklit, Ask; Elhai, Jon D
2013-10-01
The three-factor structure of posttraumatic stress disorder (PTSD) specified by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, is not supported in the empirical literature. Two alternative four-factor models have received a wealth of empirical support. However, a consensus regarding which is superior has not been reached. A recent five-factor model has been shown to provide superior fit over the existing four-factor models. The present study investigated the fit of the five-factor model against the existing four-factor models and assessed the resultant factors' association with depression in a bereaved European trauma sample (N = 325). The participants were assessed for PTSD via the Harvard Trauma Questionnaire and depression via the Beck Depression Inventory. The five-factor model provided superior fit to the data compared with the existing four-factor models. In the dysphoric arousal model, depression was equally related to both dysphoric arousal and emotional numbing, whereas depression was more related to dysphoric arousal than to anxious arousal.
Familiar, Itziar; Murray, Laura; Gross, Alden; Skavenski, Stephanie; Jere, Elizabeth; Bass, Judith
2014-11-01
Scant information exists on PTSD symptoms and structure in youth from developing countries. We describe the symptom profile and exposure to trauma experiences among 343 orphan and vulnerable children and adolescents from Zambia. We distinguished profiles of post-traumatic stress symptoms using latent class analysis. Average number of trauma-related symptoms (21.6; range 0-38) was similar across sex and age. Latent class model suggested 3 classes varying by level of severity: low (31% of the sample), medium (45% of the sample), and high (24% of the sample) symptomatology. Results suggest that PTSD is a continuously distributed latent trait.
Wang, Yang; Wu, Lin
2018-07-01
Low-Rank Representation (LRR) is arguably one of the most powerful paradigms for Multi-view spectral clustering, which elegantly encodes the multi-view local graph/manifold structures into an intrinsic low-rank self-expressive data similarity embedded in high-dimensional space, to yield a better graph partition than their single-view counterparts. In this paper we revisit it with a fundamentally different perspective by discovering LRR as essentially a latent clustered orthogonal projection based representation winged with an optimized local graph structure for spectral clustering; each column of the representation is fundamentally a cluster basis orthogonal to others to indicate its members, which intuitively projects the view-specific feature representation to be the one spanned by all orthogonal basis to characterize the cluster structures. Upon this finding, we propose our technique with the following: (1) We decompose LRR into latent clustered orthogonal representation via low-rank matrix factorization, to encode the more flexible cluster structures than LRR over primal data objects; (2) We convert the problem of LRR into that of simultaneously learning orthogonal clustered representation and optimized local graph structure for each view; (3) The learned orthogonal clustered representations and local graph structures enjoy the same magnitude for multi-view, so that the ideal multi-view consensus can be readily achieved. The experiments over multi-view datasets validate its superiority, especially over recent state-of-the-art LRR models. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Gao, Feng; Han, Jiaxing; Lv, Caifeng; Wang, Qin; Zhang, Jun; Li, Qun; Bao, Liru; Li, Xin
2012-10-01
Fingerprint detection is important in criminal investigation. This paper reports a facile powder brushing technique for improving latent fingerprint detection using core-shell-structured CdTe@SiO2 quantum dots (QDs) as fluorescent labeling marks. Core-shell-structured CdTe@SiO2 QDs are prepared via a simple solution-based approach using NH2NH2·H2O as pH adjustor and stabilizer, and their application for improving latent fingerprint detection is explored. The obtained CdTe@SiO2 QDs show spherical shapes with well-defined core-shell structures encapsulating different amounts of QDs depending on the type of the pH adjustor and stabilizer. Moreover, the fluorescence of CdTe@SiO2 QDs is largely enhanced by surface modification of the SiO2 shell. The CdTe@SiO2 QDs overcome the oxidation problem of pure CdTe QDs in air, thus affording better variability with strong adhesive ability, better resolution, and bright emission colors for practical application in latent fingerprint detection. In comparison with the conventional fluorescence powders, silver powders, and others, the effectiveness of CdTe@SiO2 QD powders for detection of latent fingerprints present on a large variety of object surfaces is greatly improved. The synthesis method for CdTe@SiO2 QDs is simple, cheap, and easy for large-scale production, and thus offers many advantages in the practical application of fingerprint detection.
Monsma, Eva
2016-01-01
This paper examines the factor structure and measurement invariance of the Task and Ego Orientation in Sport Questionnaire (TEOSQ) across American and Chinese samples. Results based on the mean and covariance structure analyses supported configural invariance, metric invariance and scalar invariance across groups. Latent means analyses revealed that American sample had significantly higher mean scores on task and ego orientations than the Chinese sample. The findings suggest that the TEOSQ is a valid and reliable instrument in assessing achievement motivation across these two diverse populations. PMID:27399869
A taxometric investigation of agoraphobia in a clinical and a community sample.
Slade, Tim; Grisham, Jessica R
2009-08-01
The nosological status of agoraphobia is controversial. Agoraphobia may be a distinct diagnostic entity or a marker of avoidance severity. The current study examines the latent structure of agoraphobia through the use of taxometric analysis. The latent structure of agoraphobia was examined in two independent samples, one comprising outpatients presenting for treatment for panic disorder (PD) with or without agoraphobia (n=365), and the other comprising community volunteers to a national mental health survey who experienced fear or avoidance of at least one prototypic agoraphobic situation (n=640). Two taxometric procedures were carried out - maximum eigenvalue (MAXEIG) and mean above minus below a cut (MAMBAC) - using indicators derived from questionnaire measures of, and structured diagnostic interviews for, agoraphobia. Results show consistent evidence of dimensional latent structure in both samples. It is concluded that scores on measures of agoraphobia best represent an agoraphobic severity dimension.
Hammond, R; Smith, D R; Diener, T O
1989-01-01
The Columnea latent viroid (CLV) occurs latently in certain Columnea erythrophae plants grown commercially. In potato and tomato, CLV causes potato spindle tuber viroid (PSTV)-like symptoms. Its nucleotide sequence and proposed secondary structure reveal that CLV consists of a single-stranded circular RNA of 370 nucleotides which can assume a rod-like structure with extensive base-pairing characteristic of all known viroids. The electrophoretic mobility of circular CLV under nondenaturing conditions suggests a potential tertiary structure. CLV contains extensive sequence homologies to the PSTV group of viroids but contains a central conserved region identical to that of hop stunt viroid (HSV). CLV also shares some biological properties with each of the two types of viroids. Most probably, CLV is the result of intracellular RNA recombination between an HSV-type and one or more PSTV-type viroids replicating in the same plant. Images PMID:2602114
Predicting Viral Infection From High-Dimensional Biomarker Trajectories
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
Robust Measurement via A Fused Latent and Graphical Item Response Theory Model.
Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang
2018-03-12
Item response theory (IRT) plays an important role in psychological and educational measurement. Unlike the classical testing theory, IRT models aggregate the item level information, yielding more accurate measurements. Most IRT models assume local independence, an assumption not likely to be satisfied in practice, especially when the number of items is large. Results in the literature and simulation studies in this paper reveal that misspecifying the local independence assumption may result in inaccurate measurements and differential item functioning. To provide more robust measurements, we propose an integrated approach by adding a graphical component to a multidimensional IRT model that can offset the effect of unknown local dependence. The new model contains a confirmatory latent variable component, which measures the targeted latent traits, and a graphical component, which captures the local dependence. An efficient proximal algorithm is proposed for the parameter estimation and structure learning of the local dependence. This approach can substantially improve the measurement, given no prior information on the local dependence structure. The model can be applied to measure both a unidimensional latent trait and multidimensional latent traits.
Measurement of psychological disorders using cognitive diagnosis models.
Templin, Jonathan L; Henson, Robert A
2006-09-01
Cognitive diagnosis models are constrained (multiple classification) latent class models that characterize the relationship of questionnaire responses to a set of dichotomous latent variables. Having emanated from educational measurement, several aspects of such models seem well suited to use in psychological assessment and diagnosis. This article presents the development of a new cognitive diagnosis model for use in psychological assessment--the DINO (deterministic input; noisy "or" gate) model--which, as an illustrative example, is applied to evaluate and diagnose pathological gamblers. As part of this example, a demonstration of the estimates obtained by cognitive diagnosis models is provided. Such estimates include the probability an individual meets each of a set of dichotomous Diagnostic and Statistical Manual of Mental Disorders (text revision [DSM-IV-TR]; American Psychiatric Association, 2000) criteria, resulting in an estimate of the probability an individual meets the DSM-IV-TR definition for being a pathological gambler. Furthermore, a demonstration of how the hypothesized underlying factors contributing to pathological gambling can be measured with the DINO model is presented, through use of a covariance structure model for the tetrachoric correlation matrix of the dichotomous latent variables representing DSM-IV-TR criteria. Copyright 2006 APA
Human Life History Strategies.
Chua, Kristine J; Lukaszewski, Aaron W; Grant, DeMond M; Sng, Oliver
2017-01-01
Human life history (LH) strategies are theoretically regulated by developmental exposure to environmental cues that ancestrally predicted LH-relevant world states (e.g., risk of morbidity-mortality). Recent modeling work has raised the question of whether the association of childhood family factors with adult LH variation arises via (i) direct sampling of external environmental cues during development and/or (ii) calibration of LH strategies to internal somatic condition (i.e., health), which itself reflects exposure to variably favorable environments. The present research tested between these possibilities through three online surveys involving a total of over 26,000 participants. Participants completed questionnaires assessing components of self-reported environmental harshness (i.e., socioeconomic status, family neglect, and neighborhood crime), health status, and various LH-related psychological and behavioral phenotypes (e.g., mating strategies, paranoia, and anxiety), modeled as a unidimensional latent variable. Structural equation models suggested that exposure to harsh ecologies had direct effects on latent LH strategy as well as indirect effects on latent LH strategy mediated via health status. These findings suggest that human LH strategies may be calibrated to both external and internal cues and that such calibrational effects manifest in a wide range of psychological and behavioral phenotypes.
Ku-Yuan, Lee; Li-Chi, Lan; Jiun-Hao, Wang; Chen-Ling, Fang; Kun-Sun, Shiao
2014-06-04
To control the latent social risk of disease, the government usually spreads accurate information and attempts to improve the public's attitude toward adopting prevention. However, these methods with the Knowledge, Attitudes, and Practices (KAP) model do not always work. Therefore, we used the theory of planned behavior (TPB) to understand dog owners' behavior and distinguished the knowledge effect as objective knowledge (OK) and subjective knowledge (SK). A total of 310 dog owners completed a questionnaire based on our model. We employed structural equation modeling to verify the structural relationships and found three main results. First, our model was fit, and each path was significant. People with better attitudes, stronger subjective norms, and more perceptive behavioral control have stronger behavioral intention. Second, perceived behavioral control, not attitude, was the best predictive index in this model. Finally, on perceived behavioral control, subjective knowledge showed more influence than objective knowledge. We successfully extended TPB to explain the behavioral intention of dog owners and presented more workable recommendations. To reduce the latent social risk of disease, the government should not only address dog owners' attitudes, but also their subjective norms and perceptive behavioral control. Indeed, perceptive behavioral control and SK showed the most influence in this model. It is implied that the self-efficacy of dog owners is the most important factor in such a behavior. Therefore, the government should focus on enhancing dog owners' self-efficacy first while devoted to prevention activities.
Ku-Yuan, Lee; Li-Chi, Lan; Jiun-Hao, Wang; Chen-Ling, Fang; Kun-Sun, Shiao
2014-01-01
To control the latent social risk of disease, the government usually spreads accurate information and attempts to improve the public’s attitude toward adopting prevention. However, these methods with the Knowledge, Attitudes, and Practices (KAP) model do not always work. Therefore, we used the theory of planned behavior (TPB) to understand dog owners’ behavior and distinguished the knowledge effect as objective knowledge (OK) and subjective knowledge (SK). A total of 310 dog owners completed a questionnaire based on our model. We employed structural equation modeling to verify the structural relationships and found three main results. First, our model was fit, and each path was significant. People with better attitudes, stronger subjective norms, and more perceptive behavioral control have stronger behavioral intention. Second, perceived behavioral control, not attitude, was the best predictive index in this model. Finally, on perceived behavioral control, subjective knowledge showed more influence than objective knowledge. We successfully extended TPB to explain the behavioral intention of dog owners and presented more workable recommendations. To reduce the latent social risk of disease, the government should not only address dog owners’ attitudes, but also their subjective norms and perceptive behavioral control. Indeed, perceptive behavioral control and SK showed the most influence in this model. It is implied that the self-efficacy of dog owners is the most important factor in such a behavior. Therefore, the government should focus on enhancing dog owners’ self-efficacy first while devoted to prevention activities. PMID:24901413
Michaelides, Michalis P; Koutsogiorgi, Chrystalla; Panayiotou, Georgia
2016-01-01
Rosenberg's Self-Esteem Scale is a balanced, 10-item scale designed to be unidimensional; however, research has repeatedly shown that its factorial structure is contaminated by method effects due to item wording. Beyond the substantive self-esteem factor, 2 additional factors linked to the positive and negative wording of items have been theoretically specified and empirically supported. Initial evidence has revealed systematic relations of the 2 method factors with variables expressing approach and avoidance motivation. This study assessed the fit of competing confirmatory factor analytic models for the Rosenberg Self-Esteem Scale using data from 2 samples of adult participants in Cyprus. Models that accounted for both positive and negative wording effects via 2 latent method factors had better fit compared to alternative models. Measures of experiential avoidance, social anxiety, and private self-consciousness were associated with the method factors in structural equation models. The findings highlight the need to specify models with wording effects for a more accurate representation of the scale's structure and support the hypothesis of method factors as response styles, which are associated with individual characteristics related to avoidance motivation, behavioral inhibition, and anxiety.
de Frias, Cindy M; Dixon, Roger A; Strauss, Esther
2009-11-01
The authors examined the structure and invariance of executive functions (EF) across (a) a continuum of cognitive status in 3 groups of older adults (cognitively elite [CE], cognitively normal [CN], and cognitively impaired [CI]) and (b) a 3-year longitudinal interval. Using latent variable analyses (LISREL 8.80), the authors tested 3-factor models ("Inhibition": Hayling [Burgess & Shallice, 1997], Stroop [Regard, 1981]; "Shifting": Brixton [Burgess & Shallice, 1997], Color Trails [D'Elia et al., 1996]; and "Updating": Reading and Computational Span [Salthouse & Babcock, 1991]) and 1-factor models within each group. Participants (initial N = 570; 53-90 years) were from the Victoria Longitudinal Study (Sample 3, Waves 1 and 2). Cross-sectionally, the authors observed a 3-factor EF structure especially for the CE group and 1-factor solutions for all 3 groups. Longitudinally, temporal invariance was supported for the 3-factor model (CE and CN groups) and the 1-factor model (CI and CN groups). Subgroups with higher cognitive status and greater 3-year stability performed better on EF factors than corresponding groups with lower cognitive status and less stability. Studies of EF structure, performance, dedifferentiation, and dysfunction will benefit from considering initial cognitive status and longitudinal stability.
NASA Astrophysics Data System (ADS)
Anekawati, Anik; Widjanarko Otok, Bambang; Purhadi; Sutikno
2017-06-01
Research in education often involves a latent variable. Statistical analysis technique that has the ability to analyze the pattern of relationship among latent variables as well as between latent variables and their indicators is Structural Equation Modeling (SEM). SEM partial least square (PLS) was developed as an alternative if these conditions are met: the theory that underlying the design of the model is weak, does not assume a certain scale measurement, the sample size should not be large and the data does not have the multivariate normal distribution. The purpose of this paper is to compare the results of modeling of the educational quality in high school level (SMA/MA) in Sumenep Regency with structural equation modeling approach partial least square with three schemes estimation of score factors. This paper is a result of explanatory research using secondary data from Sumenep Education Department and Badan Pusat Statistik (BPS) Sumenep which was data of Sumenep in the Figures and the District of Sumenep in the Figures for the year 2015. The unit of observation in this study were districts in Sumenep that consists of 18 districts on the mainland and 9 districts in the islands. There were two endogenous variables and one exogenous variable. Endogenous variables are the quality of education level of SMA/MA (Y1) and school infrastructure (Y2), whereas exogenous variable is socio-economic condition (X1). In this study, There is one improved model which represented by model from path scheme because this model is a consistent, all of its indicators are valid and its the value of R-square increased which is: Y1=0.651Y2. In this model, the quality of education influenced only by the school infrastructure (0.651). The socio-economic condition did not affect neither the school infrastructure nor the quality of education. If the school infrastructure increased 1 point, then the quality of education increased 0.651 point. The quality of education had an R2 of 0.418, which indicates that 41.8 percent of variance in the quality of education is explained by the school infrastructure, the remaining 58.2% is explained by the other factors which were not investigated in this work.
Person Re-Identification via Distance Metric Learning With Latent Variables.
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.
Validation of the burns itch questionnaire.
Van Loey, N E; Hofland, H W; Hendrickx, H; Van de Steenoven, J; Boekelaar, A; Nieuwenhuis, M K
2016-05-01
Itch (pruritus) is a common multidimensional complaint after burn that can persist for months to years. A questionnaire able to investigate itch and its consequences is imperative for clinical and research purposes. The current study investigated the factor structure, internal consistency and construct validity of the Burns Itch Questionnaire (BIQ), a questionnaire particularly focusing on itch in the burns population. The BIQ was completed by 195 respondents at 3 months after burn. An exploratory factor analysis (EFA) was performed to investigate the factor structure. EFA showed the BIQ comprised three latent factors: itch severity, sleep interference and daily life interference. This was re-evaluated in a confirmatory factor analysis that yielded good fit indices after removing two items. The three subscales showed to have high internal consistency (.89) and were able to distinguish between patients with severe and less severe complaints. In conclusion, the BIQ showed to be useful in persons suffering from itch following burns. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.
Evaluating the Latent Structure of the MMPI-2 F(p) Scale in a Forensic Sample: A Taxometric Analysis
ERIC Educational Resources Information Center
Strong, David R.; Glassmire, David M.; Frederick, Richard I.; Greene, Roger L.
2006-01-01
P. A. Arbisi and Y. S. Ben-Porath (1995) originally proposed that the Infrequency Psychopathology scale, F(p), be used as the final step in an algorithm to determine the validity of a Minnesota Multiphasic Personality Inventory-2 (MMPI-2) protocol. The current study used taxometric procedures to determine the latent structure of F(p) among…
ERIC Educational Resources Information Center
Ferrer, Emilio; Hamagami, Fumiaki; McArdle, John J.
2004-01-01
This article offers different examples of how to fit latent growth curve (LGC) models to longitudinal data using a variety of different software programs (i.e., LISREL, Mx, Mplus, AMOS, SAS). The article shows how the same model can be fitted using both structural equation modeling and multilevel software, with nearly identical results, even in…
ERIC Educational Resources Information Center
Olatunji, Bunmi O.; Broman-Fulks, Joshua J.; Bergman, Shawn M.; Green, Bradley A.; Zlomke, Kimberly R.
2010-01-01
Worry has been described as a core feature of several disorders, particularly generalized anxiety disorder (GAD). The present study examined the latent structure of worry by applying 3 taxometric procedures (MAXEIG, MAMBAC, and L-Mode) to data collected from 2 large samples. Worry in the first sample (Study 1) of community participants (n = 1,355)…
Optical properties of drug metabolites in latent fingermarks
Shen, Yao; Ai, Qing
2016-01-01
Drug metabolites usually have structures of split-ring resonators (SRRs), which might lead to negative permittivity and permeability in electromagnetic field. As a result, in the UV-vis region, the latent fingermarks images of drug addicts and non drug users are inverse. The optical properties of latent fingermarks are quite different between drug addicts and non-drug users. This is a technic superiority for crime scene investigation to distinguish them. In this paper, we calculate the permittivity and permeability of drug metabolites using tight-binding model. The latent fingermarks of smokers and non-smokers are given as an example. PMID:26838730
Predictive Inference Using Latent Variables with Covariates*
Schofield, Lynne Steuerle; Junker, Brian; Taylor, Lowell J.; Black, Dan A.
2014-01-01
Plausible Values (PVs) are a standard multiple imputation tool for analysis of large education survey data that measures latent proficiency variables. When latent proficiency is the dependent variable, we reconsider the standard institutionally-generated PV methodology and find it applies with greater generality than shown previously. When latent proficiency is an independent variable, we show that the standard institutional PV methodology produces biased inference because the institutional conditioning model places restrictions on the form of the secondary analysts’ model. We offer an alternative approach that avoids these biases based on the mixed effects structural equations (MESE) model of Schofield (2008). PMID:25231627
Ethnic differences in longitudinal latent verbal profiles in the millennium cohort study.
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*
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
Rosenström, Tom; Ystrom, Eivind; Torvik, Fartein Ask; Czajkowski, Nikolai Olavi; Gillespie, Nathan A.; Aggen, Steven H.; Krueger, Robert F.; Kendler, Kenneth S; Reichborn-Kjennerud, Ted
2017-01-01
Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI = 40–67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct. PMID:28108863
Rosenström, Tom; Ystrom, Eivind; Torvik, Fartein Ask; Czajkowski, Nikolai Olavi; Gillespie, Nathan A; Aggen, Steven H; Krueger, Robert F; Kendler, Kenneth S; Reichborn-Kjennerud, Ted
2017-05-01
Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI 40-67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct.
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.
Hallquist, Michael N; Wright, Aidan G C
2014-01-01
Over the past 75 years, the study of personality and personality disorders has been informed considerably by an impressive array of psychometric instruments. Many of these tests draw on the perspective that personality features can be conceptualized in terms of latent traits that vary dimensionally across the population. A purely trait-oriented approach to personality, however, might overlook heterogeneity that is related to similarities among subgroups of people. This article describes how factor mixture modeling (FMM), which incorporates both categories and dimensions, can be used to represent person-oriented and trait-oriented variability in the latent structure of personality. We provide an overview of different forms of FMM that vary in the degree to which they emphasize trait- versus person-oriented variability. We also provide practical guidelines for applying FMM to personality data, and we illustrate model fitting and interpretation using an empirical analysis of general personality dysfunction.
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.
2003-01-01
NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs. S. America ) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in stratiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model. Review of other latent heating algorithms will be discussed in the workshop.
Tensor-driven extraction of developmental features from varying paediatric EEG datasets.
Kinney-Lang, Eli; Spyrou, Loukianos; Ebied, Ahmed; Chin, Richard Fm; Escudero, Javier
2018-05-21
Constant changes in developing children's brains can pose a challenge in EEG dependant technologies. Advancing signal processing methods to identify developmental differences in paediatric populations could help improve function and usability of such technologies. Taking advantage of the multi-dimensional structure of EEG data through tensor analysis may offer a framework for extracting relevant developmental features of paediatric datasets. A proof of concept is demonstrated through identifying latent developmental features in resting-state EEG. Approach. Three paediatric datasets (n = 50, 17, 44) were analyzed using a two-step constrained parallel factor (PARAFAC) tensor decomposition. Subject age was used as a proxy measure of development. Classification used support vector machines (SVM) to test if PARAFAC identified features could predict subject age. The results were cross-validated within each dataset. Classification analysis was complemented by visualization of the high-dimensional feature structures using t-distributed Stochastic Neighbour Embedding (t-SNE) maps. Main Results. Development-related features were successfully identified for the developmental conditions of each dataset. SVM classification showed the identified features could accurately predict subject at a significant level above chance for both healthy and impaired populations. t-SNE maps revealed suitable tensor factorization was key in extracting the developmental features. Significance. The described methods are a promising tool for identifying latent developmental features occurring throughout childhood EEG. © 2018 IOP Publishing Ltd.
Haltigan, John D.; Leerkes, Esther M.; Wong, Maria S.; Fortuna, Keren; Roisman, Glenn I.; Supple, Andrew J.; O’Brien, Marion; Calkins, Susan D.; Plamondon, André
2017-01-01
The current study examined the developmental significance of mothers’ adult attachment representations assessed prenatally with the Adult Attachment Interview in relation to observed maternal sensitivity at 6 months postpartum in an ethnically diverse sample (N = 131 African American; N = 128 European American). Multiple groups confirmatory factor analyses provided evidence for partial measurement invariance of a two factor dismissing and preoccupied latent structure of adult attachment across the two ethnic groups of women. African American women showed modest elevations on the preoccupied factor relative to European American women. Although the dismissing factor showed an empirically equivalent negative association with maternal sensitivity in both ethnic groups, this effect was reduced to marginal significance when controlling for maternal socioeconomic status. PMID:24936609
LAT region factors mediating differential neuronal tropism of HSV-1 and HSV-2 do not act in trans.
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
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
Augmenting Latent Dirichlet Allocation and Rank Threshold Detection with Ontologies
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
Temperament Factor Structure in Fragile X Syndrome: The Children's Behavior Questionnaire
Roberts, Jane E.; Tonnsen, Bridgette L.; Robinson, Marissa; McQuillin, Samuel D.; Hatton, Deborah D.
2014-01-01
Early patterns of temperament lay the foundation for a variety of developmental constructs such as self-regulation, psychopathology, and resilience. Children with fragile X syndrome (FXS) display unique patterns of temperament compared to age-matched clinical and non-clinical samples, and early patterns of temperament have been associated with later anxiety in this population. Despite these unique patterns in FXS and recent reports of atypical factor structure of temperament questionnaires in Williams Syndrome (Leyfer, John, Woodruff-Borden, & Mervis, 2012), no studies have examined the latent factor structure of temperament scales in FXS to ensure measurement validity in this sample. The present study used confirmatory factor analysis to examine the factor structure of a well-validated parent-reported temperament questionnaire, the Children's Behavior Questionnaire (Rothbart, Ahadi, Hershey, & Fisher, 2001), in a sample of 90 males with FXS ages 3-9 years. Our data produced a similar, but not identical, three-factor model that retained the original CBQ factors of negative affectivity, effortful control, and extraversion/surgency. In particular, our FXS sample demonstrated stronger factor loadings for fear and shyness than previously reported loadings in non-clinical samples, consistent with reports of poor social approach and elevated anxiety in this population. Although the original factor structure of the Children's Behavior Questionnaire is largely retained in children with FXS, differences in factor loading magnitudes may reflect phenotypic characteristics of the syndrome. These findings may inform future developmental and translational research efforts. PMID:24380785
Perceived Stress Latent Factors and the Burnout Subtypes: A Structural Model in Dental Students
Montero-Marín, Jesús; Piva Demarzo, Marcelo Marcos; Stapinski, Lexine; Gili, Margarita; García-Campayo, Javier
2014-01-01
Background Students of health-professions suffer high levels of stress and burnout. The aim of the present study was to evaluate the relationship between perceived stress latent factors (‘tenseness’ and ‘frustration’) and the features (‘overload’, ‘lack of development’ and ‘neglect’) of the three burnout subtypes (‘frenetic’, ‘under-challenged’ and ‘worn-out’, respectively), in a sample of Spanish dental students. Methods The study employed a cross-sectional design. A sample of Spanish dental students (n = 314) completed the ‘Perceived Stress Questionnaire’ and the ‘Burnout Clinical Subtype Questionnaire Student Survey’. The associations among variables were observed by means of structural equation modelling using the unweighted least squares method from polychoric correlations. Results Strong associations among perceived stress factors and the burnout characteristics were observed, although a distinct pattern of relations was observed for each burnout subtype. The ‘overload’ was moderately and positively associated with both ‘tenseness’ (0.45), and ‘frustration’ (0.38) dimensions of perceived stress; the ‘lack of development’ was positively associated with the ‘frustration’ dimension (0.72), but negatively associated with ‘tenseness’ (−0.69); the ‘neglect’ showed a weaker positive associated with ‘frustration’ (0.41), and a small negative association with ‘tenseness’ (−0.20). The model was a very good fit to the data (GFI = 0.96; RSMR = 0.07; AGFI = 0.96; NFI = 0.95; RFI = 0.95). Conclusions The stress factors of ‘frustration’ and ‘tenseness’ seems to be related in a distinct way to the burnout subtypes in Spanish dental students. This finding suggests that intervention programs specifically tailored to these subtypes may be a promising future direction. PMID:24927260
Familiar, Itziar; Murray, Laura; Gross, Alden; Skavenski, Stephanie; Jere, Elizabeth; Bass, Judith
2014-01-01
Background Scant information exists on PTSD symptoms and structure in youth from developing countries. Methods We describe the symptom profile and exposure to trauma experiences among 343 orphan and vulnerable children and adolescents from Zambia. We distinguished profiles of post-traumatic stress symptoms using latent class analysis. Results Average number of trauma-related symptoms (21.6; range 0-38) was similar across sex and age. Latent class model suggested 3 classes varying by level of severity: low (31% of the sample), medium (45% of the sample), and high (24% of the sample) symptomatology. Conclusions Results suggest that PTSD is a continuously distributed latent trait. PMID:25382359
A lattice protein with an amyloidogenic latent state: stability and folding kinetics.
Palyanov, Andrey Yu; Krivov, Sergei V; Karplus, Martin; Chekmarev, Sergei F
2007-03-15
We have designed a model lattice protein that has two stable folded states, the lower free energy native state and a latent state of somewhat higher energy. The two states have a sizable part of their structures in common (two "alpha-helices") and differ in the content of "alpha-helices" and "beta-strands" in the rest of their structures; i.e. for the native state, this part is alpha-helical, and for the latent state it is composed of beta-strands. Thus, the lattice protein free energy surface mimics that of amyloidogenic proteins that form well organized fibrils under appropriate conditions. A Go-like potential was used and the folding process was simulated with a Monte Carlo method. To gain insight into the equilibrium free energy surface and the folding kinetics, we have combined standard approaches (reduced free energy surfaces, contact maps, time-dependent populations of the characteristic states, and folding time distributions) with a new approach. The latter is based on a principal coordinate analysis of the entire set of contacts, which makes possible the introduction of unbiased reaction coordinates and the construction of a kinetic network for the folding process. The system is found to have four characteristic basins, namely a semicompact globule, an on-pathway intermediate (the bifurcation basin), and the native and latent states. The bifurcation basin is shallow and consists of the structure common to the native and latent states, with the rest disorganized. On the basis of the simulation results, a simple kinetic model describing the transitions between the characteristic states was developed, and the rate constants for the essential transitions were estimated. During the folding process the system dwells in the bifurcation basin for a relatively short time before it proceeds to the native or latent state. We suggest that such a bifurcation may occur generally for proteins in which native and latent states have a sizable part of their structures in common. Moreover, there is the possibility of introducing changes in the system (e.g., mutations), which guide the system toward the native or misfolded state.
Generalized Structured Component Analysis with Uniqueness Terms for Accommodating Measurement Error
Hwang, Heungsun; Takane, Yoshio; Jung, Kwanghee
2017-01-01
Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling (SEM), where latent variables are approximated by weighted composites of indicators. It has no formal mechanism to incorporate errors in indicators, which in turn renders components prone to the errors as well. We propose to extend GSCA to account for errors in indicators explicitly. This extension, called GSCAM, considers both common and unique parts of indicators, as postulated in common factor analysis, and estimates a weighted composite of indicators with their unique parts removed. Adding such unique parts or uniqueness terms serves to account for measurement errors in indicators in a manner similar to common factor analysis. Simulation studies are conducted to compare parameter recovery of GSCAM and existing methods. These methods are also applied to fit a substantively well-established model to real data. PMID:29270146
Psychometrics and latent structure of the IDS and QIDS with young adult students.
González, David Andrés; Boals, Adriel; Jenkins, Sharon Rae; Schuler, Eric R; Taylor, Daniel
2013-07-01
Students and young adults have high rates of suicide and depression, thus are a population of interest. To date, there is no normative psychometric information on the IDS and QIDS in these populations. Furthermore, there is equivocal evidence on the factor structure and subscales of the IDS. Two samples of young adult students (ns=475 and 1681) were given multiple measures to test the psychometrics and dimensionality of the IDS and QIDS. The IDS, its subscales, and QIDS had acceptable internal consistencies (αs=.79-90) and favorable convergent and divergent validity correlations. A three-factor structure and two Rasch-derived subscales best fit the IDS. The samples were collected from one university, which may influence generalizability. The IDS and QIDS are desirable measures of depressive symptoms when studying young adult students. Copyright © 2013 Elsevier B.V. All rights reserved.
Mehralizadeh, Semira; Dehdashti, Alireza; Motalebi Kashani, Masoud
2017-01-01
Statistics indicate a high risk of developing work-related musculoskeletal disorders among hospital nurses. The challenge is to understand the associations between musculoskeletal symptoms and various individual and occupational risk factors. This study examined the direct and indirect interactions of various risk factors with musculoskeletal complaints in hospital nurses. In a cross-sectional design, Iranian hospital nurses from Semnan University of Medical Sciences participated in a questionnaire survey reporting their perceived perceptions of various work-related risk factors and musculoskeletal symptoms. We tested our proposed structural equation model to evaluate the relations between latent and observed concepts and the relative importance and strength of exogenous variables in explaining endogenous musculoskeletal complaints. Measurement model fits the data relatively acceptable. Our findings showed direct effects of psychological, role-related and work posture stressors on musculoskeletal complaints. Fatigue mediated the adverse indirect relations of psychological, role-related, work posture and individual factors with musculoskeletal complaints. Structural equation modeling may provide methodological opportunities in occupational health research with a potential to explain the complexity of interactions among risk factors. Prevention of work-related musculoskeletal disorders among nurses must account for physical and psychosocial conditions.
Factor structure and clinical correlates of the 61-item Wender Utah Rating Scale (WURS).
Calamia, Matthew; Hill, Benjamin D; Musso, Mandi W; Pella, Russell D; Gouvier, Wm Drew
2018-02-09
The objective of this study was to assess the factor structure and clinical correlates of a 61-item version of the Wender Utah Rating Scale (WURS), a self-report retrospective measure of childhood problems, experiences, and behavior used in ADHD assessment. Given the currently mostly widely used form of the WURS was derived via a criterion-keyed approach, the study aimed to use latent variable modeling of the 61-item WURS to potentially identify more and more homogeneous set of items reflecting current conceptualizations of ADHD symptoms. Exploratory structural equation modeling was used to generate factor scores which were then correlated with neuropsychological measures of intelligence and executive attention as well as a broad measure of personality and emotional functioning. Support for a modified five-factor model was found: ADHD, disruptive mood and behavior, negative affectivity, social confidence, and academic problems. The ADHD factor differed somewhat from the traditional 25-item WURS short form largely through weaker associations with several measures of personality and psychopathology. This study identified a factor more aligned with DSM-5 conceptualization of ADHD as well as measures of other types of childhood characteristics and symptoms which may prove useful for both research and clinical practice.
Latent Heating Retrievals Using the TRMM Precipitation Radar: A Multi-Seasonal Study
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Lang, S.; Meneghini, R.; Halverson, J.; Johnson, R.; Simpson, J.; Einaudi, Franco (Technical Monitor)
2001-01-01
Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid, and solid water. Present largescale weather and climate models can simulate latent heat release only crudely, thus reducing their confidence in predictions on both global and regional scales. This paper represents the first attempt to use NASA Tropical Rainfall Measuring Mission (TRMM) rainfall information to estimate the four-dimensional structure of global monthly latent heating profiles over the global tropics from December 1997 to October 2000. The Goddard Convective-Stratiform. Heating (CSH) algorithm and TRMM precipitation radar data are used for this study. We will examine and compare the latent heating structures between 1997-1998 (winter) ENSO and 1998-2000 (non-ENSO). We will also examine over the tropics. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental; Indian oceans vs west Pacific; Africa vs S. America) will be also examined and compared. In addition, we will examine the relationship between latent heating (max heating level) and SST. The period of interest also coincides with several TRMM field campaigns that recently occurred over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and in the central Pacific in 1999 (KWAJEX). Sounding diagnosed Q1 budgets from these experiments could provide a means of validating the retrieved profiles of latent heating from the CSH algorithm.
Discriminative latent models for recognizing contextual group activities.
Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N; Mori, Greg
2012-08-01
In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities.
Discriminative Latent Models for Recognizing Contextual Group Activities
Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N.; Mori, Greg
2012-01-01
In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities. PMID:22144516
Understanding the latent structure of the emotional disorders in children and adolescents.
Trosper, Sarah E; Whitton, Sarah W; Brown, Timothy A; Pincus, Donna B
2012-05-01
Investigators are persistently aiming to clarify structural relationships among the emotional disorders in efforts to improve diagnostic classification. The high co-occurrence of anxiety and mood disorders, however, has led investigators to portray the current structure of anxiety and depression in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV, APA 2000) as more descriptive than empirical. This study assesses various structural models in a clinical sample of youths with emotional disorders. Three a priori factor models were tested, and the model that provided the best fit to the data showed the dimensions of anxiety and mood disorders to be hierarchically organized within a single, higher-order factor. This supports the prevailing view that the co-occurrence of anxiety and mood disorders in children is in part due to a common vulnerability (e.g., negative affectivity). Depression and generalized anxiety loaded more highly onto the higher-order factor than the other disorders, a possible explanation for the particularly high rates of comorbidity between the two. Implications for the taxonomy and treatment of mood and anxiety disorders for children and adolescents are discussed.
Trull, Timothy J.; Vergés, Alvaro; Wood, Phillip K.; Jahng, Seungmin; Sher, Kenneth J.
2013-01-01
We examined the latent structure underlying the criteria for DSM–IV–TR (American Psychiatric Association, 2000, Diagnostic and statistical manual of mental disorders (4th ed., text revision). Washington, DC: Author.) personality disorders in a large nationally representative sample of U.S. adults. Personality disorder symptom data were collected using a structured diagnostic interview from approximately 35,000 adults assessed over two waves of data collection in the National Epidemiologic Survey on Alcohol and Related Conditions. Our analyses suggested that a seven-factor solution provided the best fit for the data, and these factors were marked primarily by one or at most two personality disorder criteria sets. A series of regression analyses that used external validators tapping Axis I psychopathology, treatment for mental health problems, functioning scores, interpersonal conflict, and suicidal ideation and behavior provided support for the seven-factor solution. We discuss these findings in the context of previous studies that have examined the structure underlying the personality disorder criteria as well as the current proposals for DSM-5 personality disorders. PMID:22506626
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
ERIC Educational Resources Information Center
Farrell, Albert D.; Sullivan, Terri N.; Esposito, Layla E.; Meyer, Aleta L.; Valois, Robert F.
2005-01-01
Latent growth curve analysis was used to examine the structure and interrelations among aggression, drug use, and delinquent behavior during early adolescence. Five waves of data were collected from 667 students at three urban middle schools serving a predominantly African American population, and from a more ethnically diverse sample of 950…
Toward a Model-Based Approach to the Clinical Assessment of Personality Psychopathology
Eaton, Nicholas R.; Krueger, Robert F.; Docherty, Anna R.; Sponheim, Scott R.
2015-01-01
Recent years have witnessed tremendous growth in the scope and sophistication of statistical methods available to explore the latent structure of psychopathology, involving continuous, discrete, and hybrid latent variables. The availability of such methods has fostered optimism that they can facilitate movement from classification primarily crafted through expert consensus to classification derived from empirically-based models of psychopathological variation. The explication of diagnostic constructs with empirically supported structures can then facilitate the development of assessment tools that appropriately characterize these constructs. Our goal in this paper is to illustrate how new statistical methods can inform conceptualization of personality psychopathology and therefore its assessment. We use magical thinking as example, because both theory and earlier empirical work suggested the possibility of discrete aspects to the latent structure of personality psychopathology, particularly forms of psychopathology involving distortions of reality testing, yet other data suggest that personality psychopathology is generally continuous in nature. We directly compared the fit of a variety of latent variable models to magical thinking data from a sample enriched with clinically significant variation in psychotic symptomatology for explanatory purposes. Findings generally suggested a continuous latent variable model best represented magical thinking, but results varied somewhat depending on different indices of model fit. We discuss the implications of the findings for classification and applied personality assessment. We also highlight some limitations of this type of approach that are illustrated by these data, including the importance of substantive interpretation, in addition to use of model fit indices, when evaluating competing structural models. PMID:24007309
The structure of musical preferences: a five-factor model.
Rentfrow, Peter J; Goldberg, Lewis R; Levitin, Daniel J
2011-06-01
Music is a cross-cultural universal, a ubiquitous activity found in every known human culture. Individuals demonstrate manifestly different preferences in music, and yet relatively little is known about the underlying structure of those preferences. Here, we introduce a model of musical preferences based on listeners' affective reactions to excerpts of music from a wide variety of musical genres. The findings from 3 independent studies converged to suggest that there exists a latent 5-factor structure underlying music preferences that is genre free and reflects primarily emotional/affective responses to music. We have interpreted and labeled these factors as (a) a Mellow factor comprising smooth and relaxing styles; (b) an Unpretentious factor comprising a variety of different styles of sincere and rootsy music such as is often found in country and singer-songwriter genres; (c) a Sophisticated factor that includes classical, operatic, world, and jazz; (d) an Intense factor defined by loud, forceful, and energetic music; and (e) a Contemporary factor defined largely by rhythmic and percussive music, such as is found in rap, funk, and acid jazz. The findings from a fourth study suggest that preferences for the MUSIC factors are affected by both the social and the auditory characteristics of the music. 2011 APA, all rights reserved
Predicting aggression in children with ADHD
2014-01-01
Objective The present study uses structural equation modeling of latent traits to examine the extent to which family factors, cognitive factors and perceptions of rejection in mother-child relations differentially correlate with aggression at home and at school. Methods Data were collected from 476 school-age (7–15 years old) children with a diagnosis of ADHD who had previously shown different types of aggressive behavior, as well as from their parents and teachers. Structural equation modeling was used to examine the differential relationships between maternal rejection, family, cognitive factors and aggression in home and school settings. Results Family factors influenced aggression reported at home (.68) and at school (.44); maternal rejection seems to be related to aggression at home (.21). Cognitive factors influenced aggression reported at school (.-05) and at home (-.12). Conclusions Both genetic and environmental factors contribute to the development of aggressive behavior in ADHD. Identifying key risk factors will advance the development of appropriate clinical interventions and prevention strategies and will provide information to guide the targeting of resources to those children at highest risk. PMID:24860616
The genetic and environmental etiology of antisocial behavior from childhood to emerging adulthood.
Tuvblad, Catherine; Narusyte, Jurgita; Grann, Martin; Sarnecki, Jerzy; Lichtenstein, Paul
2011-09-01
Previous research suggests that both genetic and environmental influences are important for antisocial behavior across the life span, even though the prevalence and incidence of antisocial behavior varies considerably across ages. However, little is known of how genetic and environmental effects influence the development of antisocial behavior. A total of 2,600 male and female twins from the population-based Swedish Twin Registry were included in the present study. Antisocial behavior was measured on four occasions, when twins were 8-9, 13-14, 16-17, and 19-20 years old. Longitudinal analyses of the data were conducted using structural equation modeling. The stability of antisocial behavior over time was explained by a common latent persistent antisocial behavior factor. A common genetic influence accounted for 67% of the total variance in this latent factor, the shared environment explained 26%, and the remaining 7% was due to the non-shared environment. Significant age-specific shared environmental factors were found at ages 13-14 years, suggesting that common experiences (e.g., peers) are important for antisocial behavior at this age. Results from this study show that genetic as well as shared environmental influences are important in antisocial behavior that persists from childhood to emerging adulthood.
Tuberculosis and latent tuberculosis infection among healthcare workers in Kisumu, Kenya.
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.
Longitudinal Measurement Invariance of Posttraumatic Stress Disorder in Deployed Marines.
Contractor, Ateka A; Bolton, Elisa; Gallagher, Matthew W; Rhodes, Charla; Nash, William P; Litz, Brett
2017-06-01
The meaningful interpretation of longitudinal study findings requires temporal stability of the constructs assessed (i.e., measurement invariance). We sought to examine measurement invariance of the construct of posttraumatic stress disorder (PTSD) as based on the Diagnostic and Statistical Manual of Mental Disorders indexed by the PTSD Checklist (PCL) and the Clinician-Administered PTSD Scale (CAPS) in a sample of 834 Marines with significant combat experience. PTSD was assessed 1-month predeployment (T0), and again at 1-month (T1), 5-months (T2), and 8-months postdeployment (T3). We tested configural (pattern of item/parcel loadings), metric (item/parcel loadings on latent factors), and scalar (item/parcel-level severity) invariance and explored sources of measurement instability (partial invariance testing). The T0 best-fitting emotional numbing model factor structure informed the conceptualization of PTSD's latent factors and parcel formations. We found (1) scalar noninvariance for the construct of PTSD as measured by the PCL and the CAPS, and for PTSD symptom clusters as assessed by the CAPS; and (2) metric noninvariance for PTSD symptom clusters as measured by the PCL. Exploratory analyses revealed factor-loading and intercept differences from pre- to postdeployment for avoidance symptoms, numbing symptoms (mainly psychogenic amnesia and foreshortened future), and the item assessing startle, each of which reduced construct stability. Implications of these findings for longitudinal studies of PTSD are discussed. Copyright © 2017 International Society for Traumatic Stress Studies.
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.
Validity test and its consistency in the construction of patient loyalty model
NASA Astrophysics Data System (ADS)
Yanuar, Ferra
2016-04-01
The main objective of this present study is to demonstrate the estimation of validity values and its consistency based on structural equation model. The method of estimation was then implemented to an empirical data in case of the construction the patient loyalty model. In the hypothesis model, service quality, patient satisfaction and patient loyalty were determined simultaneously, each factor were measured by any indicator variables. The respondents involved in this study were the patients who ever got healthcare at Puskesmas in Padang, West Sumatera. All 394 respondents who had complete information were included in the analysis. This study found that each construct; service quality, patient satisfaction and patient loyalty were valid. It means that all hypothesized indicator variables were significant to measure their corresponding latent variable. Service quality is the most measured by tangible, patient satisfaction is the most mesured by satisfied on service and patient loyalty is the most measured by good service quality. Meanwhile in structural equation, this study found that patient loyalty was affected by patient satisfaction positively and directly. Service quality affected patient loyalty indirectly with patient satisfaction as mediator variable between both latent variables. Both structural equations were also valid. This study also proved that validity values which obtained here were also consistence based on simulation study using bootstrap approach.
Armour, Cherie; Layne, Christopher M; Naifeh, James A; Shevlin, Mark; Duraković-Belko, Elvira; Djapo, Nermin; Pynoos, Robert S; Elhai, Jon D
2011-01-01
Posttraumatic stress disorder's (PTSD) tripartite factor structure proposed by the DSM-IV is rarely empirically supported. Other four-factor models (King et al., 1998; Simms et al., 2002) have proven to better account for PTSD's latent structure; however, results regarding model superiority are conflicting. The current study assessed whether endorsement of PTSD's Criterion A2 would impact on the factorial invariance of the King et al. (1998) model. Participants were 1572 war-exposed Bosnian secondary students who were assessed two years following the 1992-1995 Bosnian conflict. The sample was grouped by those endorsing both parts of the DSM-IV Criterion A (A2 Group) and those endorsing only A1 (Non-A2 Group). The factorial invariance of the King et al. (1998) model was not supported between the A2 vs. Non-A2 Groups; rather, the groups significantly differed on all model parameters. The impact of removing A2 on the factor structure of King et al. (1998) PTSD model is discussed in light of the proposed removal of Criterion A2 for the DSM-V. Copyright © 2010 Elsevier Ltd. All rights reserved.
Scherer, Ronny; Nilsen, Trude; Jansen, Malte
2016-01-01
Students' perceptions of instructional quality are among the most important criteria for evaluating teaching effectiveness. The present study evaluates different latent variable modeling approaches (confirmatory factor analysis, exploratory structural equation modeling, and bifactor modeling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance, and the relations to selected educational outcomes (achievement, self-concept, and motivation in mathematics). On the basis of the Programme for International Student Assessment (PISA) 2012 large-scale data sets of Australia, Canada, and the USA (N = 26,746 students), we find support for the distinction between three factors of individual students' perceptions and full measurement invariance across countries for all modeling approaches. In this regard, bifactor exploratory structural equation modeling outperformed alternative approaches with respect to model fit. Our findings reveal significant relations to the educational outcomes. This study synthesizes different modeling approaches of individual students' perceptions of instructional quality and provides insights into the nature of these perceptions from an individual differences perspective. Implications for the measurement and modeling of individually perceived instructional quality are discussed. PMID:26903917
Bayesian structural equation modeling: a more flexible representation of substantive theory.
Muthén, Bengt; Asparouhov, Tihomir
2012-09-01
This article proposes a new approach to factor analysis and structural equation modeling using Bayesian analysis. The new approach replaces parameter specifications of exact zeros with approximate zeros based on informative, small-variance priors. It is argued that this produces an analysis that better reflects substantive theories. The proposed Bayesian approach is particularly beneficial in applications where parameters are added to a conventional model such that a nonidentified model is obtained if maximum-likelihood estimation is applied. This approach is useful for measurement aspects of latent variable modeling, such as with confirmatory factor analysis, and the measurement part of structural equation modeling. Two application areas are studied, cross-loadings and residual correlations in confirmatory factor analysis. An example using a full structural equation model is also presented, showing an efficient way to find model misspecification. The approach encompasses 3 elements: model testing using posterior predictive checking, model estimation, and model modification. Monte Carlo simulations and real data are analyzed using Mplus. The real-data analyses use data from Holzinger and Swineford's (1939) classic mental abilities study, Big Five personality factor data from a British survey, and science achievement data from the National Educational Longitudinal Study of 1988.
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).
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 Structure Agreement Analysis
1989-11-01
correct for bias in estimation of disease prevalence due to misclassification error [39]. Software Varying panel latent class agreement models can be...D., and L. M. Irwig, "Estimation of Test Error Rates, Disease Prevalence and Relative Risk from Misclassified Data: A Review," Journal of Clinical
Exline, David L; Wallace, Christie; Roux, Claude; Lennard, Chris; Nelson, Matthew P; Treado, Patrick J
2003-09-01
Chemical imaging technology is a rapid examination technique that combines molecular spectroscopy and digital imaging, providing information on morphology, composition, structure, and concentration of a material. Among many other applications, chemical imaging offers an array of novel analytical testing methods, which limits sample preparation and provides high-quality imaging data essential in the detection of latent fingerprints. Luminescence chemical imaging and visible absorbance chemical imaging have been successfully applied to ninhydrin, DFO, cyanoacrylate, and luminescent dye-treated latent fingerprints, demonstrating the potential of this technology to aid forensic investigations. In addition, visible absorption chemical imaging has been applied successfully to visualize untreated latent fingerprints.
Non-destructive forensic latent fingerprint acquisition with chromatic white light sensors
NASA Astrophysics Data System (ADS)
Leich, Marcus; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus
2011-02-01
Non-destructive latent fingerprint acquisition is an emerging field of research, which, unlike traditional methods, makes latent fingerprints available for additional verification or further analysis like tests for substance abuse or age estimation. In this paper a series of tests is performed to investigate the overall suitability of a high resolution off-the-shelf chromatic white light sensor for the contact-less and non-destructive latent fingerprint acquisition. Our paper focuses on scanning previously determined regions with exemplary acquisition parameter settings. 3D height field and reflection data of five different latent fingerprints on six different types of surfaces (HDD platter, brushed metal, painted car body (metallic and non-metallic finish), blued metal, veneered plywood) are experimentally studied. Pre-processing is performed by removing low-frequency gradients. The quality of the results is assessed subjectively; no automated feature extraction is performed. Additionally, the degradation of the fingerprint during the acquisition period is observed. While the quality of the acquired data is highly dependent on surface structure, the sensor is capable of detecting the fingerprint on all sample surfaces. On blued metal the residual material is detected; however, the ridge line structure dissolves within minutes after fingerprint placement.
Semiparametric Time-to-Event Modeling in the Presence of a Latent Progression Event
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.
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.
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...
McCurley, Jessica L; Penedo, Frank; Roesch, Scott C; Isasi, Carmen R; Carnethon, Mercedes; Sotres-Alvarez, Daniela; Schneiderman, Neil; Gonzalez, Patricia; Chirinos, Diana A; Camacho, Alvaro; Teng, Yanping; Gallo, Linda C
2017-08-01
U.S. Hispanics/Latinos display a high prevalence of metabolic syndrome (MetSyn), a group of co-occurring cardiometabolic risk factors (abdominal obesity, impaired fasting glucose, dyslipidemia, elevated blood pressure) associated with higher cardiovascular disease and mortality risk. Low socioeconomic status (SES) is associated with higher risk for MetSyn in Hispanics/Latinos, and psychosocial factors may play a role in this relationship. This cross-sectional study examined psychosocial factors in the association of SES and MetSyn components in 4,996 Hispanic/Latino adults from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Sociocultural Ancillary Study. MetSyn components were measured at the baseline examination. Participants completed interviews to determine psychosocial risks (e.g., depression) and resources (e.g., social support) within 9 months of baseline (< 4 months in 72.6% of participants). Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to identify latent constructs and examine associations. Participant mean age was 41.7 years (SE = 0.4) and 62.7% were female. CFA identified single latent factors for SES and psychosocial indicators, and three factors for MetSyn [blood pressure, lipids, metabolic factors]. SEMs showed that lower SES was related to MetSyn factors indirectly through higher psychosocial risk/lower resources (Y-Bχ 2 (df = 420) = 4412.90, p < .05, RMSEA = .042, SRMR = .051). A statistically significant effect consistent with mediation was found from lower SES to higher metabolic risk (glucose/waist circumference) via psychosocial risk/resource variables (Mackinnon's 95% asymmetric CI = -0.13 to -0.02). SES is related to metabolic variables indirectly through psychosocial factors in U.S. Hispanics/Latinos of diverse ancestries.
Neumann, Craig S.; Malterer, Melanie B.; Newman, Joseph P.
2010-01-01
Recent exploratory factor analysis (EFA) of the Psychopathic Personality Inventory (PPI; Lilienfeld, 1990) with a community sample suggested that the PPI subscales may be comprised of two higher-order factors (Benning et al., 2003). However, little research has examined the PPI structure in offenders. The current study attempted to replicate the Benning et al. two-factor solution using a large (N=1224) incarcerated male sample. Confirmatory factor analysis (CFA) of this model with the full sample resulted in poor model fit. Next, to identify a factor solution that would summarize the offender data, EFA was conducted using a split-half of the total sample, followed by an attempt to replicate the EFA solution via CFA with the other split-half sample. Using the recommendations of Prooijen and van der Kloot (2001) for recovering EFA solutions, model fit results provided some evidence that the EFA solution could be recovered via CFA. However, this model involved extensive cross-loadings of the subscales across three factors, suggesting item overlap across PPI subscales. In sum, the two-factor solution reported by Benning et al. (2003) was not a viable model for the current sample of offenders, and additional research is needed to elucidate the latent structure of the PPI. PMID:18557694
A new dimension of organizational justice: procedural voice.
Jepsen, Denise; Rodwell, John
2009-10-01
Dimensionality of the Colquitt justice measures was investigated across a wide range of service occupations. Structural equation modeling of data from 410 survey respondents found support for the 4-factor model of justice (procedural, distributive, interpersonal, and informational), although significant improvement of model fit was obtained by including a new latent variable, "procedural voice," which taps employees' desire to express their views and feelings and influence results. The model was confirmed in a second sample (N = 505) in the same organization six months later.
Tsigilis, Nikolaos; Gregoriadis, Athanasios; Grammatikopoulos, Vasilis; Zachopoulou, Evridiki
2018-01-01
Teacher-child relationships in early childhood are a fundamental prerequisite for children's social, emotional, and academic development. The Student-Teacher Relationship Scale (STRS) is one of the most widely accepted and used instruments that evaluate the quality of teacher-child relationships. STRS is a 28-item questionnaire that assess three relational dimensions, Closeness, Conflict, and Dependency. The relevant literature has shown a pattern regarding the difficulty to support the STRS factor structure with CFA, while it is well-documented with EFA. Recently, a new statistical technique was proposed to combine the best of the CFA and EFA namely, the Exploratory Structural Equation Modeling (ESEM). The purpose of this study was (a) to examine the factor structure of the STRS in a Greek national sample. Toward this end, the ESEM framework was applied in order to overcome the limitations of EFA and CFA, (b) to confirm previous findings about the cultural influence in teacher-child relationship patterns, and (c) to examine the invariance of STRS across gender and age. Early educators from a representative Greek sample size of 535 child care and kindergarten centers completed the STRS for 4,158 children. CFA as well as ESEM procedures were implemented. Results showed that ESEM provided better fit to the data than CFA in both groups, supporting the argument that CFA is an overly restrictive approach in comparison to ESEM for the study of STRS. All primary loadings were statistically significant and were associated with their respective latent factors. Contrary to the existing literature conducted in USA and northern Europe, the association between Closeness and Dependency yielded a positive correlation. This finding is in line with previous studies conducted in Greece and confirm the existence of cultural differences in teacher-child relationships. In addition, findings supported the configural, metric, scalar, and variance/covariance equivalence of the STRS between males and females and between preschoolers (3-5 years) and early primary years (5-7 years). Latent factor means comparisons showed that females seem to have a warmer and more dependent relationship with their teachers and are less conflictual in comparison to males.
Tsigilis, Nikolaos; Gregoriadis, Athanasios; Grammatikopoulos, Vasilis; Zachopoulou, Evridiki
2018-01-01
Teacher-child relationships in early childhood are a fundamental prerequisite for children's social, emotional, and academic development. The Student-Teacher Relationship Scale (STRS) is one of the most widely accepted and used instruments that evaluate the quality of teacher-child relationships. STRS is a 28-item questionnaire that assess three relational dimensions, Closeness, Conflict, and Dependency. The relevant literature has shown a pattern regarding the difficulty to support the STRS factor structure with CFA, while it is well-documented with EFA. Recently, a new statistical technique was proposed to combine the best of the CFA and EFA namely, the Exploratory Structural Equation Modeling (ESEM). The purpose of this study was (a) to examine the factor structure of the STRS in a Greek national sample. Toward this end, the ESEM framework was applied in order to overcome the limitations of EFA and CFA, (b) to confirm previous findings about the cultural influence in teacher-child relationship patterns, and (c) to examine the invariance of STRS across gender and age. Early educators from a representative Greek sample size of 535 child care and kindergarten centers completed the STRS for 4,158 children. CFA as well as ESEM procedures were implemented. Results showed that ESEM provided better fit to the data than CFA in both groups, supporting the argument that CFA is an overly restrictive approach in comparison to ESEM for the study of STRS. All primary loadings were statistically significant and were associated with their respective latent factors. Contrary to the existing literature conducted in USA and northern Europe, the association between Closeness and Dependency yielded a positive correlation. This finding is in line with previous studies conducted in Greece and confirm the existence of cultural differences in teacher-child relationships. In addition, findings supported the configural, metric, scalar, and variance/covariance equivalence of the STRS between males and females and between preschoolers (3–5 years) and early primary years (5–7 years). Latent factor means comparisons showed that females seem to have a warmer and more dependent relationship with their teachers and are less conflictual in comparison to males. PMID:29867688
Costa, Danielle Cristina Silva; Ribeiro, Marizélia Rodrigues Costa; Batista, Rosângela Fernandes Lucena; Valente, Camila Maia; Ribeiro, João Victor Fonseca; Almeida, Laysa Andrade; Costa, Ludmilla Emilia Martins; Alves, Maria Teresa Seabra Soares de Britto E; Silva, Antônio Augusto Moura da
2017-01-23
The factors associated with physical violence against pregnant women were analyzed in a cross-sectional study of 1,446 pregnant women from a prenatal cohort who were interviewed in 2010 and 2011 in São Luís, Brazil. In the initial model, socioeconomic status occupied the most distal position, determining sociodemographic factors, social support and the behavioral factors that ultimately determined physical violence, which was investigated as a latent variable. Structural equation modeling was used in the analysis. Pregnant women who were from more disadvantaged backgrounds (p = 0.027), did not reside with intimate partners (p = 0.005), had low social support (p < 0.001) and had a high number of lifetime intimate partners (p = 0.001) reported more episodes of physical violence. Low social support was the primary mediator of the effect of socioeconomic status on physical violence. The effect of marital status was mainly mediated by a high number of lifetime intimate partners.
Giesbrecht, Chantelle J; O'Rourke, Norm; Leonova, Olga; Strehlau, Verena; Paquet, Karine; Vila-Rodriguez, Fidel; Panenka, William J; MacEwan, G William; Smith, Geoffrey N; Thornton, Allen E; Honer, William G
2016-01-01
Rates of psychopathology are elevated in marginalized and unstably housed persons, underscoring the need for applicable clinical measures for these populations. The Positive and Negative Syndrome Scale (PANSS) is a clinical instrument principally developed for use in schizophrenia to identify the presence and severity of psychopathology symptoms. The current study investigates whether a reliable and valid PANSS factor structure emerges in a marginally housed, heterogeneous sample recruited from the Downtown Eastside of Vancouver where substance use disorders and psychiatric illness are pervasive. Participants (n = 270) underwent structured clinical assessments including the PANSS and then were randomly assigned to either exploratory (EFA) or confirmatory factor analytic (CFA) subsamples. EFA pointed to a novel three factor PANSS. This solution was supported by CFA. All retained items (28 out of 30) load significantly upon hypothesized factors and model goodness of fit analyses are in the acceptable to good range. Each of the three first-order factor constructs, labeled Psychosis/Disorganized, Negative Symptoms/Hostility, and Insight/Awareness, contributed significantly to measurement of a higher-order psychopathology construct. Further, the latent structure of this 3-factor solution appears temporally consistent over one-year. This PANSS factor structure appears valid and reliable for use in persons with multimorbidity, including substance use disorders. The structure is somewhat distinct from existing solutions likely due to the unique characteristics of this marginally housed sample.
Giesbrecht, Chantelle J.; O’Rourke, Norm; Leonova, Olga; Strehlau, Verena; Paquet, Karine; Vila-Rodriguez, Fidel; Panenka, William J.; MacEwan, G. William; Smith, Geoffrey N.; Thornton, Allen E.; Honer, William G.
2016-01-01
Rates of psychopathology are elevated in marginalized and unstably housed persons, underscoring the need for applicable clinical measures for these populations. The Positive and Negative Syndrome Scale (PANSS) is a clinical instrument principally developed for use in schizophrenia to identify the presence and severity of psychopathology symptoms. The current study investigates whether a reliable and valid PANSS factor structure emerges in a marginally housed, heterogeneous sample recruited from the Downtown Eastside of Vancouver where substance use disorders and psychiatric illness are pervasive. Participants (n = 270) underwent structured clinical assessments including the PANSS and then were randomly assigned to either exploratory (EFA) or confirmatory factor analytic (CFA) subsamples. EFA pointed to a novel three factor PANSS. This solution was supported by CFA. All retained items (28 out of 30) load significantly upon hypothesized factors and model goodness of fit analyses are in the acceptable to good range. Each of the three first-order factor constructs, labeled Psychosis/Disorganized, Negative Symptoms/Hostility, and Insight/Awareness, contributed significantly to measurement of a higher-order psychopathology construct. Further, the latent structure of this 3-factor solution appears temporally consistent over one-year. This PANSS factor structure appears valid and reliable for use in persons with multimorbidity, including substance use disorders. The structure is somewhat distinct from existing solutions likely due to the unique characteristics of this marginally housed sample. PMID:26999280
Autonomy and social norms in a three factor grief model predicting perinatal grief in India.
Roberts, Lisa R; Lee, Jerry W
2014-01-01
Perinatal grief following stillbirth is a significant social and mental health burden. We examined associations among the following latent variables: autonomy, social norms, self-despair, strained coping, and acute grief-among poor, rural women in India who experienced stillbirth. A structural equation model was built and tested using quantitative data from 347 women of reproductive age in Chhattisgarh. Maternal acceptance of traditional social norms worsens self-despair and strained coping, and increases the autonomy granted to women. Greater autonomy increases acute grief. Greater despair and acute grief increase strained coping. Social and cultural factors were found to predict perinatal grief in India.
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
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.
Hounkpatin, Hilda Osafo; Boyce, Christopher J; Dunn, Graham; Wood, Alex M
2017-09-18
A number of structural equation models have been developed to examine change in 1 variable or the longitudinal association between 2 variables. The most common of these are the latent growth model, the autoregressive cross-lagged model, the autoregressive latent trajectory model, and the latent change score model. The authors first overview each of these models through evaluating their different assumptions surrounding the nature of change and how these assumptions may result in different data interpretations. They then, to elucidate these issues in an empirical example, examine the longitudinal association between personality traits and life satisfaction. In a representative Dutch sample (N = 8,320), with participants providing data on both personality and life satisfaction measures every 2 years over an 8-year period, the authors reproduce findings from previous research. However, some of the structural equation models overviewed have not previously been applied to the personality-life satisfaction relation. The extended empirical examination suggests intraindividual changes in life satisfaction predict subsequent intraindividual changes in personality traits. The availability of data sets with 3 or more assessment waves allows the application of more advanced structural equation models such as the autoregressive latent trajectory or the extended latent change score model, which accounts for the complex dynamic nature of change processes and allows stronger inferences on the nature of the association between variables. However, the choice of model should be determined by theories of change processes in the variables being studied. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Tenascin-X promotes epithelial-to-mesenchymal transition by activating latent TGF-β
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
Obasi, Ezemenari M; Brooks, Jessica J; Cavanagh, Lucia
2016-01-01
Few studies have sought to understand the concurrent relationship between cognitive and affective processes on alcohol use and negative alcohol-related consequences, despite both being identified as predictive risk factors in the college population. More research is needed to understand the relationships between identified factors of problem drinking among this at-risk population. The purpose of this study was to test if the relationship between psychological distress and problem drinking among university students (N = 284; M-age = 19.77) was mediated by negative affect regulation strategies and positive alcohol-related expectancies. Two latent mediation models of problem drinking were tested using structural equation modeling (SEM). The parsimonious three-path mediated latent model was supported by the data, as evidenced by several model fit indices. Furthermore, the alternate saturated model provided similar fit to the data, but contained several direct relationships that were not statistically significant. The relationship between psychological distress and problem drinking was mediated by an extended contributory chain, including negative affect regulation and positive alcohol-related expectancies. Implications for prevention and treatment, as well as future directions, are discussed. © The Author(s) 2015.
Furnes, Bjarte; Samuelsson, Stefan
2010-01-01
In this study, the relationship between latent constructs of phonological awareness (PA) and rapid automatized naming (RAN) were investigated and related to later measures of reading and spelling in children learning to read in different alphabetic writing systems (i.e., Norwegian/Swedish vs. English). 750 U.S./Australian children and 230 Scandinavian children were followed longitudinally between kindergarten and 2nd grade. PA and RAN were measured in kindergarten and Grade 1, while word recognition, phonological decoding, and spelling were measured in kindergarten, Grade 1, and Grade 2. In general, high stability was observed for the various reading and spelling measures, such that little additional variance was left open for PA and RAN. However, results demonstrated that RAN was more related to reading than spelling across orthographies, with the opposite pattern shown for PA. In addition, tests of measurement invariance show that the factor loadings of each observed indicator on the latent PA factor was the same across U.S./Australia and Scandinavia. Similar findings were obtained for RAN. In general, tests of structural invariance show that models of early literacy development are highly transferable across languages. PMID:21359098
Research-based care on an acute inpatient psychiatric unit.
Bartholomew, David; Collier, Elizabeth
Many studies of research-based practice in nursing highlight factors that impede the development of practice. With the aim of adding to this body of knowledge, a modified grounded theory approach was used in order to understand more about these barriers and how individual nurses utilize research in their practice. A selective sample of five staff nurses from one acute inpatient psychiatric unit took part in semi-structured interviews. Three main themes were identified, each with two sub-themes. These were (a) activities to utilize research with (i) a 'systematic' model and (ii) a 'latent' model of research utilization (b) enhancing research utilization with (i) organizational culture and (ii) individual attitude and knowledge and (c) impeding research utilization with (i) resources (ii) resistance to change. It is suggested that for these nurses research utilization occurs through their individual knowledge, skill and motivation coupled with organizational commitment. Recommendation is made that further investigation of the 'systematic' and 'latent' models should be carried out. Additionally, it is suggested that these research findings might be used to inform future training, further research-based initiatives and to raise managerial awareness of the impeding factors of research utilization.
Measurement Model Specification Error in LISREL Structural Equation Models.
ERIC Educational Resources Information Center
Baldwin, Beatrice; Lomax, Richard
This LISREL study examines the robustness of the maximum likelihood estimates under varying degrees of measurement model misspecification. A true model containing five latent variables (two endogenous and three exogenous) and two indicator variables per latent variable was used. Measurement model misspecification considered included errors of…
Construction of a memory battery for computerized administration, using item response theory.
Ferreira, Aristides I; Almeida, Leandro S; Prieto, Gerardo
2012-10-01
In accordance with Item Response Theory, a computer memory battery with six tests was constructed for use in the Portuguese adult population. A factor analysis was conducted to assess the internal structure of the tests (N = 547 undergraduate students). According to the literature, several confirmatory factor models were evaluated. Results showed better fit of a model with two independent latent variables corresponding to verbal and non-verbal factors, reproducing the initial battery organization. Internal consistency reliability for the six tests were alpha = .72 to .89. IRT analyses (Rasch and partial credit models) yielded good Infit and Outfit measures and high precision for parameter estimation. The potential utility of these memory tasks for psychological research and practice willbe discussed.
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.
Iliceto, Paolo; D'Antuono, Laura; Bowden-Jones, Henrietta; Giovani, Eleni; Giacolini, Teodosio; Candilera, Gabriella; Sabatello, Ugo; Panksepp, Jaak
2016-03-01
The aim of this study was to explore the relations between gambling, brain emotion systems, personality, self/other perception, and hopelessness in an Italian community. Dimensions of gambling, positive and negative emotions, self/other perception, personality and hopelessness were assessed in a community sample of 235 adults aged 19-59 years. Two structural models were tested. We found a significant correlation between problem gambling and impulsivity, which in association with aggressivity and negative personality dimensions may help explain the psychopathology factor, i.e. a latent variable involving neurotic personality, hopelessness, high sensation seeking, low metacognitive responsiveness, and disorganized patterns of interpersonal relationships. These results contribute to develop a theoretical framework of gambling in relation with personality factors and provide a new approach for clinical intervention of problem gambling that relies on a solid multidimensional perspective.
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.
Implicit measurement of the latent heat in a magnetocaloric NiMnIn Heusler alloy
NASA Astrophysics Data System (ADS)
Ghahremani, Mohammadreza; ElBidweihy, Hatem; Bennett, Lawrence H.; Della Torre, Edward; Zou, Min; Johnson, Francis
2013-05-01
The latent heat linked with the first-order transformation of a NiMnIn Heusler alloy has been studied through direct measurements of the adiabatic temperature change, ΔTad, during magnetization process. The experimental procedure used guarantees independent data points and negates any contribution of hysteretic losses to the magnetocaloric effect. Thus, the differences between the magnitudes of ΔTad measurements during the magnetization with the initial temperature change directions from low-to-high and high-to-low are solely attributed to the latent heat exchange, which accompanies the irreversible structural first-order transformation. An estimate of the latent heat inducing such differences is about 0.292 J/g.
Seeto, Mark
2017-01-01
Recent epidemiological data suggest the relation between hearing difficulty and depression is more evident in younger and middle-aged populations than in older adults. There are also suggestions that the relation may be more evident in specific subgroups; that is, other factors may influence a relationship between hearing and depression in different subgroups. Using cross-sectional data from the UK Biobank on 134,357 community-dwelling people and structural equation modelling, this study examined the potential mediating influence of social isolation and unemployment and the confounding influence of physical illness and cardiovascular conditions on the relation between a latent hearing variable and both a latent depressive episodes variable and a latent depressive symptoms variable. The models were stratified by age (40s, 50s, and 60s) and gender and further controlled for physical illness and professional support in associations involving social isolation and unemployment. The latent hearing variable was primarily defined by reported hearing difficulty in noise. For all subgroups, poor hearing was significantly related to both more depressive episodes and more depressive symptoms. In all models, the direct and generally small association exceeded the indirect associations via physical health and social interaction. Significant (depressive episodes) and near significant (depressive symptoms) higher direct associations were estimated for males in their 40s and 50s than for males in their 60s. There was at each age-group no significant difference in estimated associations across gender. Irrespective of the temporal order of variables, findings suggest that audiological services should facilitate psychosocial counselling. PMID:28752806
Keidser, Gitte; Seeto, Mark
2017-01-01
Recent epidemiological data suggest the relation between hearing difficulty and depression is more evident in younger and middle-aged populations than in older adults. There are also suggestions that the relation may be more evident in specific subgroups; that is, other factors may influence a relationship between hearing and depression in different subgroups. Using cross-sectional data from the UK Biobank on 134,357 community-dwelling people and structural equation modelling, this study examined the potential mediating influence of social isolation and unemployment and the confounding influence of physical illness and cardiovascular conditions on the relation between a latent hearing variable and both a latent depressive episodes variable and a latent depressive symptoms variable. The models were stratified by age (40s, 50s, and 60s) and gender and further controlled for physical illness and professional support in associations involving social isolation and unemployment. The latent hearing variable was primarily defined by reported hearing difficulty in noise. For all subgroups, poor hearing was significantly related to both more depressive episodes and more depressive symptoms. In all models, the direct and generally small association exceeded the indirect associations via physical health and social interaction. Significant (depressive episodes) and near significant (depressive symptoms) higher direct associations were estimated for males in their 40s and 50s than for males in their 60s. There was at each age-group no significant difference in estimated associations across gender. Irrespective of the temporal order of variables, findings suggest that audiological services should facilitate psychosocial counselling.
Behavioral Scale Reliability and Measurement Invariance Evaluation Using Latent Variable Modeling
ERIC Educational Resources Information Center
Raykov, Tenko
2004-01-01
A latent variable modeling approach to reliability and measurement invariance evaluation for multiple-component measuring instruments is outlined. An initial discussion deals with the limitations of coefficient alpha, a frequently used index of composite reliability. A widely and readily applicable structural modeling framework is next described…
Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling
ERIC Educational Resources Information Center
Raykov, Tenko; Marcoulides, George A.
2012-01-01
A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…
Diagnostic Procedures for Detecting Nonlinear Relationships between Latent Variables
ERIC Educational Resources Information Center
Bauer, Daniel J.; Baldasaro, Ruth E.; Gottfredson, Nisha C.
2012-01-01
Structural equation models are commonly used to estimate relationships between latent variables. Almost universally, the fitted models specify that these relationships are linear in form. This assumption is rarely checked empirically, largely for lack of appropriate diagnostic techniques. This article presents and evaluates two procedures that can…
Latent Heating from TRMM Satellite Measurements
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Smith, E.; Olson, W.
2005-01-01
Rainfall production is a fundamental process within the Earth;s hydrological cycle because it represents both a principal forcing term in surface water budgets, and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations with the Tropics - as well as modify the energetic efficiencies of mid-latitude weather systems. This paper highlights the retrieval of observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing an accurate four-dimensional amount of rainfall over the global Tropics and sub-tropics - information which can be used to estimate the spacetime structure of latent heating across the Earth's low latitudes. A set of algorithm methodologies has and continues to be developed to estimate latent heating based on rain rate profile retrievals obtained from TRMM measurements. These algorithms are briefly described followed by a discussion of the foremost latent heating products that can be generate from them. The investigation then provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.
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
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.
2002-01-01
NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2001. Rainfall, latent heating and radar reflectivity structures between El Nino (DE 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs. west Pacific, Africa vs. S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in strtaiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model.
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Starr, David (Technical Monitor)
2002-01-01
NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in stratiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model.
NASA Technical Reports Server (NTRS)
Tao, W.-K.
2003-01-01
NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in straitform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMXX), Brazil in 1999 (TRMM- LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model.
Selvi, Yavuz; Boysan, Murat; Kandeger, Ali; Uygur, Omer F; Sayin, Ayca A; Akbaba, Nursel; Koc, Basak
2018-08-01
The current study aimed at investigating the latent dimensional structure of sleep quality as indexed by the seven components of the Pittsburgh Sleep Quality Index (PSQI), as well as latent covariance structure between sleep quality, circadian preferences and depressive symptoms. Two hundred twenty-five patients with major depressive disorder (MDD), with an average age of 29.92 ± 10.49 years (aged between 17 and 63), participated in the study. The PSQI, Morningness-Eveningness Questionnaire (MEQ) and Beck Depression Inventory (BDI) were administered to participants. Four sets of latent class analyses were subsequently run to obtain optimal number of latent classes best fit to the data. Mixture models revealed that sleep quality is multifaceted in MDD. The data best fit to four-latent-class model: Poor Habitual Sleep Quality (PHSQ), Poor Subjective Sleep Quality (PSSQ), Intermediate Sleep Quality (ISQ), and Good Sleep Quality (GSQ). MDD patients classified into GSQ latent class (23.6%) reported the lowest depressive symptoms and were more prone to morningness diurnal preferences compared to other three homogenous sub-groups. Finally, the significant association between eveningness diurnal preferences and depressive symptomatology was significantly mediated by poor sleep quality. The cross-sectional nature of the study and the lack of an objective measurement of sleep such as polysomnography recordings was the most striking limitation of the study. We concluded sleep quality in relation to circadian preferences and depressive symptoms has a heterogeneous nature in MDD. Copyright © 2018. Published by Elsevier B.V.
Latent geometry of bipartite networks
NASA Astrophysics Data System (ADS)
Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri
2017-03-01
Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.
Urbán, Róbert; Szigeti, Réka; Kökönyei, Gyöngyi; Demetrovics, Zsolt
2014-06-01
The Rosenberg Self-Esteem Scale (RSES) is a widely used measure for assessing self-esteem, but its factor structure is debated. Our goals were to compare 10 alternative models for the RSES and to quantify and predict the method effects. This sample involves two waves (N =2,513 9th-grade and 2,370 10th-grade students) from five waves of a school-based longitudinal study. The RSES was administered in each wave. The global self-esteem factor with two latent method factors yielded the best fit to the data. The global factor explained a large amount of the common variance (61% and 46%); however, a relatively large proportion of the common variance was attributed to the negative method factor (34 % and 41%), and a small proportion of the common variance was explained by the positive method factor (5% and 13%). We conceptualized the method effect as a response style and found that being a girl and having a higher number of depressive symptoms were associated with both low self-esteem and negative response style, as measured by the negative method factor. Our study supported the one global self-esteem construct and quantified the method effects in adolescents.
Urbán, Róbert; Szigeti, Réka; Kökönyei, Gyöngyi; Demetrovics, Zsolt
2013-01-01
The Rosenberg Self-Esteem Scale (RSES) is a widely used measure for assessing self-esteem, but its factor structure is debated. Our goals were to compare 10 alternative models for RSES; and to quantify and predict the method effects. This sample involves two waves (N=2513 ninth-grade and 2370 tenth-grade students) from five waves of a school-based longitudinal study. RSES was administered in each wave. The global self-esteem factor with two latent method factors yielded the best fit to the data. The global factor explained large amount of the common variance (61% and 46%); however, a relatively large proportion of the common variance was attributed to the negative method factor (34 % and 41%), and a small proportion of the common variance was explained by the positive method factor (5% and 13%). We conceptualized the method effect as a response style, and found that being a girl and having higher number of depressive symptoms were associated with both low self-esteem and negative response style measured by the negative method factor. Our study supported the one global self-esteem construct and quantified the method effects in adolescents. PMID:24061931
Exploring context and content links in social media: a latent space method.
Qi, Guo-Jun; Aggarwal, Charu; Tian, Qi; Ji, Heng; Huang, Thomas S
2012-05-01
Social media networks contain both content and context-specific information. Most existing methods work with either of the two for the purpose of multimedia mining and retrieval. In reality, both content and context information are rich sources of information for mining, and the full power of mining and processing algorithms can be realized only with the use of a combination of the two. This paper proposes a new algorithm which mines both context and content links in social media networks to discover the underlying latent semantic space. This mapping of the multimedia objects into latent feature vectors enables the use of any off-the-shelf multimedia retrieval algorithms. Compared to the state-of-the-art latent methods in multimedia analysis, this algorithm effectively solves the problem of sparse context links by mining the geometric structure underlying the content links between multimedia objects. Specifically for multimedia annotation, we show that an effective algorithm can be developed to directly construct annotation models by simultaneously leveraging both context and content information based on latent structure between correlated semantic concepts. We conduct experiments on the Flickr data set, which contains user tags linked with images. We illustrate the advantages of our approach over the state-of-the-art multimedia retrieval techniques.
Smith, David; Woodman, Richard; Drummond, Aaron; Battersby, Malcolm
2016-03-30
Knowledge of a problem gambler's underlying gambling related cognitions plays an important role in treatment planning. The Gambling Related Cognitions Scale (GRCS) is therefore frequently used in clinical settings for screening and evaluation of treatment outcomes. However, GRCS validation studies have generated conflicting results regarding its latent structure using traditional confirmatory factor analyses (CFA). This may partly be due to the rigid constraints imposed on cross-factor loadings with traditional CFA. The aim of this investigation was to determine whether a Bayesian structural equation modelling (BSEM) approach to examination of the GRCS factor structure would better replicate substantive theory and also inform model re-specifications. Participants were 454 treatment-seekers at first presentation to a gambling treatment centre between January 2012 and December 2014. Model fit indices were well below acceptable standards for CFA. In contrast, the BSEM model which included small informative priors for the residual covariance matrix in addition to cross-loadings produced excellent model fit for the original hypothesised factor structure. The results also informed re-specification of the CFA model which provided more reasonable model fit. These conclusions have implications that should be useful to both clinicians and researchers evaluating measurement models relating to gambling related cognitions in treatment-seekers. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
The Joint Structure of DSM–IV Axis I and Axis II Disorders
Røysamb, Espen; Tambs, Kristian; Ørstavik, Ragnhild E.; Torgersen, Svenn; Kendler, Kenneth S.; Neale, Michael C.; Aggen, Steven H.; Reichborn-Kjennerud, Ted
2011-01-01
The Diagnostic and Statistical Manual (4th ed. [DSM–IV]; American Psychiatric Association, 1994) distinction between clinical disorders on Axis I and personality disorders on Axis II has become increasingly controversial. Although substantial comorbidity between axes has been demonstrated, the structure of the liability factors underlying these two groups of disorders is poorly understood. The aim of this study was to determine the latent factor structure of a broad set of common Axis I disorders and all Axis II personality disorders and thereby to identify clusters of disorders and account for comorbidity within and between axes. Data were collected in Norway, through a population-based interview study (N = 2,794 young adult twins). Axis I and Axis II disorders were assessed with the Composite International Diagnostic Interview (CIDI) and the Structured Interview for DSM–IV Personality (SIDP–IV), respectively. Exploratory and confirmatory factor analyses were used to investigate the underlying structure of 25 disorders. A four-factor model fit the data well, suggesting a distinction between clinical and personality disorders as well as a distinction between broad groups of internalizing and externalizing disorders. The location of some disorders was not consistent with the DSM–IV classification; antisocial personality disorder belonged primarily to the Axis I externalizing spectrum, dysthymia appeared as a personality disorder, and borderline personality disorder appeared in an interspectral position. The findings have implications for a meta-structure for the DSM. PMID:21319931
Heritabilities of Facial Measurements and Their Latent Factors in Korean Families
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
Retrieved Vertical Profiles of Latent Heat Release Using TRMM Rainfall Products
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Lang, S.; Olson, W. S.; Meneghini, R.; Yang, S.; Simpson, J.; Kummerow, C.; Smith, E.
2000-01-01
This paper represents the first attempt to use TRMM rainfall information to estimate the four dimensional latent heating structure over the global tropics for February 1998. The mean latent heating profiles over six oceanic regions (TOGA COARE IFA, Central Pacific, S. Pacific Convergence Zone, East Pacific, Indian Ocean and Atlantic Ocean) and three continental regions (S. America, Central Africa and Australia) are estimated and studied. The heating profiles obtained from the results of diagnostic budget studies over a broad range of geographic locations are used to provide comparisons and indirect validation for the heating algorithm estimated heating profiles. Three different latent heating algorithms, the Goddard Convective-Stratiform (CSH) heating, the Goddard Profiling (GPROF) heating, and the Hydrometeor heating (HH) are used and their results are intercompared. The horizontal distribution or patterns of latent heat release from the three different heating retrieval methods are quite similar. They all can identify the areas of major convective activity (i.e., a well defined ITCZ in the Pacific, a distinct SPCZ) in the global tropics. The magnitude of their estimated latent heating release is also not in bad agreement with each other and with those determined from diagnostic budget studies. However, the major difference among these three heating retrieval algorithms is the altitude of the maximum heating level. The CSH algorithm estimated heating profiles only show one maximum heating level, and the level varies between convective activity from various geographic locations. These features are in good agreement with diagnostic budget studies. By contrast, two maximum heating levels were found using the GPROF heating and HH algorithms. The latent heating profiles estimated from all three methods can not show cooling between active convective events. We also examined the impact of different TMI (Multi-channel Passive Microwave Sensor) and PR (Precipitation Radar) rainfall information on latent heating structures.
Induction of reactivation of herpes simplex virus in murine sensory ganglia in vivo by cadmium.
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
Guenole, Nigel
2016-01-01
We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis) on conclusions about homology (i.e., equivalent structural relations across levels of analysis) under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs). We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even correctly specified models rules out empirical examination of isomorphism and homology without taking precautions, for instance, larger Level-2 sample sizes, or using informative priors.
Guenole, Nigel
2016-01-01
We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis) on conclusions about homology (i.e., equivalent structural relations across levels of analysis) under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs). We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even correctly specified models rules out empirical examination of isomorphism and homology without taking precautions, for instance, larger Level-2 sample sizes, or using informative priors. PMID:26973580
The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality.
Congdon, Peter
2011-01-01
Analysis of geographical patterns of suicide and psychiatric morbidity has demonstrated the impact of latent ecological variables (such as deprivation, rurality). Such latent variables may be derived by conventional multivariate techniques from sets of observed indices (for example, by principal components), by composite variable methods or by methods which explicitly consider the spatial framework of areas and, in particular, the spatial clustering of latent risks and outcomes. This article considers a latent random variable approach to explaining geographical contrasts in suicide in the US; and it develops a spatial structural equation model incorporating deprivation, social fragmentation and rurality. The approach allows for such latent spatial constructs to be correlated both within and between areas. Potential effects of area ethnic mix are also included. The model is applied to male and female suicide deaths over 2002–06 in 3142 US counties.
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.
Gains in Life Expectancy Associated with Higher Education in Men
Bijwaard, Govert E.; van Poppel, Frans; Ekamper, Peter; Lumey, L. H.
2015-01-01
Background Many studies show large differences in life expectancy across the range of education, intelligence, and socio-economic status. As educational attainment, intelligence, and socio-economic status are highly interrelated, appropriate methods are required to disentangle their separate effects. The aim of this paper is to present a novel method to estimate gains in life expectancy specifically associated with increased education. Our analysis is based on a structural model in which education level, IQ at age 18 and mortality all depend on (latent) intelligence. The model allows for (selective) educational choices based on observed factors and on an unobserved factor capturing intelligence. Our estimates are based on information from health examinations of military conscripts born in 1944–1947 in The Netherlands and their vital status through age 66 (n = 39,798). Results Our empirical results show that men with higher education have lower mortality. Using structural models to account for education choice, the estimated gain in life expectancy for men moving up one educational level ranges from 0.3 to 2 years. The estimated gain in months alive over the observational period ranges from -1.2 to 5.7 months. The selection effect is positive and amounts to a gain of one to two months. Decomposition of the selection effect shows that the gain from selection on (latent) intelligence is larger than the gain from selection on observed factors and amounts to 1.0 to 1.7 additional months alive. Conclusion Our findings confirm the strong selection into education based on socio-economic status and intelligence. They also show significant higher life expectancy among individuals with higher education after the selectivity of education choice has been taken into account. Based on these estimates, it is plausible therefore that increases in education could lead to increases in life expectancy. PMID:26496647
Gains in Life Expectancy Associated with Higher Education in Men.
Bijwaard, Govert E; van Poppel, Frans; Ekamper, Peter; Lumey, L H
2015-01-01
Many studies show large differences in life expectancy across the range of education, intelligence, and socio-economic status. As educational attainment, intelligence, and socio-economic status are highly interrelated, appropriate methods are required to disentangle their separate effects. The aim of this paper is to present a novel method to estimate gains in life expectancy specifically associated with increased education. Our analysis is based on a structural model in which education level, IQ at age 18 and mortality all depend on (latent) intelligence. The model allows for (selective) educational choices based on observed factors and on an unobserved factor capturing intelligence. Our estimates are based on information from health examinations of military conscripts born in 1944-1947 in The Netherlands and their vital status through age 66 (n = 39,798). Our empirical results show that men with higher education have lower mortality. Using structural models to account for education choice, the estimated gain in life expectancy for men moving up one educational level ranges from 0.3 to 2 years. The estimated gain in months alive over the observational period ranges from -1.2 to 5.7 months. The selection effect is positive and amounts to a gain of one to two months. Decomposition of the selection effect shows that the gain from selection on (latent) intelligence is larger than the gain from selection on observed factors and amounts to 1.0 to 1.7 additional months alive. Our findings confirm the strong selection into education based on socio-economic status and intelligence. They also show significant higher life expectancy among individuals with higher education after the selectivity of education choice has been taken into account. Based on these estimates, it is plausible therefore that increases in education could lead to increases in life expectancy.
Hajimiri, Khadijeh; Shakibazadeh, Elham; Mehrizi, Ali Asghar Haeri; Shabbidar, Sakineh
2018-01-01
Background and aim Postpartum is a critical period for mothers which often leads to neglect of their own health. Mothers’ new responsibilities may affect their health promoting lifestyle (HPL). The aim of this study was to determine the impact of both general health and social support on health-promoting lifestyle. Methods A cross-sectional survey was conducted on 310 women who gave birth over a one-year period in Zanjan (Iran), 2016. A proportionate stratified random sampling technique was used to select respondents from each stratum. Health-promoting lifestyle was assessed using the health-promoting lifestyle profile II (HPLP II) scale. A structure equation model (SEM) was used to determine the relationship between observed and latent variables. Data were analysed using SPSS version 22 and LISREL 8.5 software. Results The age of 42.6% of the participants was more than 30 years and 40.3% of them had an academic education. The mean score of the health-promoting lifestyle was 131.28 (15.37). The structural equation model fitted well with RMSEA =0.07, CFI=0.92, and GFI=0.94. Among the latent factors, general health, with a factor load of −0.68, had greater impact on health-promoting lifestyle than social support. Moreover, there was a significant correlation (−0.63) between general health and perceived social support in the postpartum period. Conclusion health-promoting lifestyle was not at appropriate levels among women in the first year after delivery. These findings suggest that strengthening general health and social support would improve a health-promoting lifestyle in Iranian postpartum women. PMID:29588825
Vleeschouwer, Marloes; Schubart, Chris D.; Henquet, Cecile; Myin-Germeys, Inez; van Gastel, Willemijn A.; Hillegers, Manon H. J.; van Os, Jim J.; Boks, Marco P. M.; Derks, Eske M.
2014-01-01
Background The psychometric properties of an online test are not necessarily identical to its paper and pencil original. The aim of this study is to test whether the factor structure of the Community Assessment of Psychic Experiences (CAPE) is measurement invariant with respect to online vs. paper and pencil assessment. Method The factor structure of CAPE items assessed by paper and pencil (N = 796) was compared with the factor structure of CAPE items assessed by the Internet (N = 21,590) using formal tests for Measurement Invariance (MI). The effect size was calculated by estimating the Signed Item Difference in the Sample (SIDS) index and the Signed Test Difference in the Sample (STDS) for a hypothetical subject who scores 2 standard deviations above average on the latent dimensions. Results The more restricted Metric Invariance model showed a significantly worse fit compared to the less restricted Configural Invariance model (χ2(23) = 152.75, p<0.001). However, the SIDS indices appear to be small, with an average of −0.11. A STDS of −4.80 indicates that Internet sample members who score 2 standard deviations above average would be expected to score 4.80 points lower on the CAPE total scale (ranging from 42 to 114 points) than would members of the Paper sample with the same latent trait score. Conclusions Our findings did not support measurement invariance with respect to assessment method. Because of the small effect sizes, the measurement differences between the online assessed CAPE and its paper and pencil original can be neglected without major consequences for research purposes. However, a person with a high vulnerability for psychotic symptoms would score 4.80 points lower on the total scale if the CAPE is assessed online compared to paper and pencil assessment. Therefore, for clinical purposes, one should be cautious with online assessment of the CAPE. PMID:24465389
Using structural equation modeling for network meta-analysis.
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.
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…
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…
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.