Relevant bibliographies by topics / Network psychometric

Academic literature on the topic 'Network psychometric'

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Published: 10 March 2023

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Journal articles on the topic "Network psychometric"

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Kan, Kees-Jan, Hannelies de Jonge, Han L. J. van der Maas, Stephen Z. Levine, and Sacha Epskamp. "How to Compare Psychometric Factor and Network Models." Journal of Intelligence 8, no. 4 (October 2, 2020): 35. http://dx.doi.org/10.3390/jintelligence8040035.

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In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to write, shortly before his death. We first discuss the statistical procedure McFarland used, which involved structural equation modeling (SEM) in standard SEM software. Next, we evaluate the penta-factor model of intelligence. We conclude that (1) standard SEM software is not suitable for the comparison of psychometric networks with latent variable models, and (2) the penta-factor model of intelligence is only of limited value, as it is nonidentified. We conclude with a reanalysis of the Wechlser Adult Intelligence Scale data McFarland discussed and illustrate how network and latent variable models can be compared using the recently developed R package Psychonetrics. Of substantive theoretical interest, the results support a network interpretation of general intelligence. A novel empirical finding is that networks of intelligence replicate over standardization samples.
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McNally, Richard J. "Points of contact between network psychometrics and experimental psychopathology." Journal of Experimental Psychopathology 14, no. 1 (January 2023): 204380872311515. http://dx.doi.org/10.1177/20438087231151505.

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Experimental psychology has long embodied the quest to identify the causes of psychopathology. This venerable tradition has been joined in this quest by network theory, a novel approach to conceptualizing episodes of disorder as emerging from complex systems characterized by dynamic interactions of symptoms. Although issuing from the correlational, psychometric tradition rather than the experimental one, it nevertheless offers methods for identifying symptom targets for clinical experimental intervention. The purpose of this article is to sketch the points of contact between network psychometrics and experimental psychopathology.
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Christensen, Alexander P., Hudson Golino, and Paul J. Silvia. "A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires." European Journal of Personality 34, no. 6 (December 2020): 1095–108. http://dx.doi.org/10.1002/per.2265.

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This article reviews the causal implications of latent variable and psychometric network models for the validation of personality trait questionnaires. These models imply different data generating mechanisms that have important consequences for the validity and validation of questionnaires. From this review, we formalize a framework for assessing the evidence for the validity of questionnaires from the psychometric network perspective. We focus specifically on the structural phase of validation, where items are assessed for redundancy, dimensionality, and internal structure. In this discussion, we underline the importance of identifying unique personality components (i.e. an item or set of items that share a unique common cause) and representing the breadth of each trait's domain in personality networks. After, we argue that psychometric network models have measures that are statistically equivalent to factor models but we suggest that their substantive interpretations differ. Finally, we provide a novel measure of structural consistency, which provides complementary information to internal consistency measures. We close with future directions for how external validation can be executed using psychometric network models. © 2020 European Association of Personality Psychology
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Schmank, Christopher J., Sara Anne Goring, Kristof Kovacs, and Andrew R. A. Conway. "Psychometric Network Analysis of the Hungarian WAIS." Journal of Intelligence 7, no. 3 (September 9, 2019): 21. http://dx.doi.org/10.3390/jintelligence7030021.

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The positive manifold—the finding that cognitive ability measures demonstrate positive correlations with one another—has led to models of intelligence that include a general cognitive ability or general intelligence (g). This view has been reinforced using factor analysis and reflective, higher-order latent variable models. However, a new theory of intelligence, Process Overlap Theory (POT), posits that g is not a psychological attribute but an index of cognitive abilities that results from an interconnected network of cognitive processes. These competing theories of intelligence are compared using two different statistical modeling techniques: (a) latent variable modeling and (b) psychometric network analysis. Network models display partial correlations between pairs of observed variables that demonstrate direct relationships among observations. Secondary data analysis was conducted using the Hungarian Wechsler Adult Intelligence Scale Fourth Edition (H-WAIS-IV). The underlying structure of the H-WAIS-IV was first assessed using confirmatory factor analysis assuming a reflective, higher-order model and then reanalyzed using psychometric network analysis. The compatibility (or lack thereof) of these theoretical accounts of intelligence with the data are discussed.
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Yordanova, Juliana, Vasil Kolev, Roumen Kirov, and Aribert Rothenberger. "Comorbidity in the context of neural network properties." Behavioral and Brain Sciences 33, no. 2-3 (June 2010): 176–77. http://dx.doi.org/10.1017/s0140525x1000083x.

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AbstractCramer et al.'s network approach reconceptualizes mental comorbidity on the basis of symptom space originating from psychometric signatures. We argue that the advantages of this approach need to be regarded in the context of the multi-level functional organization of the neural substrate, ranging from neurogenetic to psychometric. Neuroelectric oscillations are proposed as a level-integrating principle.
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Punzi, Clara, Manuela Petti, and Paolo Tieri. "Network-based methods for psychometric data of eating disorders: A systematic review." PLOS ONE 17, no. 10 (October 31, 2022): e0276341. http://dx.doi.org/10.1371/journal.pone.0276341.

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Background Network science represents a powerful and increasingly promising method for studying complex real-world problems. In the last decade, it has been applied to psychometric data in the attempt to explain psychopathologies as complex systems of causally interconnected symptoms. One category of mental disorders, relevant for their severity, incidence and multifaceted structure, is that of eating disorders (EDs), serious disturbances that negatively affect a person’s eating behavior. Aims We aimed to review the corpus of psychometric network analysis methods by scrutinizing a large sample of network-based studies that exploit psychometric data related to EDs. A particular focus is given to the description of the methodologies for network estimation, network description and network stability analysis providing also a review of the statistical software packages currently used to carry out each phase of the network estimation and analysis workflow. Moreover, we try to highlight aspects with potential clinical impact such as core symptoms, influences of external factors, comorbidities, and related changes in network structure and connectivity across both time and subpopulations. Methods A systematic search was conducted (February 2022) on three different literature databases to identify 57 relevant research articles. The exclusion criteria comprehended studies not based on psychometric data, studies not using network analysis, studies with different aims or not focused on ED, and review articles. Results Almost all the selected 57 papers employed the same analytical procedures implemented in a collection of R packages specifically designed for psychometric network analysis and are mostly based on cross-sectional data retrieved from structured psychometric questionnaires, with just few exemptions of panel data. Most of them used the same techniques for all phases of their analysis. In particular, a pervasive use of the Gaussian Graphical Model with LASSO regularization was registered for in network estimation step. Among the clinically relevant results, we can include the fact that all papers found strong symptom interconnections between specific and nonspecific ED symptoms, suggesting that both types should therefore be addressed by clinical treatment. Conclusions We here presented the largest and most comprehensive review to date about psychometric network analysis methods. Although these methods still need solid validation in the clinical setting, they have already been able to show many strengths and important results, as well as great potentials and perspectives, which have been analyzed here to provide suggestions on their use and their possible improvement.
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Steinley, Douglas, and Michael J. Brusco. "On Fixed Marginal Distributions and Psychometric Network Models." Multivariate Behavioral Research 56, no. 2 (March 4, 2021): 329–35. http://dx.doi.org/10.1080/00273171.2021.1895706.

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Lange, Jens, Jonas Dalege, Denny Borsboom, Gerben A. van Kleef, and Agneta H. Fischer. "Toward an Integrative Psychometric Model of Emotions." Perspectives on Psychological Science 15, no. 2 (February 10, 2020): 444–68. http://dx.doi.org/10.1177/1745691619895057.

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Emotions are part and parcel of the human condition, but their nature is debated. Three broad classes of theories about the nature of emotions can be distinguished: affect-program theories, constructionist theories, and appraisal theories. Integrating these broad classes of theories into a unifying theory is challenging. An integrative psychometric model of emotions can inform such a theory because psychometric models are intertwined with theoretical perspectives about constructs. To identify an integrative psychometric model, we delineate properties of emotions stated by emotion theories and investigate whether psychometric models account for these properties. Specifically, an integrative psychometric model of emotions should allow (a) identifying distinct emotions (central in affect-program theories), (b) between- and within-person variations of emotions (central in constructionist theories), and (c) causal relationships between emotion components (central in appraisal theories). Evidence suggests that the popular reflective and formative latent variable models—in which emotions are conceptualized as unobservable causes or consequences of emotion components—cannot account for all properties. Conversely, a psychometric network model—in which emotions are conceptualized as systems of causally interacting emotion components—accounts for all properties. The psychometric network model thus constitutes an integrative psychometric model of emotions, facilitating progress toward a unifying theory.
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Epskamp, Sacha. "Psychometric network models from time-series and panel data." Psychometrika 85, no. 1 (March 2020): 206–31. http://dx.doi.org/10.1007/s11336-020-09697-3.

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Christensen, Alexander P., Yoed N. Kenett, Tomaso Aste, Paul J. Silvia, and Thomas R. Kwapil. "Network structure of the Wisconsin Schizotypy Scales–Short Forms: Examining psychometric network filtering approaches." Behavior Research Methods 50, no. 6 (March 8, 2018): 2531–50. http://dx.doi.org/10.3758/s13428-018-1032-9.

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Dissertations / Theses on the topic "Network psychometric"

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Zimmerman, Tekeisha. "Testing the Psychometric Properties of the Online Student Connectedness Survey." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804927/.

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The Online Student Connectedness Survey (OSCS) was introduced to the academic community in 2012 as an instrument designed to measure feelings of connectedness between students participating in online degree and certification programs. The purpose of this study was to examine data from the instrument for initial evidence of validity and reliability and to establish a nomological network between the OSCS and similar instruments utilized in the field. The study utilized sequential exploratory factor analysis- confirmatory factor analysis (EFA-CFA) and correlational analysis to assess results of the data. Students enrolled in online courses at higher education institutions located in the United States served as the sample for this study. Three instruments were used during the study. The OSCS was administered first so that the factor structure could be examined for factor validity. Once confirmed, the Classroom Community Scale (CCS) and the Community of Inquiry Scale (COI) served as the instruments to examine nomological validity through correlational analysis of data.This study provided evidence of factor validity and reliability for data from the OSCS. After the initial EFA-CFA, the four-factor structure held, and 16 of the 25 original items remained for nomological testing. Statistically significant correlations were demonstrated between factors contained in the OSCS, CCS, and COI, providing further evidence of construct validity. These results indicate that for the sample used in this study, the OSCS provides data that are valid and reliable for assessing feelings of connection between participants in online courses at institutions of higher learning.
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Grasset, Raphaël. "Apprenance et équipes de travail : mise à l’épreuve d’une évaluation individuelle du rapport à l’apprendre dans les interactions des collectifs." Thesis, Paris 10, 2019. http://www.theses.fr/2019PA100029.

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Alors que les sujets sociaux sont poussés à porter seuls la responsabilité de la mise à jour de leurs connaissances et compétences, la création de valeur qui passe de plus en plus dans les entreprises par un travail collectif leur demande aussi d’apprendre à travailler et apprendre ensemble. Une étude exploratoire sur la possibilité d’apprendre en équipe rapporte la complexité de ce couplage entre l’individuel et le collectif. De ce contexte émerge la problématique de la relation entre les différences interindividuelles de rapport à l’apprendre et les interactions au sein des collectifs de travail.Nous proposons d’aborder ces différences interindividuelles au travers de la notion d’apprenance. Une étude de validation en confirme la structure triadique, sa stabilité, sa valence et son objet tout en fournissant une échelle psychométrique permettant une évaluation située, stable et normée du concept. Cette recherche permet également d’appréhender les particularités de ces sujets au travers de leurs caractéristiques sociodémographiques, de la structuration de leurs connaissances et de leur sentiment d’efficacité professionnelle. Suite à une revue de littérature sur les processus collectifs d’apprentissage au travail, nous proposons d’utiliser le concept de système de mémoire transactive qui soutient les apprentissages entre les membres d’un groupe par des interactions communicationnelles. Une étude qui l’appréhende sous la forme de réseaux en permet une analyse relationnelle à la lumière de l’apprenance. Il en ressort que celle-ci offre un potentiel d’expertise à l’individu au travers d’une optimisation de ses stratégies sociales et un potentiel d’innovation à l’entreprise au travers de l’émergence de ponts informationnels compressant l’espace organisationnel
Although individuals are encouraged to be solely responsible for updating their knowledge and skills, the creation of value in companies emerges more and more through collective work that require them to learn to work and learn together. An exploratory study on the possibility of learning within teams reveals the complexity of the coupling between the individual and the collective. From this context emerges the problem of the link between interindividual differences in relation to learning and the interactions within working collectives.We suggest addressing these interindividual differences through the notion of learning readiness (“apprenance” in French). Our validation study confirms the triadic structure of learning readiness, its stability, its valence and its object while providing a psychometric scale allowing a situated, stable and standardized evaluation of the concept. This research also makes it possible to understand the peculiarities of learning individuals through their socio-demographic characteristics, the structuring of their knowledge and their sense of professional efficiency.Following an extensive literature review on collective learning processes in the workplace, we suggest using the notion of transactive memory system that supports learning between group members through communication interactions. A study that examines it in the form of networks allows for a relational analysis in the light of learning readiness. It appears that learning readiness offers to the individual a potential for expertise through an optimization of its social strategies and to the company a potential for innovation through the emergence of information bridges compressing the organizational space
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Idani, Arman. "Assessment of individual differences in online social networks using machine learning." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/270109.

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The services that define our personal and professional lives are increasingly accessed through digital devices, which store extensive records of our behaviour. An individual's psychological profile can be accurately assessed using offline behaviour, and I investigate if an automated machine learning system can measure the same psychological factors, only from observing the footprints of online behaviour, without observing any offline behaviour or any direct input from the individual. Prior research shows that psychological traits such as personality can be predicted using these digital footprints, although current state-of-the-art accuracy is below psychometric standards of reliability and self-reports consistently outperform machine-ratings in external validity. I introduce a new machine learning system that is capable of doing five-factor personality assessments, as well as other psychological assessments, from online data as accurately as self-report questionnaires in terms of reliability, internal consistency and external and discriminant validity, and demonstrate that passive psychological assessment can be a realistic option in addition to self-report questionnaires for both research and practice. Achieving this goal is not possible using conventional dimensionality reduction and linear regression models. Here I develop a supervised dimensionality reduction method capable of intelligently selecting only useful parts of data for the relevant prediction at hand which also does not lose variance when eliminating redundancies. In the learning stage, instead of linear regression models, I use an ensemble of decision trees which are able to distinguish scenarios where the same observations on digital data can mean different things for different individuals. This work highlights the interesting idea that similar to how a human expert who is able to assess personality from offline behaviour, an expert machine learning system is able to assess personality from online behaviour. It also demonstrates that big-5 personality are predictors of how predictable users are in social media, with neuroticism having the greatest correlation with unpredictability, while openness having the greatest correlation with predictability.
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Joshi, Aditi A. "Effects of meditation training on attentional networks : a randomized controlled trial examining psychometric and electrophysiological (EEG) measures /." Connect to title online (ProQuest), 2007. http://proquest.umi.com/pqdweb?did=1453198271&sid=1&Fmt=2&clientId=11238&RQT=309&VName=PQD.

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Thesis (Ph. D.)--University of Oregon, 2007.
Typescript. Includes vita and abstract. Includes bibliographical references (leaves 126-133). Also available for download via the World Wide Web; free to University of Oregon users.
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Joshi, Aditi A. "Effects of meditation training on attentional networks: A randomized controlled trial examining psychometric and electro-physiological (EEG) measures." Thesis, University of Oregon, 2007. http://hdl.handle.net/1794/8452.

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x, 133 p. ; ill. (some col.) A print copy of this title is available through the UO Libraries under the call number: SCIENCE QP405 .J67 2007
Meditation has been defined as a "group of practices that self-regulate the body and mind, thereby affecting mental events by engaging a specific attentional set" (Cahn & Polich, 2006). We conducted a randomized, longitudinal trial to examine the effects of concentrative meditation training (40 min/day, 5 days/week for 8 weeks) on top-down, voluntary control of attention with a progressive muscle relaxation training group as a control. To determine if training produced changes in attentional network efficiency we compared, pre- and post-training, mean validity effect scores (difference between invalid cue and center cue reaction time) in the contingent capture paradigm (Folk et al., 1992). The meditation group showed a trend towards improvement of top-down attention while the relaxation group did not. Using EEG we assessed the changes in amplitudes of wavelets during periods of mind-wandering and meditation. Periods in which subjects were on- vs. off-focus during the meditation task were identified by asking subjects to make button presses whenever the mind wandered and also at probe tones, if they were off-focus. After training, the episodes of mind-wandering were significantly lower in the meditation group as compared to the relaxation group. Increased amplitudes of alpha and theta EEG frequencies in the occipital and right parietal areas were seen during the meditation task for the meditation but not the relaxation group as an effect of training. A baseline EEG trait effect of reduced mental activity was seen (meditation training: occipital and right parietal areas; relaxation training: only occipital areas). Within a given meditation session, prior to training, alpha and theta activity was lower in on-focus conditions (occurring immediately after subjects discovered they were off-focus and returned to active focus on the breath/syllable) compared to meditative focus segments. After training, we found higher alpha amplitude in periods of meditative focus as compared to periods of mind wandering for both groups. However, the meditation group showed significantly higher theta amplitude than the relaxation group during the meditative state segments.
Adviser: Marjorie Woollacott
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Schallock, Jessica Marie. "The central role of stress relief in video gaming motivations and preferences." Thesis, University of Cambridge, 2019. https://www.repository.cam.ac.uk/handle/1810/288483.

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Video games are played by more than 1.8 billion people and are a pervasive force in society, but despite decades of research there has been little consensus on their effects. Before we are able to model complex outcomes such as excessive engagement, we must first understand how and why people play video games. This dissertation integrates latent factor models with techniques from machine learning and network analysis to develop a holistic picture of gaming style, motivations, and individual differences. It employs diverse sources of data across several studies and a total of 2,143 participants, combining online questionnaires with qualitative analysis of participant responses and objective information about gaming behaviour from the API of the popular gaming network "Steam", and finds that stress relief is a primary motivation for engaging in the immersive worlds of video games. Previous research has indicated three underlying factors of Immersion, Achievement and Socialising which replicated across three comprehensive studies of 480 adults, 106 adults and children with an Autism Spectrum Condition, and 961 adults and adolescents. Gamers experiencing more stress in their daily lives were more likely to have Immersion rather than Social or Achievement play styles. Achievement-oriented gamers tended to be lower in stress, higher in conscientiousness and emotional stability, and played more than Immersion-focused gamers. A qualitative analysis of 54 gamers' descriptions of why they recently chose to play a game was used to develop the "Reasons for Playing Video Games" items (RPVG), which were administered to independent samples of 243, 299 and 961 gamers. The qgraph R package was used to perform network analyses of the RPVG items and gameplay style factors, employing the machine learning-based adaptive LASSO technique to estimate a partial correlation matrix from a set of variables as a Pairwise Markov Random Field. Gamers higher in Immersion tended to play for escapism, distraction, and fantasy, while social gamers played for excitement, energy, and self-expression. Network analysis and graph theory illustrate the central role of stress relief in the network of Reasons for Playing Video Games and shows that playing when feeling stressed is strongly linked with Immersion.
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ZAMBELLI, MICHELA. "INVESTIGATING DYNAMICS OF CHANGE OF PSYCHOLOGICAL PROCESSES WITHIN A COMPLEXITY FRAMEWORK: APPLICATION TO THE MEANING-MAKING PROCESS." Doctoral thesis, Università Cattolica del Sacro Cuore, 2023. http://hdl.handle.net/10280/134702.

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La tesi di dottorato si propone di aprire una riflessione su come misurare le dinamiche di cambiamento dei processi psicologici in ottica di complessità, presentando un’applicazione al processo di creazione di significato (meaning-making). Dopo la formulazione di una nuova definizione concettuale integrata del processo di meaning-making a seguito di una revisione sistematica (primo capitolo), si è sviluppata una nuova misura self-report del significato della vita (SMILE; situational meaning in life evaluation), validata in un campione rappresentativo nazionale e in un campione di giovani adulti emergenti (secondo capitolo). Il terzo capitolo ha visto la conduzione di due studi con l’utilizzo rispettivamente dei modelli dinamici di equazioni strutturali (DSEM) e l’approccio della Network Psychometric Analysis per indagare le dinamiche di cambiamento del processo di meaning-making nella vita quotidiana di giovani adulti che, durante la pandemia di Covid-19, hanno partecipato a due raccolte giornaliere (measurement burst design). In questi studi è stato indagato il ruolo di fattori individuali (condizione transitiva in amore e lavoro), situazionali (eventi positivi e negativi) e contestuali (pandemia) come attivatori del processo di meaning-making. Le evidenze raccolte mostrano come sia importante indagare i processi psicologici tenendo conto sia del cambiamento intra-soggetto nel tempo, sia delle differenze tra gli individui.
This doctoral thesis aims to open a reflection on how to measure dynamics of change of psychological processes by presenting an application of the complexity framework to the meaning-making process. The first chapter fronts the challenge of how to conceptualize the meaning-making process, by conducting a systematic review of the literature that led toward the formulation of a new integrated conceptual definition of meaning-making. The second chapter presents the development of a new self-report measure of meaning in life (SMILE; situational meaning in life evaluation) that has been validated in a national representative sample and in a sample of emerging and young adults. The third chapter deals with the challenge of how to investigate the dynamics of change of the meaning-making process in the daily life by applying two state-of-the-art data analysis approaches, the Dynamic Structural Equation Models (DSEM) and the Multilevel Network Psychometric approach. Data from emerging and young adults were collected with a measurement burst design made of two daily diary studies during the COVID-19 pandemic. The role of individual factors (transitive condition in love and work), situational factors (positive vs negative events), and contextual factors (pandemic) as activators of the meaning-making process has also been investigated.
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Pardos, Zachary Alexander. "Predictive Models of Student Learning." Digital WPI, 2012. https://digitalcommons.wpi.edu/etd-dissertations/185.

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In this dissertation, several approaches I have taken to build upon the student learning model are described. There are two focuses of this dissertation. The first focus is on improving the accuracy with which future student knowledge and performance can be predicted by individualizing the model to each student. The second focus is to predict how different educational content and tutorial strategies will influence student learning. The two focuses are complimentary but are approached from slightly different directions. I have found that Bayesian Networks, based on belief propagation, are strong at achieving the goals of both focuses. In prediction, they excel at capturing the temporal nature of data produced where student knowledge is changing over time. This concept of state change over time is very difficult to capture with classical machine learning approaches. Interpretability is also hard to come by with classical machine learning approaches; however, it is one of the strengths of Bayesian models and aids in studying the direct influence of various factors on learning. The domain in which these models are being studied is the domain of computer tutoring systems, software which uses artificial intelligence to enhance computer based tutorial instruction. These systems are growing in relevance. At their best they have been shown to achieve the same educational gain as one on one human interaction. Computer tutors have also received the attention of White House, which mentioned an tutoring platform called ASSISTments in its National Educational Technology Plan. With the fast paced adoption of these data driven systems it is important to learn how to improve the educational effectiveness of these systems by making sense of the data that is being generated from them. The studies in this proposal use data from these educational systems which primarily teach topics of Geometry and Algebra but can be applied to any domain with clearly defined sub-skills and dichotomous student response data. One of the intended impacts of this work is for these knowledge modeling contributions to facilitate the move towards computer adaptive learning in much the same way that Item Response Theory models facilitated the move towards computer adaptive testing.
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Neves, Aline da Silva Boschi Martins. "Evid?ncias de Validade da PSS-10 e PSS- 14: Estudo com An?lise Fatorial e de Rede." Pontif?cia Universidade Cat?lica de Campinas, 2018. http://tede.bibliotecadigital.puc-campinas.edu.br:8080/jspui/handle/tede/1093.

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Submitted by SBI Biblioteca Digital (sbi.bibliotecadigital@puc-campinas.edu.br) on 2018-05-04T18:39:57Z No. of bitstreams: 1 ALINE DA SILVA BOSCHI MARTINS NEVES.pdf: 1713644 bytes, checksum: f8d45029bc62915e3c5e77690c011494 (MD5)
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Stress is one of the constructs emphasized when evaluating the health-disease process. However, because it is a latent variable, specific instruments are needed to measure it. The Perceived Stress Scale (PSS) is an instrument that has been used to assess the perception of stress in the last month. Despite numerous validations in several countries, their psychometric properties have not been consensual. The main objective of this work was to investigate the internal structure of the PSS-10 and PSS-14 versions, through exploratory factorial (AFE) and network analysis. Thus, two studies were carried out: in Study I, PSS-10 and PSS-14 were analyzed through AFE and, in study II, the scales were analyzed through network analysis. We used: a) the PSS-10 with a sample composed of 686 participants, being 175 (27.3%) men and 466 (72.7%) women (n = 641), with a mean age of 33.9 SD = 11.3) years, ranging from 18 to 73 (n = 632); and (b) the PSS-14 was answered by 690 participants, of which 304 (44.1%) were men and 386 (55.9.7%) were women, with a mean age of 34.72 (SD = 12, 56), with a range of 18 to 65. In both analyzes, the psychometric properties of PSS-10 and PSS-14 were shown to be reliable and confirmed the two-dimensional structure of distress and coping. Also, the network analysis allowed to explore the PSS in the Brazilian context, allowing new association patterns to emerge from the analyzed samples. And, even AFE being a widely used technique in the construction and evaluation of psychometric tests, network analysis has shown to be a promising and much more comprehensive tool at the level of the symptom, accommodating the numerous processes of psychological constructions. In this study, the network analysis showed how the perception of control influences the outcome of stress. Thus, in addition to providing evidence of validity of the PSS-10 and PSS-14, this study demonstrated how much the network analysis has to contribute in the psychology and health area.
O estresse ? um dos construtos enfatizados quando se avalia o processo sa?de- doen?a. No entanto, por ser uma vari?vel latente, instrumentos espec?ficos s?o necess?rios para mensur?-lo. A Escala de Estresse Percebido (Perceived Stress Scale - PSS) ? um instrumento que tem sido utilizado para avaliar a percep??o do estresse no ?ltimo m?s. Apesar de in?meras valida??es em diversos pa?ses, suas propriedades psicom?tricas n?o t?m sido consensuais. O objetivo principal deste trabalho foi investigar a estrutura interna das vers?es PSS-10 e PSS-14, por meio de an?lise fatorial explorat?ria (AFE) e de rede. Assim, dois estudos foram realizados: no Estudo I, a PSS-10 e a PSS-14 foram analisadas atrav?s da AFE e, no estudo II, analisaram-se as escalas por meio da an?lise de rede. Foram utilizadas: a) a PSS-10 com uma amostra composta por 686 participantes, sendo 175 (27,3%) homens e 466 (72,7%) mulheres (n = 641), com m?dia de idade de 33,9 (SD = 11,3) anos, com amplitude de 18 a 73 (n = 632); e b) a PSS-14 que foi respondida por 690 participantes, dos quais 304 (44,1%) s?o homens e 386 (55,9,7%), mulheres, com m?dia de idade de 34,72 (SD = 12,56) anos, com amplitude de 18 a 65. Nas duas an?lises, as propriedades psicom?tricas da PSS-10 e PSS-14 demonstraram-se confi?veis e confirmaram a estrutura bidimensional de distress e coping. Ainda, a an?lise de rede permitiu explorar a PSS no contexto brasileiro, permitindo que novos padr?es de associa??o emergissem das amostras analisadas. E, mesmo a AFE sendo t?cnica muito utilizada na constru??o e avalia??o de testes psicom?tricos, a an?lise de rede demonstra ser uma ferramenta promissora e muito mais abrangente no n?vel do sintoma, acomodando os numerosos processos das constru??es psicol?gicas. Neste estudo, a an?lise de rede evidenciou o quanto a percep??o de controle influencia no desfecho do estresse. Assim, al?m de fornecer evid?ncias de validade da PSS-10 e PSS-14, este estudo demonstrou o quanto ? an?lise de rede tem a contribuir no ?mbito da psicologia e na ?rea da sa?de.
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Dias, Sofia Alexandra Fontoura. "Study of the Glasgow Sleep Effort Scale (GSES) psychometric properties through CTT, IRT and network analysis." Master's thesis, 2021. http://hdl.handle.net/10773/32886.

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The Glasgow Sleep Effort Scale (GSES) was developed with the aim of measuring sleep effort. The present study evaluates the psychometric properties of the European Portuguese version of the GSES through Classical Test Theory (CTT), Item Response Theory (IRT), and Network Analysis (NA). It was used an existing database comprising a community sample of 227 Portuguese adults, aged 20–74 (M = 42.99; SD = 12.44) years old, encopassing 49.8% men and 50.2% women. In CFA, a well-adjusted to data one-factor model was identified, with sleep effort as the single factor. IRT analysis indicated an adequate performance of all items and satisfactory coverage of the latent trait, with items 3 (a = 3.37), 4 (a = 3 .18), and 6 (a = 3.02) as the most discriminative ones. Considering NA, items 4 and 7 presented the strongest edge weight (.48). Item 1 was displayed at the centre of the networks and accounted for the largest number of connections with the remaining items. The results suggest that the GSES is a reliable measure, comprising highly discriminative items with good centrality indices. Moreover, the measure is particularly important in the evaluation of individuals with moderate to severe levels of sleep effort. We underline the application of more contemporary psychometric techniques (IRT and NA) beyond CTT in the emergent sophistication of measures with the integration of approaches. Specifically, this study builds upon the evidence regarding the development of shorter, yet reliable and valid measures in the sleep medicine area to face the overloading of patients with extensive research protocols and clinical evaluations.
A Glasgow Sleep Effort Scale (GSES) foi desenvolvida com o objetivo de medir o esforço para dormir. O presente estudo visa avaliar as propriedades psicométricas da sua versão em Português Europeu através da Teoria Clássica dos Testes (TCT), Análise da Teoria da Resposta ao Item (TRI) e Análise de Redes (AR). Para tal, foi usada uma base de dados existente, composta por uma amostra comunitária de 227 adultos Portugueses, com idades entre os 20 e os 74 (M = 42.99; DP = 12.44) anos, compreendendo 49.8% homens e 50.2% mulheres. Na AFC, um modelo de um fator bem ajustado aos dados foi identificado, com o esforço para dormir como o único fator. A análise TRI indicou um desempenho adequado de todos os itens com uma cobertura satisfatória do traço latente, em que os itens item 3 (a = 3.37), 4 (a = 3.18) e 6 (a = 3.02) foram os mais discriminativos. Tendo em conta a AR, os itens 4 e 7 apresentaram a maior edge weight (.48) em 21 correlações positivas. O item 1 foi posicionado no centro da rede e contou com o maior número de conexões com os restantes itens. Os resultados sugerem que a GSES é um exemplo de uma medida fidedigna, com itens muito discriminativos e com bons índices de centralidade. Além disso, a medida é particularmente importante na avaliação de indivíduos com níveis moderados a severos de esforço para dormir. Sublinha-se, assim, a aplicação de técnicas psicométricas mais contemporâneas (TRI e AR) para além da TCT na sofisticação emergente de medidas com a integração destas abordagens. Especificamente, este estudo contribui para a evidência no desenvolvimento de medidas mais curtas, fidedignas e válidas para colmatar a sobrecarga dos pacientes com protocolos de pesquisa e avaliações clínicas extensivas.
Mestrado em Psicologia da Saúde e Reabilitação Neuropsicológica
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Books on the topic "Network psychometric"

1

Isvoranu, Adela-Maria, Sacha Epskamp, Lourens J. Waldorp, and Denny Borsboom. Network Psychometrics with R. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003111238.

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L, Commons Michael, and Symposium on Quantitative Analyses of Behavior., eds. Behavioral approaches to pattern recognition and concept formation. Hillsdale, NJ: Erlbaum Associates, 1990.

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L, Commons Michael, and Symposium on Quantitative Analyses of Behavior. (8th : 1985 : Harvard University), eds. Computational and clinical approaches to pattern recognition and concept formation. Hillsdale, N.J: Lawrence Erlbaum Associates, 1990.

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Borsboom, Denny. Mental disorders, network models, and dynamical systems. Edited by Kenneth S. Kendler and Josef Parnas. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198796022.003.0011.

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Network approaches have been proposed as an alternative way of thinking about relations between symptoms of mental disorders. Unlike traditional psychometric approaches, network models view these associations as the result of direct interactions between symptoms. Disorders are defined as alternative stable states of a network due to increased connectivity between symptoms. This increased connectivity creates a pattern of reinforcement, so the system can get stuck in a state of prolonged activation. Mental health is defined as the stable state of a weakly connected network. Although symptomatology may be temporarily increased in a healthy network (e.g., due to adverse life events), as the influence of a shock wanes the network will spontaneously return to its healthy state. Strongly connected networks, however, may transition into disordered states upon similar external shocks, and may not naturally recover. Thus, the proposed definitions yield plausible conceptualizations of resilience and vulnerability.
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Network Psychometrics with R. Taylor & Francis Group, 2022.

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Network Psychometrics with R. Taylor & Francis Group, 2022.

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Borsboom, Denny, Adela-Maria Isvoranu, Sacha Epskamp, and Lourens Waldorp. Network Psychometrics with R: A Guide for Behavioral and Social Scientists. Taylor & Francis Group, 2022.

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Borsboom, Denny, Adela-Maria Isvoranu, Sacha Epskamp, and Lourens Waldorp. Network Psychometrics with R: A Guide for Behavioral and Social Scientists. Taylor & Francis Group, 2022.

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Borsboom, Denny, Adela-Maria Isvoranu, Sacha Epskamp, and Lourens Waldorp. Network Psychometrics with R: A Guide for Behavioral and Social Scientists. Taylor & Francis Group, 2022.

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Farvolden, Judith Margaret. A PRIMAL PARTITIONING SOLUTION FOR MULTICOMMODITY NETWORK FLOW PROBLEMS. 1989.

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Book chapters on the topic "Network psychometric"

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Epskamp, Sacha, Gunter Maris, Lourens J. Waldorp, and Denny Borsboom. "Network Psychometrics." In The Wiley Handbook of Psychometric Testing, 953–86. Chichester, UK: John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781118489772.ch30.

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Sapkal, D. D., Chintan Mehta, Mohit Nimgaonkar, Rohan Devasthale, and Shreyas Phansalkar. "Prediction of Mental Disorder Using Artificial Neural Network and Psychometric Analysis." In Data Management, Analytics and Innovation, 369–77. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5619-7_26.

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Borsboom, Denny, Angélique O. J. Cramer, Eiko I. Fried, Adela-Maria Isvoranu, Donald J. Robinaugh, Jonas Dalege, and Han L. J. van der Maas. "Network Perspectives." In Network Psychometrics with R, 9–27. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003111238-2.

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Deserno, Marie K., Adela-Maria Isvoranu, Sacha Epskamp, and Tessa F. Blanken. "Descriptive Analysis of Network Structures." In Network Psychometrics with R, 45–65. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003111238-4.

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Burger, Julian, Ria H. A. Hoekstra, Alessandra C. Mansueto, and Sacha Epskamp. "Network Estimation from Time Series and Panel Data." In Network Psychometrics with R, 169–92. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003111238-13.

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Lunansky, Gabriela, Sacha Epskamp, and Adela-Maria Isvoranu. "Short Introduction to R." In Network Psychometrics with R, 29–44. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003111238-3.

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Epskamp, Sacha, Jonas M. B. Haslbeck, Adela-Maria Isvoranu, and Claudia D. van Borkulo. "Pairwise Markov Random Fields." In Network Psychometrics with R, 93–110. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003111238-8.

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Waldorp, Lourens J., Denny Borsboom, and Sacha Epskamp. "Association and Conditional Independence." In Network Psychometrics with R, 79–89. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003111238-6.

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Isvoranu, Adela-Maria, and Sacha Epskamp. "Constructing and Drawing Networks in qgraph." In Network Psychometrics with R, 67–78. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003111238-5.

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Dablander, Fabian, and Riet van Bork. "Causal Inference." In Network Psychometrics with R, 213–32. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003111238-16.

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Conference papers on the topic "Network psychometric"

1

Thorat, Shashikant G., Amol P. Bhagat, and Kiran A. Dongre. "Neural Network Based Psychometric Analysis for Employability." In 2018 International Conference on Research in Intelligent and Computing in Engineering (RICE). IEEE, 2018. http://dx.doi.org/10.1109/rice.2018.8509092.

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Prokopyev, N. A., G. Z. Vakhitov, and P. N. Ustin. "Indexing of Social Network Texts for Psychometric Model of Academic Success Prediction." In International Scientific Conference “Digitalization of Education: History, Trends and Prospects” (DETP 2020). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.200509.143.

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Di Nuovo, Alessandro G., Santo Di Nuovo, Serafino Buono, and Vincenzo Catania. "Feedforward artificial neural network to estimate iq of mental retarded people from different psychometric instruments." In 2009 International Joint Conference on Neural Networks (IJCNN 2009 - Atlanta). IEEE, 2009. http://dx.doi.org/10.1109/ijcnn.2009.5178847.

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Duarte, Vannessa de J. "Artificial Neural Network techniques to distinguish children with Fetal Alcohol Spectrum Disorder from psychometric data." In 2020 39th International Conference of the Chilean Computer Science Society (SCCC). IEEE, 2020. http://dx.doi.org/10.1109/sccc51225.2020.9281147.

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Hasan, Muhammad Naimul, Anower Jahan Tamanna, and Md Armanul Haque. "Divergence of Upper Materials to Specific Footwear Construction: Seeking a Culture of Sustainable Material Solicitation." In The 9th International Conference on Advanced Materials and Systems. INCDTP - Leather and Footwear Research Institute (ICPI), Bucharest, Romania, 2022. http://dx.doi.org/10.24264/icams-2022.v.1.

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Footwear is equally a fashion and function apparel item constructed of leather and non-leather materials. This research aims to investigate the selection of materials for footwear fabrication corresponding to shoe functionality and fashion aspects of consumers. Here, an attempt is taken to build a network among the consumer perception of cherry-picking shoes, sustainable fashion, and the physicomechanical behavior of versatile upper materials focusing on leather and non-leather. A psychometric rating scale is used to rate the relationship of sustainability attitude regarding both materials and users. The chosen materials are leather, pleather, and fabric. The leather items are suede, semi-aniline, and corrected grain leather whereas non-leather materials are canvas cotton, PUCF, and PVCF. The randomly selected materials with a thickness of 1.2-2.4 mm for the dress (oxford), casual, and boot shoe fabrication were brought under rigorous physicomechanical tests following ISO and SATRA methods. Besides, a quantitative statistical analysis of psychophysical material information test was carried out among 132 valid respondents. Though cent-percent of finished leather and most of the canvas fabric samples have satisfied standards of physicomechanical characteristics whereas pleather was underneath. The weighted score for green materials solicitation for sustainable use was 2.5 ± 0.01on a psychometric rating scale of 5.00, quite unsatisfactory due to a deficiency of materials knowledge among consumers. Moreover, the Pearson correlation coefficient is about 0.99152 and a p-value of 0.03 0.05 has been observed which provided strong evidence of a statistically significant positive correlation among the variables on the sustainability attitude scale of material cherry-picking.
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Dietrich, Carl, Edward Wolfe, and Garrett Vanhoy. "Evaluation of Multi-Objective Optimizers for Cognitive Radio using Psychometric Methods." In 7th International Conference on Cognitive Radio Oriented Wireless Networks. IEEE, 2012. http://dx.doi.org/10.4108/icst.crowncom.2012.248438.

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Jabson, Jennifer M., Shioban Torres, and Deborah Bowen. "Abstract B16: Ethnic differences in the psychometric properties of social networks and cancer knowledge." In Abstracts: AACR International Conference on Frontiers in Cancer Prevention Research‐‐ Oct 22-25, 2011; Boston, MA. American Association for Cancer Research, 2011. http://dx.doi.org/10.1158/1940-6207.prev-11-b16.

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Kuo, Chu-Hsuan, Malayka Mottarella, Theodros Haile, and Chantel S. Prat. "Predicting Programming Success: How Intermittent Knowledge Assessments, Individual Psychometrics, and Resting-State EEG Predict Python Programming and Debugging Skills." In 2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM). IEEE, 2022. http://dx.doi.org/10.23919/softcom55329.2022.9911411.

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Lai, Yi-Horng, and Fen-Fen Huang. "A Study on the Intention to Use the Online Face Mask Ordering System - An Application of Network Psychometrics." In 2020 IEEE 2nd Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS). IEEE, 2020. http://dx.doi.org/10.1109/ecbios50299.2020.9203720.

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