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Search · four archives
23 papers · ranked by Valyu relevance
Piotr Tarka
This paper is a tribute to researchers who have significantly contributed to improving and advancing structural equation modeling (SEM). It is, therefore, a brief overview of SEM and presents its beginnings, historical development, its usefulness in the social sciences and the statistical and philosophical…
Tanya N Beran, Claudio Violato
Background Structural equation modeling (SEM) is a set of statistical techniques used to measure and analyze the relationships of observed and latent variables. Similar but more powerful than regression analyses, it examines linear causal relationships among variables, while simultaneously accounting for measurement…
Marko Sarstedt, Christian M. Ringle
Structural equation modeling (SEM) is a statistical analytic framework that allows researchers to specify and test models with observed and latent (or unobservable) variables and their generally linear relationships. In the past decades, SEM has become a standard statistical analysis technique in behavioral…
Alina Dragan, Noori Akhtar-Danesh
Background Obesity and depression are two major diseases which are associated with many other health problems such as hypertension, dyslipidemia, diabetes mellitus, coronary heart disease, stroke, myocardial infarction, heart failure in patients with systolic hypertension, low bone mineral density and increased…
Anna A. Igolkina, G. A. Meshcheryakov
Structural equation modelling (SEM) is a multivariate statistical technique for estimating complex relationships between observed and latent variables. Although numerous SEM packages exist, each of them has limitations. Some packages are not free or open-source; the most popular package not having this disadvantage is…
Florian Schuberth, Jörg Henseler, Theo K. Dijkstra
This article introduces confirmatory composite analysis (CCA) as a structural equation modeling technique that aims at testing composite models. It facilitates the operationalization and assessment of design concepts, so-called artifacts. CCA entails the same steps as confirmatory factor analysis: model specification…
Bambang Widjanarko Otok, Purhadi, Riry Sriningsih, Dalbergia Septi Dila
'Dalbergia Septi Dila'] Nutrition is one of the important factors that play a major role in the growth and development of children so that they can develop optimally. Child malnutrition, such as stunting, underweight, and wasting, is a significant problem in Indonesia. The World Health Organization (WHO) determined…
Édgar Benítez, Álvaro Balaguer
Context of Causal Inference: A Case Study on Personal Positive Youth Development Authors: ['Édgar Benítez' 'Álvaro Balaguer'] In this study, the combined use of structural equation modeling (SEM) and Bayesian network modeling (BNM) in causal inference analysis is revisited. The perspective highlights the debate between…
Mario Fordellone, Maurizio Vichi
The identification of different homogeneous groups of observations and their appropriate analysis in PLS-SEM has become a critical issue in many application fields. Usually, both SEM and PLS-SEM assume the homogeneity of all units on which the model is estimated, and approaches of segmentation present in literature…
Ankur Ankan, Inge M. N. Wortel, Kenneth A. Bollen, Johannes Textor
Measurement error is ubiquitous in many variables – from blood pressure recordings in physiology to intelligence measures in psychology. Structural equation models (SEMs) account for the process of measurement by explicitly distinguishing between latent variables and their measurement indicators. Users often fit entire…
Edgar C. Merkle, Ellen Fitzsimmons, James Uanhoro, Ben Goodrich
Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be…
Gregory R. Hancock, Florian Schuberth
Composites, or linear combinations of variables, play an important role in multivariate behavioral research. They appear in the form of indices, inventories, formative constructs, parcels, and emergent variables. Although structural equation modeling is widely used to study relations between variables, current…
Hashem Salarzadeh Jenatabadi
This paper provides a tutorial discussion on analyzing structural equation modelling (SEM). SEM can be regarded as regression models with observed and unobserved indicators, have been extensively applied to practical and fundamental studies. We deliver an introduction to SEM method and a detailed description of how to…
Christian Damgaard
Spatial and temporal pin-point plant cover monitoring data are fitted in a structural equation model in order to understand and quantify the effect of selected environmental and land-use drivers on the observed variation and changes in the vegetation of acid grasslands. The important sources of measurement- and…
Capt Sirsendu Ghosh
Exceptional growth in the development of oral health of various populations worldwide over the last three decades cannot lessen tribulations in dental caries, periodontal disease, and psychological problems, which are still prevalent in many communities, especially among the poor socioeconomic groups in developing…
Authors not listed
Background: Batch reactor process optimization has traditionally relied on Analysis of Variance (ANOVA) for factor effect quantification. However, Structural Equation Modeling (SEM) and machine learning (ML) offer complementary mechanistic and predictive capabilities that remain underexplored in chemical engineering…
Kyle A. Kurkela, Rose A. Cooper, Ehri Ryu, Maureen Ritchey
The brain is composed of networks of interacting brain regions that support higher order cognition. For instance, a posterior medial (PM) network appears to support recollection and other forms of episodic construction. Past research has focused largely on the roles of individual brain regions in recollection or on…
Adam Sullivan, Tyler J. VanderWeele
In this paper, we consider the extent of the biases that may arise when an unmeasured confounder is omitted from a structural equation model (SEM) and we propose sensitivity analysis techniques to correct for such biases. We give an analysis of which effects in an SEM are, and are not, biased by an unmeasured…
Elliot M. Tucker-Drob
DiPrete, Burik, & Koellinger (4; http://dx.doi.org/10.1101/134197) propose using an instrumental variable (IV) framework to correct genome-wide polygenic scores (GPSs) for error, thereby producing disattenuated estimates of SNP heritability in predictions samples. They demonstrate their approach by producing two…
Authors not listed
Scientific modeling often requires navigating a trade-off between physical interpretability and empirical accuracy—a task that can take weeks of iteration, especially in systems with partial observability, structural complexity, and experimental errors. Here, we show how a state-of-the-art agentic reasoning-and-coding…
Zhiwen Pan, Jan Dellith, Lothar Wondraczek
Understanding the multivariate origin of physical properties is particularly complex for polyionic glasses. As a concept, the term genome has been used to describe the entirety of structure-property relations in solid materials, based on functional genes acting as descriptors for a particular property, for example, for…
Woo-Young Ahn, Nathaniel Haines, Lei Zhang
Reinforcement learning and decision-making (RLDM) provide a quantitative framework, which allows us to specify psychiatric conditions with basic dimensions of neurocognitive functioning. RLDM offer a novel approach to assess and potentially diagnose psychiatric patients, and there is growing enthusiasm on RLDM and…
Bruis van Vlijmen, Patrick A. Asinger, Vivek Lam, Xiao Cui + 14 more
Bruis van Vlijmen1,2 , Vivek Lam1,2 , Patrick A. Asinger 3 , Xiao Cui1,2 , Devi Ganapathi1,2 , Shijing Sun 4 , Patrick K. Herring 4 , Chirranjeevi Balaji Gopal 4 , Natalie Geise 2 , Haitao D. Deng 1,2 , Henry L. Thaman1,2 , Stephen Dongmin Kang 1 , Amalie Trewartha 4 , Abraham Anapolsky 4 , Brian D. Storey 4 , William…