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Implementation Aspects in Regularized Structural Equation Models
Algorithms, 2023 This article reviews several implementation aspects in estimating regularized single-group and multiple-group structural equation models (SEM). It is demonstrated that approximate estimation approaches that rely on a differentiable approximation of non ...
Alexander Robitzsch
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BMC Medical Research Methodology, 2022 Background Availability of linked biomedical and social science data has risen dramatically in past decades, facilitating holistic and systems-based analyses.
Xuejia Ke +2 more
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Between-Item Multidimensional IRT: How Far Can the Estimation Methods Go?
Psych, 2021 Multidimensional item response models are known to be difficult to estimate, with a variety of estimation and modeling strategies being proposed to handle the difficulties.
Mauricio Garnier-Villarreal +2 more
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Bayesian Evaluation of Inequality-Constrained Hypotheses in SEM Models Using M plus [PDF]
Structural Equation Modeling: A Multidisciplinary Journal, 2012 Researchers in the behavioural and social sciences often have expectations that can be expressed in the form of inequality constraints among the parameters of a structural equation model resulting in an informative hypothesis. The question they would like an answer to is "Is the Hypothesis Correct" or "Is the hypothesis incorrect?".
Van de Schoot, Rens +3 more
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Efficient utility-based clustering over high dimensional partition spaces [PDF]
, 2009 Because of the huge number of partitions of even a moderately sized dataset, even when Bayes factors have a closed form, in model-based clustering a comprehensive search for the highest scoring (MAP) partition is usually impossible.
Smith, JQ +9 more
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A Bayesian network approach to explaining time series with changing structure [PDF]
, 2004 Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any model that is learnt from the data will average over the different dependency structures.
Liu, X, Tucker, A
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Structural Equation Modeling of Vocabulary Size and Depth Using Conventional and Bayesian Methods
Frontiers in Psychology, 2020 In classifications of vocabulary knowledge, vocabulary size and depth have often been separately conceptualized (Schmitt, 2014). Although size and depth are known to be substantially correlated, it is not clear whether they are a single construct or two ...
Rie Koizumi, Yo In’nami
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Approximate Bayesian Inference Based on Expected Evaluations [PDF]
, 2023 Approximate Bayesian computing (ABC) and Bayesian Synthetic likelihood (BSL) are two popular families of methods to evaluate the posterior distribution when the likelihood function is not available or tractable.
Hammer, Hugo Lewi, Riegler, Michael
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Multi-trait multi-locus SEM model discriminates SNPs of different effects
BMC Genomics, 2020 Background There is a plethora of methods for genome-wide association studies. However, only a few of them may be classified as multi-trait and multi-locus, i.e.
Anna A. Igolkina +4 more
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Approximate Bayesian inference for doubly robust estimation [PDF]
, 2015 Doubly robust estimators are typically constructed by combining outcome regression and propensity score models to satisfy moment restrictions that ensure consistent estimation of causal quantities provided at least one of the component models is ...
McCoy, EJ, Graham, DJ, Stephens, DA
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