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Tihomir Asparouhov

Tihomir Asparouhov

D-Index & Metrics

Mathematics

D-Index
39
Citations
31630
World Ranking
2109
National Ranking
143

Overview

Tihomir Asparouhov is affiliated with Mplus in the United Kingdom. Their research primarily focuses on advancing psychometric methodologies, statistical methods, and Bayesian inference, with applications spanning mental health research topics and behavioral health interventions.

Their recent publications include studies published in prominent journals:

  • Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives, 2022, Social Science Research
  • Advances in Bayesian Model Fit Evaluation for Structural Equation Models, 2020, Structural Equation Modeling A Multidisciplinary Journal
  • Bayesian estimation of single and multilevel models with latent variable interactions, 2020, Structural Equation Modeling A Multidisciplinary Journal
  • Latent transition analysis with random intercepts (RI-LTA), 2020, Psychological Methods
  • Residual Structural Equation Models, 2022, Structural Equation Modeling A Multidisciplinary Journal

They have collaborated frequently with several researchers, notably:

  • Bengt Muthén
  • Heinz Leitgöb
  • Daniel Seddig
  • Dorothée Behr

Tihomir Asparouhov's publications appear predominantly in the following venues:

  • Structural Equation Modeling A Multidisciplinary Journal
  • Psychological Methods
  • Social Science Research
  • Psych
  • The SAGE Encyclopedia of Research Design

Their research spans multiple subfields, including:

  • Statistics and Probability
  • Management Science and Operations Research
  • Experimental and Cognitive Psychology
  • Transportation
  • Applied Psychology

Key topics covered in their work include:

  • Psychometric Methodologies and Testing
  • Statistical Methods and Bayesian Inference
  • Mental Health Research Topics
  • Statistical Methods and Inference
  • Behavioral Health and Interventions
  • Social and Intergroup Psychology
  • Multi-Criteria Decision Making

Best Publications

  • Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study

    Karen L. Nylund;Tihomir Asparouhov;Bengt O. Muthén

  • Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using Mplus

    Tihomir Asparouhov;Bengt Muthén

  • Exploratory Structural Equation Modeling.

    Tihomir Asparouhov;Bengt Muthen

  • Bayesian structural equation modeling: A more flexible representation of substantive theory.

    Bengt Muthén;Tihomir Asparouhov

  • Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students' Evaluations of University Teaching

    Herbert Warren Marsh;Bengt Muthen;Tihomir Asparouhov;Oliver Ludtke

  • A new look at the big five factor structure through exploratory structural equation modeling.

    Herbert W. Marsh;Oliver Lüdtke;Bengt Muthén;Tihomir Asparouhov

  • The Multilevel Latent Covariate Model: A New, More Reliable Approach to Group-Level Effects in Contextual Studies.

    Oliver Ludtke;Herbert Warren Marsh;Alexander Robitzsch;Ulrich Trautwein

  • Dynamic structural equation models

    Tihomir Asparouhov;Ellen L. Hamaker;Bengt Muthén

  • Multiple-Group Factor Analysis Alignment

    Tihomir Asparouhov;Bengt Muthén

  • Sampling Weights in Latent Variable Modeling

    Tihomir Asparouhov

  • Doubly-Latent Models of School Contextual Effects: Integrating Multilevel and Structural Equation Approaches to Control Measurement and Sampling Error.

    Herbert Warren Marsh;Oliver Ludtke;Alexander Robitzsch;Ulrich Trautwein

  • At the Frontiers of Modeling Intensive Longitudinal Data: Dynamic Structural Equation Models for the Affective Measurements from the COGITO Study.

    Ellen L. Hamaker;Tihomir Asparouhov;Annette Brose;Florian Schmiedek

  • Bayesian Structural Equation Modeling With Cross-Loadings and Residual Covariances Comments on Stromeyer et al.

    Tihomir Asparouhov;Bengt Muthén;Alexandre J. S. Morin

  • General Multi-Level Modeling with Sampling Weights

    Tihomir Asparouhov

  • Causal Effects in Mediation Modeling: An Introduction With Applications to Latent Variables

    Bengt Muthén;Tihomir Asparouhov

  • What to do when scalar invariance fails: The extended alignment method for multi-group factor analysis comparison of latent means across many groups.

    Herbert W. Marsh;Jiesi Guo;Philip D. Parker;Benjamin Nagengast

  • IRT studies of many groups: the alignment method.

    Bengt Muthén;Tihomir Asparouhov

  • Latent Variable Centering of Predictors and Mediators in Multilevel and Time-Series Models

    Tihomir Asparouhov;Bengt Muthén

  • Growth modeling with nonignorable dropout: alternative analyses of the STAR*D antidepressant trial.

    Bengt Muthén;Tihomir Asparouhov;Aimee M. Hunter;Andrew F. Leuchter

  • Beyond multilevel regression modeling: Multilevel analysis in a general latent variable framework.

    Bengt Muthén;Tihomir Asparouhov

  • Item response mixture modeling: application to tobacco dependence criteria.

    Bengt Muthen;Tihomir Asparouhov

Frequent Co-Authors

Herbert W. Marsh
Herbert W. Marsh Australian Catholic University
Ulrich Trautwein
Ulrich Trautwein University of Tübingen
Oliver Lüdtke
Oliver Lüdtke Leibniz Institute for Science and Mathematics Education
Alexandre J. S. Morin
Alexandre J. S. Morin Concordia University
Benjamin Nagengast
Benjamin Nagengast University of Tübingen
Booil Jo
Booil Jo Stanford University
Florian Schmiedek
Florian Schmiedek Max Planck Society
Nicholas S. Ialongo
Nicholas S. Ialongo Johns Hopkins University
Philip D. Parker
Philip D. Parker Australian Catholic University
Dorret I. Boomsma
Dorret I. Boomsma Vrije Universiteit Amsterdam

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