Bengt Muthén

62.6k citations
170 papers · 44.8k · 25 hit papers · h-index 77

Impact in

Papers in

Bengt Muthén

170 papers receiving 42.4k citations

Bengt Muthén's Hit Papers

Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives 2022 · 130 citations
1300+8+16Years since publication2.5k5.0k7.5k

Peers

Bengt Muthén
Comparison fields: 5 of 217
  • Applied Psychology 2.7k
  • Statistics and Probability 4.5k
  • Experimental and Cognitive Psychology 6.6k
  • Clinical Psychology 9.9k
  • Social Psychology 8.8k
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Citations per year

Countries citing papers authored by Bengt Muthén

Since Specialization
Citations

This map shows the geographic impact of Bengt Muthén's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bengt Muthén with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bengt Muthén more than expected).

Fields of papers citing papers by Bengt Muthén

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bengt Muthén. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bengt Muthén. The network helps show where Bengt Muthén may publish in the future.

Co-authors

The 25 scholars most cited alongside Bengt Muthén, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bengt Muthén Line = papers co-authored together Bengt Muthén links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 170 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study
Hit paper breakdown →
20078448
2
Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance.
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19893026
3
Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using Mplus
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20142618
4
Assessing Reliability and Stability in Panel Models
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19772424
5
How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power
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20021702
6
A General Structural Equation Model with Dichotomous, Ordered Categorical, and Continuous Latent Variable Indicators
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19841509
7
A comparison of some methodologies for the factor analysis of non‐normal Likert variables
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19851390
8
Complex Sample Data in Structural Equation Modeling
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19951298
9
Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm
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19991146
10
Bayesian structural equation modeling: A more flexible representation of substantive theory.
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20121127
11
Multilevel Covariance Structure Analysis
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1994925
12
Investigating population heterogeneity with factor mixture models.
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2005879
13
Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students' Evaluations of University Teaching
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2009856
14
Beyond SEM: General Latent Variable Modeling
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2002819
15
A new look at the big five factor structure through exploratory structural equation modeling.
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2010710
16
On Structural Equation Modeling with Data that are not Missing Completely at Random
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1987708
17
The multilevel latent covariate model: A new, more reliable approach to group-level effects in contextual studies.
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2008606
18
General longitudinal modeling of individual differences in experimental designs: A latent variable framework for analysis and power estimation.
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1997602
19
Dynamic Structural Equation Models
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2017567
20
Performance of Factor Mixture Models as a Function of Model Size, Covariate Effects, and Class-Specific Parameters
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2007516

About Bengt Muthén

Bengt Muthén is a scholar working on Statistics and Probability, Management Science and Operations Research, Computer Networks and Communications, Experimental and Cognitive Psychology and Artificial Intelligence, having authored 170 papers that have together received 44.8k indexed citations. Recurring topics across this work include Psychometric Methodologies and Testing (33 papers), Statistical Methods and Bayesian Inference (32 papers), Advanced Statistical Modeling Techniques (25 papers), Mental Health Research Topics (21 papers), Advanced Causal Inference Techniques (19 papers), Bayesian Methods and Mixture Models (14 papers), Statistical Methods and Inference (13 papers) and Substance Abuse Treatment and Outcomes (11 papers). The work is most often cited by research in Applied Psychology (2.7k citations), Statistics and Probability (4.5k citations), Experimental and Cognitive Psychology (6.6k citations), Clinical Psychology (9.9k citations) and Social Psychology (8.8k citations). Bengt Muthén has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include Tihomir Asparouhov, Karen Nylund‐Gibson, Linda K. Muthén, Barbara M. Byrne, Richard J. Shavelson, Gitta H. Lubke, David M. Kaplan, Albert Satorra, Gene F. Summers and Duane F. Alwin. Their work appears in journals such as Structural Equation Modeling A Multidisciplinary Journal, Psychological Methods, Psychometrika, British Journal of Mathematical and Statistical Psychology and Addiction.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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