Latent Variable Models
Latent Variable Models is a class of statistical models that infer unobserved (latent) variables from observed data by specifying probabilistic relationships between the latent constructs and the observed variables, thereby accounting for hidden structure or heterogeneity in the data.
3.4K
Publications
438.9K
Citations
6.3K
Authors
1.8K
Institutions
Publications per year
2017–2026
1K
3.4K
PLS-SEM: Indeed a Silver Bullet
Joe F. Hair, Christian M. Ringle, Marko Sarstedt · The Journal of Marketing Theory and Practice · 2011 · 20.9K citations
1–5 of 3.4K
6.3K
33
h-index
Chongqing Institute of Green and Intelligent Technology, China
46 publications · 4.1K citations
33
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32
h-index
University of North Carolina at Chapel Hill, United States
22 publications · 21.8K citations
20
h-index
Chongqing Institute of Green and Intelligent Technology, China
21 publications · 2K citations
18
h-index
1–5 of 6.3K
1.8K
Carnegie Mellon University
Pittsburgh, United States
38 h-index
147 publications
15.8K citations
University of California, Los Angeles
Los Angeles, United States
36 h-index
84 publications
38K citations

Tilburg University
Tilburg, The Netherlands
35 h-index
129 publications
16K citations

Pennsylvania State University
State College, United States
33 h-index
83 publications
12.9K citations
Columbia University
New York, United States
33 h-index
84 publications
7.1K citations
Princeton University
Princeton, United States
32 h-index
92 publications
13.4K citations

University of Amsterdam
Amsterdam, The Netherlands
32 h-index
96 publications
17.1K citations
Chongqing Institute of Green and Intelligent Technology
Chongqing, China
29 h-index
86 publications
7.7K citations
1–8 of 1.8K
SEM · 193 publications · 37.4K citations
71
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118 publications · 14.8K citations
54
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Repository · 206 publications · 14.9K citations
49
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58 publications · 14.3K citations
48
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73 publications · 14.1K citations
44
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