Models, Statistical
"Models, Statistical" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.
| Descriptor ID |
D015233
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| MeSH Number(s) |
E05.318.740.500 E05.599.835 N05.715.360.750.530 N06.850.520.830.500
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| Concept/Terms |
Models, Statistical- Models, Statistical
- Statistical Model
- Probabilistic Models
- Model, Probabilistic
- Models, Probabilistic
- Probabilistic Model
- Model, Statistical
- Statistical Models
Two-Parameter Models- Two-Parameter Models
- Model, Two-Parameter
- Models, Two-Parameter
- Two Parameter Models
- Two-Parameter Model
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Below are MeSH descriptors whose meaning is more general than "Models, Statistical".
Below are MeSH descriptors whose meaning is more specific than "Models, Statistical".
This graph shows the total number of publications written about "Models, Statistical" by people in this website by year, and whether "Models, Statistical" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 1996 | 1 | 1 | 2 | | 1997 | 1 | 3 | 4 | | 1998 | 0 | 2 | 2 | | 1999 | 0 | 1 | 1 | | 2000 | 1 | 4 | 5 | | 2001 | 0 | 2 | 2 | | 2002 | 2 | 6 | 8 | | 2003 | 5 | 12 | 17 | | 2004 | 3 | 12 | 15 | | 2005 | 3 | 20 | 23 | | 2006 | 6 | 20 | 26 | | 2007 | 7 | 16 | 23 | | 2008 | 4 | 13 | 17 | | 2009 | 6 | 20 | 26 | | 2010 | 9 | 10 | 19 | | 2011 | 10 | 21 | 31 | | 2012 | 17 | 18 | 35 | | 2013 | 12 | 26 | 38 | | 2014 | 9 | 17 | 26 | | 2015 | 15 | 14 | 29 | | 2016 | 8 | 20 | 28 | | 2017 | 10 | 18 | 28 | | 2018 | 13 | 14 | 27 | | 2019 | 14 | 15 | 29 | | 2020 | 9 | 19 | 28 | | 2021 | 8 | 4 | 12 | | 2022 | 5 | 2 | 7 | | 2023 | 1 | 2 | 3 | | 2024 | 8 | 6 | 14 | | 2025 | 2 | 6 | 8 | | 2026 | 6 | 3 | 9 |
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Below are the most recent publications written about "Models, Statistical" by people in Profiles.
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Pustejovsky JE. p-Uniform* is an estimator of the three-parameter selection model: Commentary on van Aert and van Assen (2026). Psychon Bull Rev. 2026 09 03; 33(7).
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Thomas SD, Kaizer AM. Subgroup analysis using exchangeability probabilities. Contemp Clin Trials. 2026 Oct; 169:108412.
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Luna LH, Parra RC, Garizoain G, Ubelaker DH, Baccino E, L Abbé E, Marques C, Sarajlic N, Gualdi-Russo E, Caldas I, Mishra M, Dulabutr D, Sabourin C, Giannotti PS, Mansegosa D, Pinto PHV, Adserias-Garriga J, Rodríguez PA, Moraitis K, Zorba E, Flores CH, Martrille L, Camarasa F, Franco A, Baz A, Condori L, Escalante-Flórez K, Retana-Milán F, Faviero CS, Retamal R, Miamoto P, Peccerelli F, Rivera C, da Silva RHA, Castellanos D, Aranda CM. A large-scale Bayesian validation of FIDBV2 and FIDBV3 methods for adult age-at-death estimation using root dentin translucency in single-rooted teeth. Int J Legal Med. 2026 Nov; 140(6):4215-4240.
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Diana G, Sermet BS, Broussard GJ, Wang SS, DiGregorio DA. High-frequency spike inference with particle Gibbs sampling. Elife. 2026 May 27; 13.
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Middleton CE, Larremore DB. Statistical methods for estimating the protective effects of immune markers using test-negative designs. Am J Epidemiol. 2026 05 07; 195(5):1357-1364.
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Razzaghi H, Wieand K, Dickinson KL, Kahn MG, Roy J, Blacketer C, Christakis DA, Forrest CB, Greenberg J, Lehmann HP, Marsolo KA, Sciolla J, Weiner MG, Weiskopf NG, Bailey LC. Beyond Missingness: Systematizing Methods for Comprehensive Data Fitness Assessment in Clinical Research. J Med Internet Res. 2026 Apr 14; 28:e76398.
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Fei Y, Juarez-Colunga E, El-Jawahri A, Kutner JS, Colborn K. Joint Modeling of Quality of Life and Survival Using a Bayesian Approach in a Retrospective Time Scale. Stat Med. 2026 Mar; 45(6-7):e70505.
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Winters DE. Probabilistic Cognitive State Modeling (PCSM): Decoding dynamic brain states to derive emergent cognitive processing properties from task fMRI. Neuroimage. 2026 03; 328:121807.
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Schmiege SJ, Kaizer LK, Stevens CJ, Bryan AD. Longitudinal mixture modeling approaches to capture heterogeneity in affective response to exercise measured within bout and over study waves. J Behav Med. 2026 04; 49(2):138-156.
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Chen J, Wei S, Liu Y, Bian Z, He Y, Carass A, Bai H, Du Y. Unsupervised learning of spatially varying regularization for diffeomorphic image registration. Med Image Anal. 2026 02; 108:103887.
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