 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 | 3 | 3 | | 2002 | 2 | 6 | 8 | | 2003 | 5 | 12 | 17 | | 2004 | 3 | 10 | 13 | | 2005 | 3 | 22 | 25 | | 2006 | 6 | 20 | 26 | | 2007 | 7 | 16 | 23 | | 2008 | 4 | 15 | 19 | | 2009 | 6 | 22 | 28 | | 2010 | 8 | 10 | 18 | | 2011 | 11 | 22 | 33 | | 2012 | 16 | 17 | 33 | | 2013 | 12 | 25 | 37 | | 2014 | 10 | 19 | 29 | | 2015 | 14 | 14 | 28 | | 2016 | 9 | 18 | 27 | | 2017 | 12 | 19 | 31 | | 2018 | 13 | 15 | 28 | | 2019 | 17 | 16 | 33 | | 2020 | 10 | 20 | 30 | | 2021 | 7 | 4 | 11 | | 2022 | 5 | 2 | 7 | | 2023 | 1 | 2 | 3 | | 2024 | 8 | 6 | 14 | | 2025 | 2 | 4 | 6 | | 2026 | 3 | 1 | 4 |
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Below are the most recent publications written about "Models, Statistical" by people in Profiles.
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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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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 Mar; 328:121807.
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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 Feb; 108:103887.
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Barnatchez K, Nethery R, Shepherd BE, Parmigiani G, Josey KP. Flexible and efficient estimation of causal effects with error-prone exposures: a control variates approach for measurement error. Biometrics. 2025 Oct 08; 81(4).
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Colborn KL, Fei Y, Henderson WG, Zhuang Y, Dyas AR, Matheny ME, Stuart CM, Meguid RA. Estimation of risk-adjusted postoperative infection outcomes using interpretable machine learning and electronic health record data. Am J Infect Control. 2026 02; 54(2):139-144.
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Goodman JE, Korchevskiy A, Wylie AG. Comparison of various methodological approaches to model asbestos thresholds for mesothelioma. Front Public Health. 2025; 13:1569343.
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Grekov P, Pustejovsky JE, Klingbeil DA. Flexible distributional models for meta-analysis of reading fluency outcomes from single-case designs: An examination using Bayesian methods. J Sch Psychol. 2025 06; 110:101429.
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Stoneman HR, Price AM, Trout NS, Lamont R, Tifour S, Pozdeyev N, Crooks K, Lin M, Rafaels N, Gignoux CR, Marker KM, Hendricks AE. Characterizing substructure via mixture modeling in large-scale genetic summary statistics. Am J Hum Genet. 2025 Feb 06; 112(2):235-253.
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