Data Interpretation, Statistical
"Data Interpretation, 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.
Application of statistical procedures to analyze specific observed or assumed facts from a particular study.
Descriptor ID |
D003627
|
MeSH Number(s) |
E05.245.380 E05.318.740.300 L01.313.500.750.190.380 N05.715.360.750.300 N06.850.520.830.300
|
Concept/Terms |
Data Interpretation, Statistical- Data Interpretation, Statistical
- Data Analysis, Statistical
- Statistical Data Interpretation
- Statistical Data Analysis
- Analyses, Statistical Data
- Analysis, Statistical Data
- Data Analyses, Statistical
- Statistical Data Analyses
- Data Interpretations, Statistical
- Interpretations, Statistical Data
- Statistical Data Interpretations
- Interpretation, Statistical Data
|
Below are MeSH descriptors whose meaning is more general than "Data Interpretation, Statistical".
Below are MeSH descriptors whose meaning is more specific than "Data Interpretation, Statistical".
This graph shows the total number of publications written about "Data Interpretation, Statistical" by people in this website by year, and whether "Data Interpretation, 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 |
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1995 | 1 | 0 | 1 |
1998 | 1 | 0 | 1 |
1999 | 0 | 3 | 3 |
2001 | 0 | 2 | 2 |
2004 | 0 | 1 | 1 |
2005 | 1 | 2 | 3 |
2006 | 1 | 4 | 5 |
2007 | 0 | 4 | 4 |
2008 | 1 | 2 | 3 |
2009 | 1 | 3 | 4 |
2010 | 0 | 5 | 5 |
2011 | 3 | 1 | 4 |
2012 | 2 | 4 | 6 |
2013 | 1 | 1 | 2 |
2014 | 2 | 3 | 5 |
2015 | 2 | 3 | 5 |
2016 | 2 | 2 | 4 |
2017 | 0 | 1 | 1 |
2018 | 0 | 1 | 1 |
2019 | 1 | 0 | 1 |
2020 | 0 | 1 | 1 |
2021 | 0 | 1 | 1 |
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Below are the most recent publications written about "Data Interpretation, Statistical" by people in Profiles.
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The Childhood Vaccination Schedule and the Lack of Association With Type 1 Diabetes. Pediatrics. 2021 12 01; 148(6).
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Methodologic Guidance and Expectations for the Development and Reporting of Prediction Models and Causal Inference Studies. Ann Am Thorac Soc. 2020 06; 17(6):679-682.
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Why we need a small data paradigm. BMC Med. 2019 07 17; 17(1):133.
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Using the E-Value to Assess the Potential Effect of Unmeasured Confounding in Observational Studies. JAMA. 2019 Feb 12; 321(6):602-603.
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Good practices for the design, analysis, and interpretation of observational studies on birth spacing and perinatal health outcomes. Paediatr Perinat Epidemiol. 2019 01; 33(1):O15-O24.
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Data Sharing and Embedded Research. Ann Intern Med. 2017 11 07; 167(9):668-670.
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Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium. Am J Hum Genet. 2016 06 02; 98(6):1067-1076.
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Methods for using clinical laboratory test results as baseline confounders in multi-site observational database studies when missing data are expected. Pharmacoepidemiol Drug Saf. 2016 07; 25(7):798-814.
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Executive Summary: Heart Disease and Stroke Statistics--2016 Update: A Report From the American Heart Association. Circulation. 2016 Jan 26; 133(4):447-54.
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Q-learning residual analysis: application to the effectiveness of sequences of antipsychotic medications for patients with schizophrenia. Stat Med. 2016 06 15; 35(13):2221-34.