 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
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| MeSH Number(s) |
E05.245.380 E05.318.740.300 L01.700.508.190.380 N05.715.360.750.300 N06.850.520.830.300
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| Concept/Terms |
Data Interpretation, Statistical- Data Interpretation, Statistical
- Interpretation, Statistical Data
- Data Analysis, Statistical
- Statistical Data Analysis
- Analyses, Statistical Data
- Analysis, Statistical Data
- Data Analyses, Statistical
- Statistical Data Analyses
- Data Interpretations, Statistical
- Interpretations, Statistical Data
- Statistical Data Interpretations
- Statistical Data Interpretation
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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 |
|---|
| 1989 | 0 | 1 | 1 | | 1990 | 1 | 0 | 1 | | 1991 | 0 | 3 | 3 | | 1992 | 1 | 0 | 1 | | 1993 | 0 | 1 | 1 | | 1994 | 1 | 0 | 1 | | 1995 | 0 | 3 | 3 | | 1996 | 2 | 0 | 2 | | 1997 | 0 | 3 | 3 | | 1998 | 0 | 2 | 2 | | 1999 | 2 | 3 | 5 | | 2000 | 0 | 3 | 3 | | 2001 | 0 | 2 | 2 | | 2002 | 1 | 3 | 4 | | 2003 | 1 | 4 | 5 | | 2004 | 1 | 4 | 5 | | 2005 | 2 | 5 | 7 | | 2006 | 1 | 9 | 10 | | 2007 | 1 | 14 | 15 | | 2008 | 2 | 8 | 10 | | 2009 | 1 | 6 | 7 | | 2010 | 1 | 8 | 9 | | 2011 | 4 | 4 | 8 | | 2012 | 4 | 6 | 10 | | 2013 | 2 | 5 | 7 | | 2014 | 1 | 3 | 4 | | 2015 | 3 | 2 | 5 | | 2016 | 0 | 2 | 2 |
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Below are the most recent publications written about "Data Interpretation, Statistical" by people in Profiles.
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Zhang Z, Fang H, Wang H. Multiple Imputation based Clustering Validation (MIV) for Big Longitudinal Trial Data with Missing Values in eHealth. J Med Syst. 2016 Jun; 40(6):146.
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Allison JJ, Nguyen HL, Ha DA, Chiriboga G, Ly HN, Tran HT, Phan NT, Vu NC, Kim M, Goldberg RJ. Culturally adaptive storytelling method to improve hypertension control in Vietnam - "We talk about our hypertension": study protocol for a feasibility cluster-randomized controlled trial. Trials. 2016 Jan 14; 17:26.
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Mayo-Wilson E, Hutfless S, Li T, Gresham G, Fusco N, Ehmsen J, Heyward J, Vedula S, Lock D, Haythornthwaite J, Payne JL, Cowley T, Tolbert E, Rosman L, Twose C, Stuart EA, Hong H, Doshi P, Suarez-Cuervo C, Singh S, Dickersin K. Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review. Syst Rev. 2015 Nov 02; 4:143.
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Gavett BE, Ashendorf L, Gurnani AS. Reliable Change on Neuropsychological Tests in the Uniform Data Set. J Int Neuropsychol Soc. 2015 Aug; 21(7):558-67.
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Hoaglin DC. We know less than we should about methods of meta-analysis. Res Synth Methods. 2015 Sep; 6(3):287-9.
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Hoaglin DC. Letter to the Editor on Cohen et al. (Letter commenting on: J Clin Epidemiol. 2015;68:299-306). J Clin Epidemiol. 2016 Jan; 69:261-2.
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Mu X, Kon M, Ergin A, Remiszewski S, Akalin A, Thompson CM, Diem M. Statistical analysis of a lung cancer spectral histopathology (SHP) data set. Analyst. 2015 Apr 7; 140(7):2449-64.
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Lajoie BR, Dekker J, Kaplan N. The Hitchhiker's guide to Hi-C analysis: practical guidelines. Methods. 2015 Jan 15; 72:65-75.
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Turner RM, Kwok CS, Chen-Turner C, Maduakor CA, Singh S, Loke YK. Thiazolidinediones and associated risk of bladder cancer: a systematic review and meta-analysis. Br J Clin Pharmacol. 2014 Aug; 78(2):258-73.
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Glickman ME, Rao SR, Schultz MR. False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. J Clin Epidemiol. 2014 Aug; 67(8):850-7.
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