 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 UAMS Profiles 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 |
|---|
| 2022 | 0 | 1 | 1 | | 2021 | 2 | 1 | 3 | | 2020 | 2 | 0 | 2 | | 2019 | 2 | 1 | 3 | | 2018 | 3 | 3 | 6 | | 2017 | 1 | 2 | 3 | | 2016 | 1 | 3 | 4 | | 2015 | 3 | 1 | 4 | | 2014 | 2 | 4 | 6 | | 2013 | 1 | 8 | 9 | | 2012 | 0 | 5 | 5 | | 2011 | 0 | 7 | 7 | | 2010 | 3 | 6 | 9 | | 2009 | 1 | 6 | 7 | | 2008 | 1 | 7 | 8 | | 2007 | 4 | 8 | 12 | | 2006 | 1 | 11 | 12 | | 2005 | 1 | 5 | 6 | | 2004 | 1 | 7 | 8 | | 2003 | 3 | 4 | 7 | | 2002 | 0 | 2 | 2 | | 2001 | 1 | 3 | 4 | | 2000 | 3 | 1 | 4 | | 1998 | 1 | 0 | 1 | | 1997 | 1 | 0 | 1 | | 1995 | 0 | 2 | 2 | | 1994 | 0 | 1 | 1 | | 1991 | 0 | 1 | 1 | | 1990 | 0 | 2 | 2 |
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Below are the most recent publications written about "Data Interpretation, Statistical" by people in Profiles over the past ten years.
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Chusyd DE, Austad SN, Brown AW, Chen X, Dickinson SL, Ejima K, Fluharty D, Golzarri-Arroyo L, Holden R, Jamshidi-Naeini Y, Landsittel D, Lartey S, Mannix E, Vorland CJ, Allison DB. From Model Organisms to Humans, the Opportunity for More Rigor in Methodologic and Statistical Analysis, Design, and Interpretation of Aging and Senescence Research. J Gerontol A Biol Sci Med Sci. 2022 11 21; 77(11):2155-2164.
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Wan F, Colditz GA, Sutcliffe S. Matched Versus Unmatched Analysis of Matched Case-Control Studies. Am J Epidemiol. 2021 09 01; 190(9):1859-1866.
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Kroeger CM, Ejima K, Hannon BA, Halliday TM, McComb B, Teran-Garcia M, Dawson JA, King DB, Brown AW, Allison DB. Persistent confusion in nutrition and obesity research about the validity of classic nonparametric tests in the presence of heteroscedasticity: evidence of the problem and valid alternatives. Am J Clin Nutr. 2021 03 11; 113(3):517-524.
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Raphael KL, Inamdar S, McKinley MJ, Martinez N, Cavaliere K, Kahn A, Leggett CL, Iyer P, Wang KK, Trindade AJ. Longitudinal and Circumferential Distributions of Dysplasia and Early Neoplasia in Barrett's Esophagus: A Pooled Analysis of Three Prospective Studies. Clin Transl Gastroenterol. 2021 02 22; 12(2):e00311.
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Lioutas VA, Beiser AS, Aparicio HJ, Himali JJ, Selim MH, Romero JR, Seshadri S. Assessment of Incidence and Risk Factors of Intracerebral Hemorrhage Among Participants in the Framingham Heart Study Between 1948 and 2016. JAMA Neurol. 2020 10 01; 77(10):1252-1260.
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Ejima K, Brown AW, Smith DL, Beyaztas U, Allison DB. Murine genetic models of obesity: type I error rates and the power of commonly used analyses as assessed by plasmode-based simulation. Int J Obes (Lond). 2020 06; 44(6):1440-1449.
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Motoi H, Jeong JW, Juhász C, Miyakoshi M, Nakai Y, Sugiura A, Luat AF, Sood S, Asano E. Quantitative analysis of intracranial electrocorticography signals using the concept of statistical parametric mapping. Sci Rep. 2019 11 22; 9(1):17385.
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Zhou Z, Lunetta KL, Smith AK, Wolf EJ, Stone A, Schichman SA, McGlinchey RE, Milberg WP, Miller MW, Logue MW. Correction for multiple testing in candidate-gene methylation studies. Epigenomics. 2019 07; 11(9):1089-1105.
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Cataldo AM, Cohen AL. The comparison process as an account of variation in the attraction, compromise, and similarity effects. Psychon Bull Rev. 2019 Jun; 26(3):934-942.
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Wan F. A note on a naive regression-based test on the validity of an instrumental variable. Stat Med. 2018 12 10; 37(28):4330-4333.
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An G, Schmidt RL, Mock DM, Veng-Pedersen P, Widness JA. Overlooked Issues on Pharmacokinetics Data Interpretation of Protein Drugs-a Case Example of Erythropoietin. AAPS J. 2018 11 26; 21(1):6.
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Wan F. Matched or unmatched analyses with propensity-score-matched data? Stat Med. 2019 01 30; 38(2):289-300.
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Wan F. Analyzing pre-post randomized studies with one post-randomization score using repeated measures and ANCOVA models. Stat Methods Med Res. 2019 Oct-Nov; 28(10-11):2952-2974.
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Wan F, Small D, Mitra N. A general approach to evaluating the bias of 2-stage instrumental variable estimators. Stat Med. 2018 05 30; 37(12):1997-2015.
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Piccolo BD, Wankhade UD, Chintapalli SV, Bhattacharyya S, Chunqiao L, Shankar K. Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing data. Bioinformatics. 2018 03 15; 34(6):1050-1052.
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Zolotarev KV, Nakhod KV, Mikhailov AN, Mikhailova MV. Correlation between LC50 for Adult Fish and Fish Embryos. Bull Exp Biol Med. 2017 Oct; 163(6):749-752.
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Howsmon DP, Kruger U, Melnyk S, James SJ, Hahn J. Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation. PLoS Comput Biol. 2017 03; 13(3):e1005385.
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Cunningham WA, Koscik TR. Balancing Type I and Type II error concerns in fMRI through compartmentalized analysis. Cogn Neurosci. 2017 07; 8(3):147-149.
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Vargason T, Howsmon DP, Melnyk S, James SJ, Hahn J. Mathematical modeling of the methionine cycle and transsulfuration pathway in individuals with autism spectrum disorder. J Theor Biol. 2017 03 07; 416:28-37.
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Shrestha RP, Horowitz J, Hollot CV, Germain MJ, Widness JA, Mock DM, Veng-Pedersen P, Chait Y. Models for the red blood cell lifespan. J Pharmacokinet Pharmacodyn. 2016 06; 43(3):259-74.
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George BJ, Beasley TM, Brown AW, Dawson J, Dimova R, Divers J, Goldsby TU, Heo M, Kaiser KA, Keith SW, Kim MY, Li P, Mehta T, Oakes JM, Skinner A, Stuart E, Allison DB. Common scientific and statistical errors in obesity research. Obesity (Silver Spring). 2016 Apr; 24(4):781-90.
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Han B, Kott PS, Hughes A, McKeon R, Blanco C, Compton WM. Estimating the rates of deaths by suicide among adults who attempt suicide in the United States. J Psychiatr Res. 2016 Jun; 77:125-33.
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La Rosa PS, Brooks TL, Deych E, Shands B, Prior F, Larson-Prior LJ, Shannon WD. Gibbs distribution for statistical analysis of graphical data with a sample application to fcMRI brain images. Stat Med. 2016 Feb 20; 35(4):566-80.
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Chen CH, Hsu CL, Huang SH, Chen SY, Hung YL, Chen HR, Wu YC, Su LJ, Lee HC. Method designed to respect molecular heterogeneity can profoundly correct present data interpretations for genome-wide expression analysis. PLoS One. 2015; 10(3):e0121154.
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Stein CK, Qu P, Epstein J, Buros A, Rosenthal A, Crowley J, Morgan G, Barlogie B. Removing batch effects from purified plasma cell gene expression microarrays with modified ComBat. BMC Bioinformatics. 2015 Feb 25; 16:63.
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Miaskowski C, Dunn L, Ritchie C, Paul SM, Cooper B, Aouizerat BE, Alexander K, Skerman H, Yates P. Latent Class Analysis Reveals Distinct Subgroups of Patients Based on Symptom Occurrence and Demographic and Clinical Characteristics. J Pain Symptom Manage. 2015 Jul; 50(1):28-37.
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Saddiki H, McAuliffe J, Flaherty P. GLAD: a mixed-membership model for heterogeneous tumor subtype classification. Bioinformatics. 2015 Jan 15; 31(2):225-32.
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Pookhao N, Sohn MB, Li Q, Jenkins I, Du R, Jiang H, An L. A two-stage statistical procedure for feature selection and comparison in functional analysis of metagenomes. Bioinformatics. 2015 Jan 15; 31(2):158-65.
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Kertai MD, White WD, Gan TJ. Cumulative duration of "triple low" state of low blood pressure, low bispectral index, and low minimum alveolar concentration of volatile anesthesia is not associated with increased mortality. Anesthesiology. 2014 Jul; 121(1):18-28.
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Hansen RA, Zeng P, Ryan P, Gao J, Sonawane K, Teeter B, Westrich K, Dubois RW. Exploration of heterogeneity in distributed research network drug safety analyses. Res Synth Methods. 2014 Dec; 5(4):352-70.
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Raja R, Sinha N. Adaptive k-space sampling design for edge-enhanced DCE-MRI using compressed sensing. Magn Reson Imaging. 2014 Sep; 32(7):899-912.
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Ruff IM, Ali SF, Goldstein JN, Lev M, Copen WA, McIntyre J, Rost NS, Schwamm LH. Improving door-to-needle times: a single center validation of the target stroke hypothesis. Stroke. 2014 Feb; 45(2):504-8.
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Sheffer CE, Mennemeier MS, Landes RD, Dornhoffer J, Kimbrell T, Bickel WK, Brackman S, Chelette KC, Brown G, Vuong M. Focal electrical stimulation as an effective sham control for active rTMS and biofeedback treatments. Appl Psychophysiol Biofeedback. 2013 Sep; 38(3):171-6.
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Meyer AC, Neugebauer NM, Zheng G, Crooks PA, Dwoskin LP, Bardo MT. Effects of VMAT2 inhibitors lobeline and GZ-793A on methamphetamine-induced changes in dopamine release, metabolism and synthesis in vivo. J Neurochem. 2013 Oct; 127(2):187-98.
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Horton DB, Nickell JR, Zheng G, Crooks PA, Dwoskin LP. GZ-793A, a lobelane analog, interacts with the vesicular monoamine transporter-2 to inhibit the effect of methamphetamine. J Neurochem. 2013 Oct; 127(2):177-86.
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Beck P, Mahaffey S, Urbano FJ, Garcia-Rill E. Role of G-proteins in the effects of leptin on pedunculopontine nucleus neurons. J Neurochem. 2013 Sep; 126(6):705-14.
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Topchiy E, Panzhinskiy E, Griffin WS, Barger SW, Das M, Zawada WM. Nox4-generated superoxide drives angiotensin II-induced neural stem cell proliferation. Dev Neurosci. 2013; 35(4):293-305.
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Garcia TP, Müller S, Carroll RJ, Dunn TN, Thomas AP, Adams SH, Pillai SD, Walzem RL. Structured variable selection with q-values. Biostatistics. 2013 Sep; 14(4):695-707.
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Väremo L, Nielsen J, Nookaew I. Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods. Nucleic Acids Res. 2013 Apr; 41(8):4378-91.
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Tripathi S, Glazko GV, Emmert-Streib F. Ensuring the statistical soundness of competitive gene set approaches: gene filtering and genome-scale coverage are essential. Nucleic Acids Res. 2013 Apr; 41(7):e82.
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