Literature DB >> 28740691

How to describe univariate data.

Stefania Canova1, Diego Luigi Cortinovis1, Federico Ambrogi2.   

Abstract

Univariate analysis has the purpose to describe a single variable distribution in one sample. It is the first important step of every clinical trial. In this short review, we focus on this analysis, the methods that authors should use to report this type of data, information that they should not miss and mistakes that they must avoid.

Keywords:  Univariate; graph; survival; variable

Year:  2017        PMID： 28740691      PMCID： PMC5506131          DOI： 10.21037/jtd.2017.05.80

Source DB:  PubMed          Journal:  J Thorac Dis        ISSN： 2072-1439            Impact factor:   2.895


  3 in total

1.  Analysis by categorizing or dichotomizing continuous variables is inadvisable: an example from the natural history of unruptured aneurysms.

Authors:  O Naggara; J Raymond; F Guilbert; D Roy; A Weill; D G Altman
Journal:  AJNR Am J Neuroradiol       Date:  2011-02-17       Impact factor: 3.825

2.  Presentation of numerical data.

Authors:  D G Altman; J M Bland
Journal:  BMJ       Date:  1996-03-02

Review 3.  Review of survival analyses published in cancer journals.

Authors:  D G Altman; B L De Stavola; S B Love; K A Stepniewska
Journal:  Br J Cancer       Date:  1995-08       Impact factor: 7.640
  3 in total
  1 in total

1.  Willingness of the Jordanian Population to Receive a COVID-19 Booster Dose: A Cross-Sectional Study.

Authors:  Walid Al-Qerem; Abdel Qader Al Bawab; Alaa Hammad; Jonathan Ling; Fawaz Alasmari
Journal:  Vaccines (Basel)       Date:  2022-03-09
  1 in total

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