Literature DB >> 17618311

Statistics in pharmacology.

D Spina1.   

Abstract

Statistics is an important tool in pharmacological research that is used to summarize (descriptive statistics) experimental data in terms of central tendency (mean or median) and variance (standard deviation, standard error of the mean, confidence interval or range) but more importantly it enables us to conduct hypothesis testing. This is of particular importance when attempting to determine whether the pharmacological effect of one drug is superior to another which clearly has implications for drug development and getting that next paper published in a respectable journal! Therefore, it is essential for pharmacologists to have an understanding of the uses and abuses of statistics. With this in mind, the British Journal of Pharmacology has commissioned a number of review articles to highlight the uses of statistics in experimental design and analysis.

Mesh:

Year:  2007        PMID: 17618311      PMCID: PMC2042957          DOI: 10.1038/sj.bjp.0707371

Source DB:  PubMed          Journal:  Br J Pharmacol        ISSN: 0007-1188            Impact factor:   8.739


  7 in total

Review 1.  An introduction to analysis of variance (ANOVA) with special reference to data from clinical experiments in optometry.

Authors:  R A Armstrong; S V Slade; F Eperjesi
Journal:  Ophthalmic Physiol Opt       Date:  2000-05       Impact factor: 3.117

2.  Principles: the need for better experimental design.

Authors:  Michael F W Festing
Journal:  Trends Pharmacol Sci       Date:  2003-07       Impact factor: 14.819

3.  Analysis of serial measurements in medical research.

Authors:  J N Matthews; D G Altman; M J Campbell; P Royston
Journal:  BMJ       Date:  1990-01-27

4.  Good statistical practice in pharmacology. Problem 1.

Authors:  M Lew
Journal:  Br J Pharmacol       Date:  2007-07-09       Impact factor: 8.739

5.  Good statistical practice in pharmacology. Problem 2.

Authors:  M Lew
Journal:  Br J Pharmacol       Date:  2007-07-09       Impact factor: 8.739

Review 6.  Comparison of treatment effects between animal experiments and clinical trials: systematic review.

Authors:  Pablo Perel; Ian Roberts; Emily Sena; Philipa Wheble; Catherine Briscoe; Peter Sandercock; Malcolm Macleod; Luciano E Mignini; Pradeep Jayaram; Khalid S Khan
Journal:  BMJ       Date:  2006-12-15

7.  Some statistical methods useful in circulation research.

Authors:  S Wallenstein; C L Zucker; J L Fleiss
Journal:  Circ Res       Date:  1980-07       Impact factor: 17.367

  7 in total
  1 in total

1.  Quality of reporting statistics in two Indian pharmacology journals.

Authors:  Preeti Yadav
Journal:  J Pharmacol Pharmacother       Date:  2011-04
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.