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Repeated measurements, bilateral observations and pseudoreplicates, why does it matter?

Ranstam, Jonas LU (2012) In Osteoarthritis and Cartilage 20(6). p.473-475
Abstract
A common requirement of statistical methods, critical to the interpretation of the data, is that the analyzed observations are independent. This is not always the case in experiments and clinical studies, a mistake which can be expected to lead to erroneous study results. The phenomenon is explained, its consequences described, and suggestions to avoid the problems presented.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Osteoarthritis and Cartilage
volume
20
issue
6
pages
473 - 475
publisher
Elsevier
external identifiers
  • wos:000304733900003
  • pmid:22406008
  • scopus:84860509953
ISSN
1063-4584
DOI
10.1016/j.joca.2012.02.011
language
English
LU publication?
yes
id
b6226ef8-081d-40c3-a190-35a8b027e23a (old id 2431967)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/22406008?dopt=Abstract
date added to LUP
2012-04-03 10:08:35
date last changed
2017-03-05 04:17:52
@article{b6226ef8-081d-40c3-a190-35a8b027e23a,
  abstract     = {A common requirement of statistical methods, critical to the interpretation of the data, is that the analyzed observations are independent. This is not always the case in experiments and clinical studies, a mistake which can be expected to lead to erroneous study results. The phenomenon is explained, its consequences described, and suggestions to avoid the problems presented.},
  author       = {Ranstam, Jonas},
  issn         = {1063-4584},
  language     = {eng},
  number       = {6},
  pages        = {473--475},
  publisher    = {Elsevier},
  series       = {Osteoarthritis and Cartilage},
  title        = {Repeated measurements, bilateral observations and pseudoreplicates, why does it matter?},
  url          = {http://dx.doi.org/10.1016/j.joca.2012.02.011},
  volume       = {20},
  year         = {2012},
}