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Alternative data treatment principles for categorical ADL data.

Iwarsson, Susanne LU and Lanke, Jan LU (2004) In International Journal of Rehabilitation Research 27(3). p.195-201
Abstract
Scaling methodology represents a problem in assessments of activities of daily living (ADL) and little is known about how the results of these assessments are affected by data treatment principles and statistical methods. The aims of this paper are to: (i) describe alternative ways of transforming a response pattern on ADL into a single number; and (ii) to present and compare different ways of analysing both changes in ADL capacity from one occasion to another and also differences in ADL between one group and another. Three datasets based on assessments with the ADL Staircase were used. Four different data treatment principles were described and the development of a novel principle to transform response patterns into ranks was put forward.... (More)
Scaling methodology represents a problem in assessments of activities of daily living (ADL) and little is known about how the results of these assessments are affected by data treatment principles and statistical methods. The aims of this paper are to: (i) describe alternative ways of transforming a response pattern on ADL into a single number; and (ii) to present and compare different ways of analysing both changes in ADL capacity from one occasion to another and also differences in ADL between one group and another. Three datasets based on assessments with the ADL Staircase were used. Four different data treatment principles were described and the development of a novel principle to transform response patterns into ranks was put forward. Thereafter, different paired-data cases and two-sample cases were analysed, using different statistical standard methods to explore possible variations in results. The results demonstrated a few marked differences among P values, no matter which data treatment principle or statistical method was used. That is, different principles and methods yield similar results in terms of P values, although there are important differences as regards selection bias. Principles and methods respecting the ordinal character of ADL data encourage the use of non-parametric methods and the novel rank principle presented here is a useful alternative. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
International Journal of Rehabilitation Research
volume
27
issue
3
pages
195 - 201
publisher
Lippincott Williams & Wilkins
external identifiers
  • pmid:15319689
  • wos:000224163900004
ISSN
1473-5660
language
English
LU publication?
yes
id
55009a82-596a-4af7-b53c-2ce634901c2f (old id 126601)
alternative location
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=15319689&dopt=Abstract
date added to LUP
2007-07-24 08:47:10
date last changed
2016-04-15 20:47:18
@article{55009a82-596a-4af7-b53c-2ce634901c2f,
  abstract     = {Scaling methodology represents a problem in assessments of activities of daily living (ADL) and little is known about how the results of these assessments are affected by data treatment principles and statistical methods. The aims of this paper are to: (i) describe alternative ways of transforming a response pattern on ADL into a single number; and (ii) to present and compare different ways of analysing both changes in ADL capacity from one occasion to another and also differences in ADL between one group and another. Three datasets based on assessments with the ADL Staircase were used. Four different data treatment principles were described and the development of a novel principle to transform response patterns into ranks was put forward. Thereafter, different paired-data cases and two-sample cases were analysed, using different statistical standard methods to explore possible variations in results. The results demonstrated a few marked differences among P values, no matter which data treatment principle or statistical method was used. That is, different principles and methods yield similar results in terms of P values, although there are important differences as regards selection bias. Principles and methods respecting the ordinal character of ADL data encourage the use of non-parametric methods and the novel rank principle presented here is a useful alternative.},
  author       = {Iwarsson, Susanne and Lanke, Jan},
  issn         = {1473-5660},
  language     = {eng},
  number       = {3},
  pages        = {195--201},
  publisher    = {Lippincott Williams & Wilkins},
  series       = {International Journal of Rehabilitation Research},
  title        = {Alternative data treatment principles for categorical ADL data.},
  volume       = {27},
  year         = {2004},
}