Linked Life Data

12034014

Source:http://linkedlifedata.com/resource/pubmed/id/12034014

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
Pt 1
pubmed:dateCreated
2002-5-29
pubmed:abstractText
This paper examines the implications of the correlational structure of repeated measurements for three indices of change that can be used to evaluate treatment effects in longitudinal studies with scheduled assessment times and fixed total duration. The generalized least squares (GLS) regression of repeated measurements on time, which is usually reserved for complex mixed model solutions, takes the correlational structure of the repeated measurements into account, whereas simple gain scores and ordinary least squares (OLS) regression calculations do not. Nevertheless, the GLS solution is equivalent to OLS under conditions of compound symmetry and is equivalent to the analysis of simple gain scores in the presence of an autoregressive (order 1) correlational structure. The understanding of these relationships is important with regard to the frequently heard criticisms of the simpler definitions of treatment response in repeated measurement designs.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0007-1102
pubmed:author
pubmed:issnType
Print
pubmed:volume
55
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
109-24
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Measuring change in controlled longitudinal studies.
pubmed:affiliation
Department of Psychiatry and Behavioral Sciences, University of Texas, Health Science Center at Houston, 77225, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.