Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
1997-5-14
pubmed:abstractText
Single-subject designs measure one individual's responses to some experimental manipulation. Statistical methods exist for validly estimating the effect of an intervention on a specific individual by using data from a single-subject design. However, without strong assumptions regarding how an intervention on one individual relates to its effects on others, the results from a single-subject design provide little useful information on the general utility of the intervention. Examination of a single subject cannot verify these assumptions. Correct analysis of data from such designs allows for the possibility of correlation among the observations and the modeling of any changes over time not related to an intervention effect. When data from single-subject designs are collected, the role of assumptions in both the analysis and the generality of conclusions must be frankly acknowledged. Research often develops in stages and the single-subject design can be useful in early stages for hypothesis generation.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0195-9131
pubmed:author
pubmed:issnType
Print
pubmed:volume
28
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
639-44
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
Statistical considerations in the use and analysis of single-subject designs.
pubmed:affiliation
Department of Public Health Services, Bowman Gray School of Medicine, Winston-Salem NC 27157, USA.
pubmed:publicationType
Journal Article