| pubmed-article:17495575 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:17495575 | lifeskim:mentions | umls-concept:C1457887 | lld:lifeskim |
| pubmed-article:17495575 | lifeskim:mentions | umls-concept:C0040223 | lld:lifeskim |
| pubmed-article:17495575 | lifeskim:mentions | umls-concept:C0234621 | lld:lifeskim |
| pubmed-article:17495575 | lifeskim:mentions | umls-concept:C0449851 | lld:lifeskim |
| pubmed-article:17495575 | lifeskim:mentions | umls-concept:C0936012 | lld:lifeskim |
| pubmed-article:17495575 | pubmed:issue | 3 | lld:pubmed |
| pubmed-article:17495575 | pubmed:dateCreated | 2007-5-14 | lld:pubmed |
| pubmed-article:17495575 | pubmed:abstractText | Research to address clinical symptoms and the way they change over time in an individual is of paramount importance to healthcare researchers who are interested in improving the quality of life for ill patients. However, typical statistical methods that rely on means can obscure individual trajectories of change. Visual graphical analysis (VGA) is a technique that can provide researchers with an alternative method of quantitative statistical analysis that is more sensitive to individual change and variation. | lld:pubmed |
| pubmed-article:17495575 | pubmed:language | eng | lld:pubmed |
| pubmed-article:17495575 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:17495575 | pubmed:citationSubset | AIM | lld:pubmed |
| pubmed-article:17495575 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:17495575 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:17495575 | pubmed:issn | 0029-6562 | lld:pubmed |
| pubmed-article:17495575 | pubmed:author | pubmed-author:BrownCarlton... | lld:pubmed |
| pubmed-article:17495575 | pubmed:author | pubmed-author:BeckSusan LSL | lld:pubmed |
| pubmed-article:17495575 | pubmed:author | pubmed-author:McGuireDebora... | lld:pubmed |
| pubmed-article:17495575 | pubmed:author | pubmed-author:PetersonDougl... | lld:pubmed |
| pubmed-article:17495575 | pubmed:author | pubmed-author:MooneyKathlee... | lld:pubmed |
| pubmed-article:17495575 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:17495575 | pubmed:volume | 56 | lld:pubmed |
| pubmed-article:17495575 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:17495575 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:17495575 | pubmed:pagination | 195-201 | lld:pubmed |
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| pubmed-article:17495575 | pubmed:meshHeading | pubmed-meshheading:17495575... | lld:pubmed |
| pubmed-article:17495575 | pubmed:articleTitle | Visual graphical analysis: a technique to investigate symptom trajectories over time. | lld:pubmed |
| pubmed-article:17495575 | pubmed:affiliation | carl@carltonbrown.org | lld:pubmed |
| pubmed-article:17495575 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:17495575 | pubmed:publicationType | Validation Studies | lld:pubmed |
| http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:17495575 | lld:pubmed |
