Linked Life Data

11027937

Source:http://linkedlifedata.com/resource/pubmed/id/11027937

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
2000-11-9
pubmed:abstractText
This article demonstrates the use of two approaches to analyzing the relationship of multiple covariates to an outcome which has a high proportion of zero values. One approach is to categorize the continuous outcome (including the zero category) and then fit a proportional odds model. Another approach is to use logistic regression to model the probability of a zero response and ordinary least squares linear regression to model the non-zero continuous responses. The use of these two approaches was demonstrated using outcomes data on hours of care received from the Springfield Elder Project. A crude linear model including both zero and non-zero values was also used for comparison. We conclude that the choice of approaches for analysis depends on the data. If the proportional odds assumption is valid, then it appears to be the method of choice; otherwise, the combination of logistic regression and a linear model is preferable.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0895-4356
pubmed:author
pubmed:issnType
Print
pubmed:volume
53
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1036-43
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Analyzing data with clumping at zero. An example demonstration.
pubmed:affiliation
New England Research Institutes, Watertown, MA 01730, USA. bhchang@bu.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.