Linked Life Data

14770056

Source:http://linkedlifedata.com/resource/pubmed/id/14770056

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2004-2-10
pubmed:abstractText
Estimates of effects of antipsychotic medication on hospitalization risk based on nonexperimental data may be affected by selection bias from either observable or unobservable factors. This study applies a statistical method, using instrumental variables, that controls for both types of possible selection bias. We use data from a large observational study of people under treatment for schizophrenia to estimate models of drug choice and hospitalization, including atypical (versus typical) medication effects on 12-month hospitalization risk. Results for younger patients (<age 45 years) indicate that unobservable factors bias the atypical effect estimate in a positive direction; correcting for this bias yields a significant negative effect on hospitalization risk. With data for older patients, our instrumental variables performed poorly and provided little information about possible selection bias. Obtaining detailed information on treatment history and other determinants of medication choice in future studies is critical for deriving more accurate estimates of medication effects from nonexperimental data.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0022-3018
pubmed:author
pubmed:issnType
Print
pubmed:volume
192
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
119-28
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Estimation of antipsychotic effects on hospitalization risk in a naturalistic study with selection on unobservables.
pubmed:affiliation
Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't