Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/52448
Campo DC Valoridioma
dc.contributor.authorHaro, Josep Maria
dc.contributor.authorKontodimas, Stathis
dc.contributor.authorNegrin, Miguel Angel
dc.contributor.authorRatcliffe, Mark
dc.contributor.authorSuarez, David
dc.contributor.authorWindmeijer, Frank
dc.date.accessioned2018-11-25T20:25:34Z-
dc.date.available2018-11-25T20:25:34Z-
dc.date.issued2006
dc.identifier.issn1175-5652
dc.identifier.urihttp://hdl.handle.net/10553/52448-
dc.description.abstractProspective observational studies, which provide information on the effectiveness of interventions in natural settings, may complement results from randomised clinical trials in the evaluation of health technologies. However, observational studies are subject to a number of potential methodological weaknesses, mainly selection and observer bias. This paper reviews and applies various methods to control for selection bias in the estimation of treatment effects and proposes novel ways to assess the presence of observer bias. We also address the issues of estimation and inference in a multilevel setting. We describe and compare the useof regression methods, propensity score matching, fixed-effects models incorporating investigator characteristics, and a multilevel, hierarchical model using Bayesian estimation techniques in the control of selection bias. We also propose to assess the existence of observer bias in observational studies by comparing patient-and investigator-reported outcomes. To illustrate these methods, we have used data from the SOHO (Schizophrenia Outpatient Health Outcomes) study, a large, prospective, observational study of health outcomes associated with the treatment of schizophrenia.The methods used to adjust for differences between treatment groups that could cause selection bias yielded comparable results, reinforcing the validity of the findings. Also, the assessment of observer bias did not show that it existed in the SOHO study. Observational studies, when properly conducted and when using adequate statistical methods, can provide valid information on the evaluation of health technologies.
dc.publisher1175-5652
dc.relation.ispartofApplied Health Economics and Health Policy
dc.sourceApplied Health Economics and Health Policy[ISSN 1175-5652],v. 5, p. 11-25
dc.titleMethodological aspects in the assessment of treatment effects in observational health outcomes studies
dc.typeinfo:eu-repo/semantics/reviewes
dc.typeArticlees
dc.identifier.doi10.2165/00148365-200605010-00003
dc.identifier.scopus33745240376
dc.identifier.isi000211355000003
dc.contributor.authorscopusid34569951400
dc.contributor.authorscopusid13005990600
dc.contributor.authorscopusid9249657200
dc.contributor.authorscopusid57197600045
dc.contributor.authorscopusid57200085207
dc.contributor.authorscopusid6603071771
dc.description.lastpage25
dc.description.firstpage11
dc.relation.volume5
dc.type2Reseñaes
dc.contributor.daisngid29616887
dc.contributor.daisngid1776032
dc.contributor.daisngid1285254
dc.contributor.daisngid114155
dc.contributor.daisngid27782460
dc.contributor.daisngid635353
dc.contributor.wosstandardWOS:Haro, JM
dc.contributor.wosstandardWOS:Kontodimas, S
dc.contributor.wosstandardWOS:Negrin, MA
dc.contributor.wosstandardWOS:Ratcliffe, M
dc.contributor.wosstandardWOS:Suarez, D
dc.contributor.wosstandardWOS:Windmeijer, F
dc.date.coverdateJunio 2006
dc.identifier.ulpgces
dc.description.scieSCIE
dc.description.ssciSSCI
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR TIDES- Técnicas estadísticas bayesianas y de decisión en la economía y empresa-
crisitem.author.deptIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.orcid0000-0002-7074-6268-
crisitem.author.parentorgIU de Turismo y Desarrollo Económico Sostenible-
crisitem.author.fullNameNegrín Hernández, Miguel Ángel-
Colección:Reseña
Vista resumida

Citas SCOPUSTM   

40
actualizado el 24-mar-2024

Citas de WEB OF SCIENCETM
Citations

35
actualizado el 25-feb-2024

Visitas

44
actualizado el 16-mar-2024

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.