A Monte Carlo method to estimate the confidence intervals for the concentration index using aggregated population register data.

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dc.contributor University of Helsinki, Department of Social Research en
dc.contributor.author Lumme, Sonja
dc.contributor.author Sund, Reijo Tapani
dc.contributor.author Leyland, Alastair H
dc.contributor.author Keskimäki, Ilmo
dc.date.accessioned 2017-07-24T09:20:00Z
dc.date.available 2017-07-24T09:20:00Z
dc.date.issued 2015-02-18
dc.identifier.citation Lumme , S , Sund , R T , Leyland , A H & Keskimäki , I 2015 , ' A Monte Carlo method to estimate the confidence intervals for the concentration index using aggregated population register data. ' Health services & outcomes research methodology , vol. 15 , no. 2 , pp. 82-98 . DOI: 10.1007/s10742-015-0137-1 en
dc.identifier.issn 1387-3741
dc.identifier.other PURE: 57894748
dc.identifier.other PURE UUID: 129f46a9-57e5-4cfe-8d93-d499e9f8ae57
dc.identifier.other Scopus: 84939956765
dc.identifier.uri http://hdl.handle.net/10138/203382
dc.description.abstract In this paper, we introduce several statistical methods to evaluate the uncertainty in the concentration index (C) for measuring socioeconomic equality in health and health care using aggregated total population register data. The C is a widely used index when measuring socioeconomic inequality, but previous studies have mainly focused on developing statistical inference for sampled data from population surveys. While data from large population-based or national registers provide complete coverage, registration comprises several sources of error. We simulate confidence intervals for the C with different Monte Carlo approaches, which take into account the nature of the population data. As an empirical example, we have an extensive dataset from the Finnish cause-of-death register on mortality amenable to health care interventions between 1996 and 2008. Amenable mortality has been often used as a tool to capture the effectiveness of health care. Thus, inequality in amenable mortality provides evidence on weaknesses in health care performance between socioeconomic groups. Our study shows using several approaches with different parametric assumptions that previously introduced methods to estimate the uncertainty of the C for sampled data are too conservative for aggregated population register data. Consequently, we recommend that inequality indices based on the register data should be presented together with an approximation of the uncertainty and suggest using a simulation approach we propose. The approach can also be adapted to other measures of equality in health. fi
dc.language.iso eng
dc.relation.ispartof Health services & outcomes research methodology
dc.rights en
dc.subject 112 Statistics and probability en
dc.title A Monte Carlo method to estimate the confidence intervals for the concentration index using aggregated population register data. en
dc.type Article
dc.description.version Peer reviewed
dc.identifier.doi https://doi.org/10.1007/s10742-015-0137-1
dc.type.uri info:eu-repo/semantics/other
dc.type.uri info:eu-repo/semantics/publishedVersion
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