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Modelling usage of medical care services: the medical expenditure panel survey data, 1996-2000

机译:医疗服务使用模型:医疗支出小组调查数据,1996-2000年

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摘要

We explore the determinants of usage of six different types of health care services, using the Medical Expenditure Panel Survey (MEPS) data, years 1996-2000. We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models. We find that the complexity of the model that is required to fit the data well depends upon the way in which the data is pooled across sexes and over time, and upon the characteristics of the usage measure. Pooling across time and sexes is almost always favoured, but when more heterogeneous data is pooled it is often the case that a more complex statistical model is required.View full textDownload full textRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/00036840903166202
机译:我们使用1996-2000年的医疗支出面板调查(MEPS)数据,探索了使用六种不同类型的医疗服务的决定因素。我们为单变量计数数据应用了许多模型,包括半参数,半非参数和有限混合模型。我们发现,很好地拟合数据所需的模型的复杂性取决于跨性别和随时间推移汇总数据的方式以及使用度量的特征。跨时间和性别的池几乎总是受到青睐,但是当池中收集更多异构数据时,通常会需要更复杂的统计模型。查看全文下载全文相关变量var addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线”,services_compact ::“ citeulike,netvibes,twitter,technorati,美味,linkedin,facebook,stumbleupon,digg,google,更多”,pubid:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/00036840903166202

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