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Modeling approaches for cost and cos...

Li, Jiaqi.

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Modeling approaches for cost and cost-effectiveness estimation using observational data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modeling approaches for cost and cost-effectiveness estimation using observational data./
Author:	Li, Jiaqi.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
Description:	83 p.
Notes:	Source: Dissertations Abstracts International, Volume: 78-02, Section: B.
Contained By:	Dissertations Abstracts International78-02B.
Subject:	Biostatistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10134946
ISBN:	9781339928791

Modeling approaches for cost and cost-effectiveness estimation using observational data.
Li, Jiaqi.

Modeling approaches for cost and cost-effectiveness estimation using observational data. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 83 p.

Source: Dissertations Abstracts International, Volume: 78-02, Section: B.

Thesis (Ph.D.)--University of Pennsylvania, 2016.

This item must not be sold to any third party vendors.

The estimation of treatment effects on medical costs and cost effectiveness measures is complicated by the need to account for non-independent censoring, skewness and the effects of confounders. In this dissertation, we develop several cost and cost-effectiveness tools that account for these issues. Since medical costs are often collected from observational claims data, we investigate propensity score methods such as covariate adjustment, stratification, inverse probability weighting and doubly robust weighting. We also propose several doubly robust estimators for common cost effectiveness measures. Lastly, we explore the role of big data tools and machine learning algorithms in cost estimation. We show how these modern techniques can be applied to big data manipulation, cost prediction and dimension reduction.

ISBN: 9781339928791Subjects--Topical Terms:

1002712
Biostatistics.

Modeling approaches for cost and cost-effectiveness estimation using observational data.
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245 1 0 $a Modeling approaches for cost and cost-effectiveness estimation using observational data.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2016
300 $a 83 p.
500 $a Source: Dissertations Abstracts International, Volume: 78-02, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Mitra, Nandita.
502 $a Thesis (Ph.D.)--University of Pennsylvania, 2016.
506 $a This item must not be sold to any third party vendors.
520 $a The estimation of treatment effects on medical costs and cost effectiveness measures is complicated by the need to account for non-independent censoring, skewness and the effects of confounders. In this dissertation, we develop several cost and cost-effectiveness tools that account for these issues. Since medical costs are often collected from observational claims data, we investigate propensity score methods such as covariate adjustment, stratification, inverse probability weighting and doubly robust weighting. We also propose several doubly robust estimators for common cost effectiveness measures. Lastly, we explore the role of big data tools and machine learning algorithms in cost estimation. We show how these modern techniques can be applied to big data manipulation, cost prediction and dimension reduction.
590 $a School code: 0175.
650 4 $a Biostatistics. $3 1002712
650 4 $a Health care management. $3 2122906
690 $a 0308
690 $a 0769
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773 0 $t Dissertations Abstracts International $g 78-02B.
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791 $a Ph.D.
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793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10134946