Semiparametric estimation for inverse density weighted expectations when responses are missing at random

Semiparametric estimation for inverse density weighted expectations when responses are missing at random

When responses are missing at random, we consider semiparametric estimation of inverse density weighted expectations, or equivalently, integrals of conditional expectations. An inverse probability weighted estimator and a full propensity score weighted estimator are proposed and shown to be asymptot...

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Main Authors: Lu, Xuewen, Lian, Heng, Liu, Wanrong
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2013
Subjects:
DRNTU::Science::Mathematics::Statistics
Online Access:https://hdl.handle.net/10356/99040
http://hdl.handle.net/10220/17092
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-990402020-03-07T12:34:45Z Semiparametric estimation for inverse density weighted expectations when responses are missing at random Lu, Xuewen Lian, Heng Liu, Wanrong School of Physical and Mathematical Sciences DRNTU::Science::Mathematics::Statistics When responses are missing at random, we consider semiparametric estimation of inverse density weighted expectations, or equivalently, integrals of conditional expectations. An inverse probability weighted estimator and a full propensity score weighted estimator are proposed and shown to be asymptotically normal. The two estimators are asymptotically equivalent and achieve the semiparametric efficiency bound. The performances of the estimators are investigated and compared with simulation studies and a real data example. 2013-10-31T01:35:34Z 2019-12-06T20:02:36Z 2013-10-31T01:35:34Z 2019-12-06T20:02:36Z 2012 2012 Journal Article Lu, X., Lian, H., & Liu, W. (2012). Semiparametric estimation for inverse density weighted expectations when responses are missing at random. Journal of nonparametric statistics, 24(1), 139-152. https://hdl.handle.net/10356/99040 http://hdl.handle.net/10220/17092 10.1080/10485252.2011.599385 en Journal of nonparametric statistics
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Science::Mathematics::Statistics
spellingShingle DRNTU::Science::Mathematics::Statistics
Lu, Xuewen
Lian, Heng
Liu, Wanrong
Semiparametric estimation for inverse density weighted expectations when responses are missing at random
description When responses are missing at random, we consider semiparametric estimation of inverse density weighted expectations, or equivalently, integrals of conditional expectations. An inverse probability weighted estimator and a full propensity score weighted estimator are proposed and shown to be asymptotically normal. The two estimators are asymptotically equivalent and achieve the semiparametric efficiency bound. The performances of the estimators are investigated and compared with simulation studies and a real data example.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Lu, Xuewen
Lian, Heng
Liu, Wanrong
format Article
author Lu, Xuewen
Lian, Heng
Liu, Wanrong
author_sort Lu, Xuewen
title Semiparametric estimation for inverse density weighted expectations when responses are missing at random
title_short Semiparametric estimation for inverse density weighted expectations when responses are missing at random
title_full Semiparametric estimation for inverse density weighted expectations when responses are missing at random
title_fullStr Semiparametric estimation for inverse density weighted expectations when responses are missing at random
title_full_unstemmed Semiparametric estimation for inverse density weighted expectations when responses are missing at random
title_sort semiparametric estimation for inverse density weighted expectations when responses are missing at random
publishDate 2013
url https://hdl.handle.net/10356/99040
http://hdl.handle.net/10220/17092
_version_ 1681039636524171264

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