DOUBLY ROBUST INFERENCE WITH MISSING DATA IN SURVEY SAMPLING

Cited 19 time in webofscience Cited 0 time in scopus
  • Hit : 217
  • Download : 0
Statistical inference with missing data requires assumptions about the population or about the response probability. Doubly robust (DR) estimators use both relationships to estimate the parameters of interest, so that they are consistent even when one of the models is misspecified. In this paper, we propose a method of computing propensity scores that leads to DR estimation. In addition, we discuss DR variance estimation so that the resulting inference is doubly robust. Some asymptotic properties are discussed. Results from two limited simulation studies are also presented
Publisher
STATISTICA SINICA
Issue Date
2014-01
Language
English
Article Type
Article
Keywords

HOT DECK IMPUTATION; RESPONSE PROBABILITY; VARIANCE-ESTIMATION; INCOMPLETE DATA; NONRESPONSE; MODELS; ADJUST

Citation

STATISTICA SINICA, v.24, no.1, pp.375 - 394

ISSN
1017-0405
DOI
10.5705/ss.2012.005
URI
http://hdl.handle.net/10203/212999
Appears in Collection
MA-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 19 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0