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Nonparametric estimation for self-selected interval data collected through a two-stage approach

Angelov, Angel G. (author)
Umeå universitet,Statistik
Ekström, Magnus (author)
Umeå universitet,Statistik
 (creator_code:org_t)
2017-01-16
2017
English.
In: Metrika (Heidelberg). - : Springer. - 0026-1335 .- 1435-926X. ; 80:4, s. 377-399
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Self-selected interval data arise in questionnaire surveys when respondents are free to answer with any interval without having pre-specified ranges. This type of data is a special case of interval-censored data in which the assumption of noninformative censoring is violated, and thus the standard methods for interval-censored data (e.g. Turnbull's estimator) are not appropriate because they can produce biased results. Based on a certain sampling scheme, this paper suggests a nonparametric maximum likelihood estimator of the underlying distribution function. The consistency of the estimator is proven under general assumptions, and an iterative procedure for finding the estimate is proposed. The performance of the method is investigated in a simulation study.

Subject headings

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

Keyword

Informative interval censoring
Self-selected intervals
Nonparameric maximum likelihood estimation
Two-stage data collection
Questionnaire surveys
Statistics
statistik

Publication and Content Type

ref (subject category)
art (subject category)

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