Large Sample Theory of Empirical Distributions in Biased Sampling Models

Vardi (1985a) introduced an s-sample model for biased sampling, gave conditions which guarantee the existence and uniqueness of the nonparametric maximum likelihood estimator Gnof the common underlying distribution G and discussed numerical methods for calculating the estimator. Here we examine the...

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Veröffentlicht in:The Annals of Statistics. - Institute of Mathematical Statistics. - 16(1988), 3, Seite 1069-1112
1. Verfasser: Gill, Richard D. (VerfasserIn)
Weitere Verfasser: Vardi, Yehuda, Wellner, Jon A.
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 1988
Zugriff auf das übergeordnete Werk:The Annals of Statistics
Schlagworte:Asymptotic theory case-control studies choice based sampling empirical processes enriched stratified sampling graphs lenght-biased sampling Neyman allocation nonparametric maximum likelihood selection bias models mehr... stratified sampling Vardi's estimator Philosophy Mathematics
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520 |a Vardi (1985a) introduced an s-sample model for biased sampling, gave conditions which guarantee the existence and uniqueness of the nonparametric maximum likelihood estimator Gnof the common underlying distribution G and discussed numerical methods for calculating the estimator. Here we examine the large sample behavior of the NPMLE Gn, including results on uniform consistency of Gn, convergence of $\sqrt n (\mathbb{G}_n - G)$ to a Gaussian process and asymptotic efficiency of Gnas an estimator of G. The proofs are based upon recent results for empirical processes indexed by sets and functions and convexity arguments. We also give a careful proof of identifiability of the underlying distribution G under connectedness of a certain graph G. Examples and applications include length-biased sampling, stratified sampling, "enriched" stratified sampling, "choice-based" sampling in econometrics and "case-control" studies in biostatistics. A final section discusses design issues and further problems. 
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