We propose a likelihood ratio test to assess that sampling has been completed in closed population size estimation studies. More precisely, we assess if the expected number of subjects that have never been sampled is below a user-specified threshold. The likelihood ratio test statistic has a nonstandard distribution under the null hypothesis. Critical values can be easily approximated and tabulated, and they do not depend on model specification. We illustrate in a simulation study and three real data examples, one of which involves ascertainment bias of amyotrophic lateral sclerosis in Gulf War veterans.

Farcomeni, A. (2023). A likelihood ratio test for completed sampling in population size estimation studies. BIOMETRICAL JOURNAL, 65(2) [10.1002/bimj.202200129].

A likelihood ratio test for completed sampling in population size estimation studies

Farcomeni, Alessio
2023-02-01

Abstract

We propose a likelihood ratio test to assess that sampling has been completed in closed population size estimation studies. More precisely, we assess if the expected number of subjects that have never been sampled is below a user-specified threshold. The likelihood ratio test statistic has a nonstandard distribution under the null hypothesis. Critical values can be easily approximated and tabulated, and they do not depend on model specification. We illustrate in a simulation study and three real data examples, one of which involves ascertainment bias of amyotrophic lateral sclerosis in Gulf War veterans.
feb-2023
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore SECS-S/01 - STATISTICA
English
ascertainment bias
capture-recapture
chi-bar squared
constrained optimization
Farcomeni, A. (2023). A likelihood ratio test for completed sampling in population size estimation studies. BIOMETRICAL JOURNAL, 65(2) [10.1002/bimj.202200129].
Farcomeni, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/315318
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