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Interval Estimates of Event Probability from Pairwise Correlated Data: Application in Epidemiology of Birth Defects
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SYSNO ASEP 0522798 Druh ASEP A - Abstrakt Zařazení RIV Záznam nebyl označen do RIV Zařazení RIV Není vybrán druh dokumentu Název Interval Estimates of Event Probability from Pairwise Correlated Data: Application in Epidemiology of Birth Defects Tvůrce(i) Klaschka, Jan (UIVT-O) RID, SAI, ORCID
Malý, Marek (UIVT-O) RID, SAI
Šípek, A. (CZ)Zdroj.dok. CFE-CMStatistics 2019: Book of Abstracts. - London : Ecosta Econometrics and Statistics, 2019 - ISBN 978-9963-2227-8-0
S. 143-143Poč.str. 1 s. Forma vydání Tištěná - P Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Institucionální podpora UIVT-O - RVO:67985807 Anotace Interval estimates of event probability are studied within a generalization of Bernoulli trials model: n = 2m zero-one-valued variables consist of m pairs with correlation phi between the two components. Independence between the m pairs and a common expectation theta of all n variables are assumed. The primary motivation and the main application field is in the epidemiology of congenital anomalies (birth defects) in twins. Occurrence of birth defects in both twins is known to be more frequent than under independence. Ignoring the fact and applying the binomial model would lead to over-liberal inferences. The focus is on the computation of exact interval estimates of theta - so far for fixed phi. Numerical procedures have been designed for the calculation of confidence bounds of Clopper-Pearson, Sterne and Blaker types. The key building block is the calculation of the probability mass function (pmf) of the number of events. Several pmf calculation methods have been tested. Among them, the numerical inversion (via iFFT) of the characteristic function appears to be the most computationally effective. A quasi-symbolic calculation based on the pmf representation as a matrix of polynomial coefficients is competitive under some (but not all) settings. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2020
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