Misreported longitudinal data in epidemiology: review of mixture-based advances and current challenges
Visualitza/Obre
Cita com:
hdl:2117/363432
Tipus de documentArticle
Data publicació2021-12
Condicions d'accésAccés obert
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Reconeixement-NoComercial 3.0 Espanya
Abstract
The problem of dealing with misreported data is very common in a wide range of contexts and for different reasons. This has been and still is an important issue for data analysts and statisticians as not accounting for it could led to biased estimates and conclusions, and in many cases that would have implications in a posterior decision making process, as we all have seen in the current worldwide Covid-19 pandemic. In the last few years, many approaches have been proposed in the literature to accomodate data presenting this issue, especially in the fields of epidemiology and public health but also in other areas as social science. In this work, a comprehensive review of the recently proposed methods based on mixture models for longitudinal data (correlated and uncorrelated) is presented and several examples of application are discussed, including several approaches to the burden of Covid-19 infection cases in Spain and different approaches to deal with underreported registries of human papillomavirus infections and genital warts in Catalunya
CitacióMoriña, D. [et al.]. Misreported longitudinal data in epidemiology: review of mixture-based advances and current challenges. "Spanish Journal of Statistics", Desembre 2021, vol. 3, núm. 1, p. 37-44.
ISSN2695-9070
Versió de l'editorhttps://www.ine.es/art/sjs/sjs_2021_01_03.pdf
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