ArticleScientific reports2021
New statistical model for misreported data with application to current public health challenges.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Knowledge and awareness regarding human papillomavirus and its association with oropharyngeal cancer among the general population in Makkah, Saudi Arabia: a cross-sectional study.Frontiers in oncology · 2026Article
- Estimated Covid-19 burden in Spain: ARCH underreported non-stationary time series.BMC medical research methodology · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The main goal of this work is to present a new model able to deal with potentially misreported continuous time series. The proposed model is able to handle the autocorrelation structure in continuous time series data, which might be partially or totally underreported or overreported. Its performance is illustrated through a comprehensive simulation study considering several autocorrelation structures and three real data applications on human papillomavirus incidence in Girona (Catalonia, Spain) and Covid-19 incidence in two regions with very different circumstances: the early days of the epidemic in the Chinese region of Heilongjiang and the most current data from Catalonia.
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Registered trials
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