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Lifetime Data Analysis
Erschienen in:

12.08.2023

Sensitivity Analysis for Observational Studies with Recurrent Events

verfasst von: Jeffrey Zhang, Dylan S. Small

Erschienen in: Lifetime Data Analysis | Ausgabe 1/2024

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Abstract

We conduct an observational study of the effect of sickle cell trait Haemoglobin AS (HbAS) on the hazard rate of malaria fevers in children. Assuming no unmeasured confounding, there is strong evidence that HbAS reduces the rate of malarial fevers. Since this is an observational study, however, the no unmeasured confounding assumption is strong. A sensitivity analysis considers how robust a conclusion is to a potential unmeasured confounder. We propose a new sensitivity analysis method for recurrent event data and apply it to the malaria study. We find that for the causal conclusion that HbAS is protective against malarial fevers to be overturned, the hypothesized unmeasured confounder must be as influential as all but one of the measured confounders.
Vorheriger Artikel Causal survival analysis under competing risks using longitudinal modified treatment policies
Nächster Artikel Assessing model prediction performance for the expected cumulative number of recurrent events

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Metadaten
Titel
Sensitivity Analysis for Observational Studies with Recurrent Events
verfasst von
Jeffrey Zhang
Dylan S. Small
Publikationsdatum
12.08.2023
Verlag
Springer US
Erschienen in
Lifetime Data Analysis / Ausgabe 1/2024
Print ISSN: 1380-7870
Elektronische ISSN: 1572-9249
DOI
https://doi.org/10.1007/s10985-023-09607-6

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