Sensitivity Analysis for Observational Studies with Recurrent Events

Jeffrey Zhang () and Dylan S. Small
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Jeffrey Zhang: The Wharton School, University of Pennsylvania, Academic Research Building
Dylan S. Small: The Wharton School, University of Pennsylvania, Academic Research Building

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2024, vol. 30, issue 1, No 9, 237-261

Abstract: 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.

Keywords: Calibration; Sensitivity analysis; Sickle-cell trait (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10985-023-09607-6

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