Study of coverage of confidence intervals for the standardized mortality ratio in studies with missing death certificates
Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic
Typ dokumentu časopisecké články
PubMed
28815680
DOI
10.1002/sim.7432
Knihovny.cz E-zdroje
- Klíčová slova
- aggregation, confidence intervals, coverage, missing certificates, profile likelihood, simulation study, standardized mortality ratio, uranium miners,
- MeSH
- interval spolehlivosti * MeSH
- lidé MeSH
- mortalita * MeSH
- nádory plic mortalita MeSH
- nemoci z povolání mortalita MeSH
- pravděpodobnost MeSH
- rizikové faktory MeSH
- statistické modely MeSH
- úmrtní listy * MeSH
- uran MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Česká republika epidemiologie MeSH
- Francie epidemiologie MeSH
- Názvy látek
- uran MeSH
This paper assesses the coverage probability of commonly used confidence intervals for the standardized mortality ratio (SMR) when death certificates are missing. It also proposes alternative confidence interval approaches with coverage probabilities close to .95. In epidemiology, the SMR is an important measure of risk of disease mortality (or incidence) to compare a specific group to a reference population. The appropriate confidence interval for the SMR is crucial, especially when the SMR is close to 1.0 and the statistical significance of the risk needs to be determined. There are several ways to calculate confidence intervals, depending on a study characteristics (ie, studies with small number of deaths, studies with small counts, aggregate SMRs based on several countries or time periods, and studies with missing death certificates). This paper summarizes the most commonly used confidence intervals and newly applies several existing approaches not previously used for SMR confidence intervals. The coverage probability and length of the different confidence intervals are assessed using a simulation study and different scenarios. The performance of the confidence intervals for the lung cancer SMR and all other cancer SMR is also assessed using the dataset of French and Czech uranium miners. Finally, the most appropriate confidence intervals to use under different study scenarios are recommended.
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