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Study of coverage of confidence intervals for the standardized mortality ratio in studies with missing death certificates
Author(s) -
Timkova Jana,
Kotik Lukas,
Tomasek Ladislav
Publication year - 2017
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.7432
Subject(s) - confidence interval , standardized mortality ratio , statistics , medicine , population , coverage probability , cdf based nonparametric confidence interval , robust confidence intervals , demography , mathematics , environmental health , sociology
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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