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Estimating the standardized incidence ratio (SIR) with incomplete follow-up data

Overview of attention for article published in BMC Medical Research Methodology, April 2017
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Title
Estimating the standardized incidence ratio (SIR) with incomplete follow-up data
Published in
BMC Medical Research Methodology, April 2017
DOI 10.1186/s12874-017-0335-3
Pubmed ID
Authors

Heiko Becher, Volker Winkler

Abstract

A standard parameter to compare the disease incidence of a cohort relative to the population is the standardized incidence ratio (SIR). For statistical inference is commonly assumed that the denominator, the expected number of cases, is fixed. If a disease registry is available, incident cases can sometimes be identified by linkage with the registry, however, registries may not contain information on migration or death from other causes. A complete follow-up with a population registry may not be possible. In that case, end-of-follow-up date and therefore, exact person-years of observation are unknown. We have developed a method to estimate the observation times and to derive the expected number of cases using population data on mortality and migration rates. We investigate the impact of the underlying assumptions with a sensitivity analysis. The method provides a useful estimate of the SIR. We illustrate the method with a numerical example, a simulation study and with a study on standardized cancer incidence ratios in a cohort of migrants relative to the German population. We show that the additional variance induced by the estimation method is small, so that standard methods for inference can be applied. Estimation of the observation time is possible for cohort studies with incomplete follow-up.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 16%
Student > Master 5 16%
Student > Postgraduate 4 13%
Student > Bachelor 4 13%
Researcher 4 13%
Other 5 16%
Unknown 4 13%
Readers by discipline Count As %
Medicine and Dentistry 10 32%
Nursing and Health Professions 4 13%
Biochemistry, Genetics and Molecular Biology 2 6%
Agricultural and Biological Sciences 2 6%
Computer Science 1 3%
Other 4 13%
Unknown 8 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 April 2017.
All research outputs
#8,450,310
of 9,689,121 outputs
Outputs from BMC Medical Research Methodology
#862
of 940 outputs
Outputs of similar age
#221,172
of 263,538 outputs
Outputs of similar age from BMC Medical Research Methodology
#30
of 32 outputs
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