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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The existence of standard-biased mortality ratios due to death certificate misclassification - a simulation study based on a true story
|
|---|---|
| Published in |
BMC Medical Research Methodology, January 2016
|
| DOI | 10.1186/s12874-016-0112-8 |
| Pubmed ID | |
| Authors |
Andreas Deckert |
| Abstract |
Mortality statistics are used to compare health status of populations; optimally, they base on individual death certificates. However, determining cause of death is error-prone. E.g. cardiovascular disease (CVD) death determination is characterized by sensitivity (SE) and specificity (SP) lower than 85 %. Furthermore, differential misclassification may be present in case of homogenous target populations. We investigate the bias of standardized mortality ratios (SMR), based on real-world data. CVD mortality of 6378 ethnic German repatriates was assessed and the SMR calculated. Non-differential age-dependent misclassification was introduced into data by scenarios of equal SE and SP in a range of 0.7 to 0.85. The bias between originally reported and actual SMR was calculated for each pair of values. Additionally, four differential misclassification scenarios were simulated, reflecting two extreme scenarios of both quality criteria varied in the cohort but fixed to either higher or lower in the reference, and two scenarios of crossed criteria values. In case of non-differential misclassification the bias is always towards the null-hypothesis. The lowest bias was 13.5 % (SE, SP = 0.85 constantly), the maximum bias was 40 % (SP = 0.7). However, in case of differential misclassification the observed SMR can be on the wrong track. If SP is high but SE low in the cohort, negative bias up to -10 % can occur. In case SE is low but SP is high in the reference, the bias remains always positive. In the opposite case plus SP is high in the cohort, the bias can reach -30 %. SMR values are always biased due to the diagnostic test character of death determination. In majority of epidemiological studies the bias should be towards the null-hypothesis (non-differential misclassification). However, caution is needed in case of differential misclassification, possibly experienced in studies on homogenous subgroups, and in large prospective cohorts with specifically trained personnel. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Members of the public | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 17% |
| Lecturer | 2 | 8% |
| Professor > Associate Professor | 2 | 8% |
| Student > Master | 2 | 8% |
| Student > Ph. D. Student | 2 | 8% |
| Other | 3 | 13% |
| Unknown | 9 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 25% |
| Nursing and Health Professions | 4 | 17% |
| Mathematics | 3 | 13% |
| Immunology and Microbiology | 1 | 4% |
| Unknown | 10 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 March 2023.
All research outputs
#14,401,201
of 23,532,144 outputs
Outputs from BMC Medical Research Methodology
#1,396
of 2,076 outputs
Outputs of similar age
#204,360
of 398,382 outputs
Outputs of similar age from BMC Medical Research Methodology
#18
of 27 outputs
Altmetric has tracked 23,532,144 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,076 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 398,382 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.