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Heckman-type selection models to obtain unbiased estimates with missing measures outcome: theoretical considerations and an application to missing birth weight data

Overview of attention for article published in BMC Medical Research Methodology, December 2019
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Mentioned by

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2 X users

Citations

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25 Dimensions

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83 Mendeley
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Title
Heckman-type selection models to obtain unbiased estimates with missing measures outcome: theoretical considerations and an application to missing birth weight data
Published in
BMC Medical Research Methodology, December 2019
DOI 10.1186/s12874-019-0840-7
Pubmed ID
Authors

Siaka Koné, Bassirou Bonfoh, Daouda Dao, Inza Koné, Günther Fink

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 83 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 17%
Student > Master 11 13%
Researcher 6 7%
Student > Doctoral Student 5 6%
Student > Bachelor 5 6%
Other 19 23%
Unknown 23 28%
Readers by discipline Count As %
Economics, Econometrics and Finance 13 16%
Medicine and Dentistry 9 11%
Social Sciences 9 11%
Psychology 4 5%
Nursing and Health Professions 3 4%
Other 17 20%
Unknown 28 34%
Attention Score in Context

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 02 November 2020.
All research outputs
#13,681,342
of 23,211,181 outputs
Outputs from BMC Medical Research Methodology
#1,308
of 2,049 outputs
Outputs of similar age
#223,900
of 459,226 outputs
Outputs of similar age from BMC Medical Research Methodology
#33
of 44 outputs
Altmetric has tracked 23,211,181 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,049 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 33rd percentile – i.e., 33% 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 459,226 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.