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Auxiliary variables in multiple imputation in regression with missing X: a warning against including too many in small sample research

Overview of attention for article published in BMC Medical Research Methodology, December 2012
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1 X user

Citations

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124 Dimensions

Readers on

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163 Mendeley
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Title
Auxiliary variables in multiple imputation in regression with missing X: a warning against including too many in small sample research
Published in
BMC Medical Research Methodology, December 2012
DOI 10.1186/1471-2288-12-184
Pubmed ID
Authors

Jochen Hardt, Max Herke, Rainer Leonhart

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 1%
France 1 <1%
United Kingdom 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 157 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 22%
Researcher 22 13%
Student > Master 22 13%
Student > Doctoral Student 18 11%
Student > Bachelor 10 6%
Other 25 15%
Unknown 30 18%
Readers by discipline Count As %
Psychology 33 20%
Medicine and Dentistry 22 13%
Social Sciences 22 13%
Mathematics 14 9%
Nursing and Health Professions 5 3%
Other 27 17%
Unknown 40 25%
Attention Score in Context

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 16 February 2018.
All research outputs
#15,492,327
of 23,023,224 outputs
Outputs from BMC Medical Research Methodology
#1,521
of 2,030 outputs
Outputs of similar age
#181,074
of 279,369 outputs
Outputs of similar age from BMC Medical Research Methodology
#22
of 28 outputs
Altmetric has tracked 23,023,224 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,030 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 16th percentile – i.e., 16% 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 279,369 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.