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Principled missing data methods for researchers

Overview of attention for article published in SpringerPlus, May 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
1 blog
twitter
6 tweeters
facebook
1 Facebook page
googleplus
2 Google+ users
q&a
2 Q&A threads

Citations

dimensions_citation
907 Dimensions

Readers on

mendeley
1554 Mendeley
citeulike
3 CiteULike
Title
Principled missing data methods for researchers
Published in
SpringerPlus, May 2013
DOI 10.1186/2193-1801-2-222
Pubmed ID
Authors

Yiran Dong, Chao-Ying Joanne Peng

Abstract

The impact of missing data on quantitative research can be serious, leading to biased estimates of parameters, loss of information, decreased statistical power, increased standard errors, and weakened generalizability of findings. In this paper, we discussed and demonstrated three principled missing data methods: multiple imputation, full information maximum likelihood, and expectation-maximization algorithm, applied to a real-world data set. Results were contrasted with those obtained from the complete data set and from the listwise deletion method. The relative merits of each method are noted, along with common features they share. The paper concludes with an emphasis on the importance of statistical assumptions, and recommendations for researchers. Quality of research will be enhanced if (a) researchers explicitly acknowledge missing data problems and the conditions under which they occurred, (b) principled methods are employed to handle missing data, and (c) the appropriate treatment of missing data is incorporated into review standards of manuscripts submitted for publication.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters 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 1,554 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 3 <1%
Germany 3 <1%
United Kingdom 3 <1%
United States 2 <1%
Spain 2 <1%
Netherlands 1 <1%
Italy 1 <1%
Sweden 1 <1%
Peru 1 <1%
Other 5 <1%
Unknown 1532 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 403 26%
Student > Master 279 18%
Researcher 164 11%
Student > Doctoral Student 124 8%
Student > Bachelor 111 7%
Other 237 15%
Unknown 236 15%
Readers by discipline Count As %
Psychology 270 17%
Medicine and Dentistry 199 13%
Social Sciences 159 10%
Computer Science 86 6%
Engineering 77 5%
Other 428 28%
Unknown 335 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 27 October 2018.
All research outputs
#1,072,605
of 17,359,532 outputs
Outputs from SpringerPlus
#63
of 1,794 outputs
Outputs of similar age
#10,807
of 163,909 outputs
Outputs of similar age from SpringerPlus
#1
of 8 outputs
Altmetric has tracked 17,359,532 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,794 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 96% of its peers.
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 163,909 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them