↓ Skip to main content

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes

Overview of attention for article published in BMC Medical Research Methodology, May 2011
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
99 Dimensions

Readers on

mendeley
280 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes
Published in
BMC Medical Research Methodology, May 2011
DOI 10.1186/1471-2288-11-77
Pubmed ID
Authors

Baoyue Li, Hester F Lingsma, Ewout W Steyerberg, Emmanuel Lesaffre

Abstract

Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models.

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 280 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 4%
Netherlands 5 2%
Germany 2 <1%
Switzerland 2 <1%
Turkey 2 <1%
United Kingdom 2 <1%
Malaysia 1 <1%
Kenya 1 <1%
Brazil 1 <1%
Other 9 3%
Unknown 245 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 60 21%
Student > Ph. D. Student 54 19%
Student > Master 26 9%
Student > Doctoral Student 16 6%
Professor > Associate Professor 16 6%
Other 61 22%
Unknown 47 17%
Readers by discipline Count As %
Medicine and Dentistry 48 17%
Agricultural and Biological Sciences 38 14%
Social Sciences 36 13%
Mathematics 14 5%
Psychology 11 4%
Other 71 25%
Unknown 62 22%
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 26 May 2012.
All research outputs
#17,634,903
of 22,665,794 outputs
Outputs from BMC Medical Research Methodology
#1,665
of 2,000 outputs
Outputs of similar age
#94,396
of 111,930 outputs
Outputs of similar age from BMC Medical Research Methodology
#22
of 24 outputs
Altmetric has tracked 22,665,794 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 2,000 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 111,930 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.