↓ Skip to main content

On the robustness of N-mixture models

Overview of attention for article published in Ecology, June 2018
Altmetric Badge

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 (87th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

28 tweeters


42 Dimensions

Readers on

126 Mendeley
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.
On the robustness of N-mixture models
Published in
Ecology, June 2018
DOI 10.1002/ecy.2362
Pubmed ID

William A. Link, Matthew R. Schofield, Richard J. Barker, John R. Sauer


N-mixture models provide an appealing alternative to mark-recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the N-mixture models: inference is very sensitive to the model's assumptions. We consider the effects of three violations of assumptions which might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness-of-fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities. This article is protected by copyright. All rights reserved.

Twitter Demographics

The data shown below were collected from the profiles of 28 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 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 126 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 21%
Student > Ph. D. Student 26 21%
Student > Master 22 17%
Student > Doctoral Student 9 7%
Other 8 6%
Other 19 15%
Unknown 15 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 61 48%
Environmental Science 32 25%
Mathematics 4 3%
Engineering 2 2%
Biochemistry, Genetics and Molecular Biology 1 <1%
Other 8 6%
Unknown 18 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 07 November 2019.
All research outputs
of 18,520,433 outputs
Outputs from Ecology
of 6,276 outputs
Outputs of similar age
of 287,892 outputs
Outputs of similar age from Ecology
of 95 outputs
Altmetric has tracked 18,520,433 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,276 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done well, scoring higher than 87% 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 287,892 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.