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Invited Commentary: Harnessing Housing Natural Experiments Is Important, but Beware Differential Misclassification of Difference in Difference

Overview of attention for article published in American Journal of Epidemiology, September 2016
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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 (87th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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1 news outlet
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1 Facebook page

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29 Mendeley
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Article details
Title
Invited Commentary: Harnessing Housing Natural Experiments Is Important, but Beware Differential Misclassification of Difference in Difference
Published in
American Journal of Epidemiology, September 2016
DOI 10.1093/aje/kww053
Pubmed ID
Authors
Abstract

In this issue of the Journal, Reeves et al. (Am J Epidemiol 2016;184(6):421-429) present the findings of a natural experiment analyzing the association between reduced housing affordability and mental ill health. Their difference-in-difference analysis of cross-sectional, quarterly population health surveys administered before and after implementation of a policy to reduce Housing Benefit payments in the United Kingdom in April 2011 represents an important way to assess the impact of a national housing policy shift on public health. It is a well-conducted study harnessing a natural experiment and adds to the weight of evidence supporting an association between housing costs and mental health. However, quantitative bias analysis based on the reported findings suggests that a small amount of differential (by unblinded Housing Benefit status) misclassification bias in the outcome may be enough to explain the observed association. Our analysis of possible misclassification bias in the outcome used in the study highlights the need for caution when a difference-in-difference estimate is small, the population is not blinded to its postintervention exposure status, and the outcome measure is subjective and prone to differential (by unblinded exposure or treatment status) misclassification.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 7 24%
Researcher 4 14%
Student > Doctoral Student 2 7%
Student > Bachelor 2 7%
Librarian 1 3%
Other 5 17%
Unknown 8 28%
Readers by discipline
Readers by discipline Count As %
Social Sciences 9 31%
Medicine and Dentistry 4 14%
Nursing and Health Professions 2 7%
Psychology 2 7%
Environmental Science 1 3%
Other 1 3%
Unknown 10 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 20 January 2020.
All research outputs
#2,209,999
of 22,886,568 outputs
Outputs from American Journal of Epidemiology
#1,525
of 9,056 outputs
Outputs of similar age
#40,646
of 332,538 outputs
Outputs of similar age from American Journal of Epidemiology
#12
of 42 outputs
Altmetric has tracked 22,886,568 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,056 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.9. This one has done well, scoring higher than 83% 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 332,538 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 42 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 71% of its contemporaries.