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Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance

Overview of attention for article published in BMC Medical Research Methodology, April 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)

Mentioned by

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11 tweeters

Citations

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104 Dimensions

Readers on

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102 Mendeley
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Title
Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance
Published in
BMC Medical Research Methodology, April 2017
DOI 10.1186/s12874-017-0338-0
Pubmed ID
Authors

Tri-Long Nguyen, Gary S. Collins, Jessica Spence, Jean-Pierre Daurès, P. J. Devereaux, Paul Landais, Yannick Le Manach

Abstract

Double-adjustment can be used to remove confounding if imbalance exists after propensity score (PS) matching. However, it is not always possible to include all covariates in adjustment. We aimed to find the optimal imbalance threshold for entering covariates into regression. We conducted a series of Monte Carlo simulations on virtual populations of 5,000 subjects. We performed PS 1:1 nearest-neighbor matching on each sample. We calculated standardized mean differences across groups to detect any remaining imbalance in the matched samples. We examined 25 thresholds (from 0.01 to 0.25, stepwise 0.01) for considering residual imbalance. The treatment effect was estimated using logistic regression that contained only those covariates considered to be unbalanced by these thresholds. We showed that regression adjustment could dramatically remove residual confounding bias when it included all of the covariates with a standardized difference greater than 0.10. The additional benefit was negligible when we also adjusted for covariates with less imbalance. We found that the mean squared error of the estimates was minimized under the same conditions. If covariate balance is not achieved, we recommend reiterating PS modeling until standardized differences below 0.10 are achieved on most covariates. In case of remaining imbalance, a double adjustment might be worth considering.

Twitter Demographics

The data shown below were collected from the profiles of 11 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 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 <1%
Unknown 101 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 22%
Researcher 18 18%
Student > Master 11 11%
Professor > Associate Professor 8 8%
Student > Doctoral Student 7 7%
Other 20 20%
Unknown 16 16%
Readers by discipline Count As %
Medicine and Dentistry 37 36%
Social Sciences 8 8%
Economics, Econometrics and Finance 8 8%
Agricultural and Biological Sciences 5 5%
Mathematics 4 4%
Other 15 15%
Unknown 25 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 17 September 2021.
All research outputs
#3,677,601
of 19,157,212 outputs
Outputs from BMC Medical Research Methodology
#620
of 1,728 outputs
Outputs of similar age
#70,147
of 277,798 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 19,157,212 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,728 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has gotten more attention than average, scoring higher than 64% of its peers.
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