| Title |
Using propensity scores in difference-in-differences models to estimate the effects of a policy change
|
|---|---|
| Published in |
Health Services and Outcomes Research Methodology, August 2014
|
| DOI | 10.1007/s10742-014-0123-z |
| Pubmed ID | |
| Authors |
Elizabeth A. Stuart, Haiden A. Huskamp, Kenneth Duckworth, Jeffrey Simmons, Zirui Song, Michael E. Chernew, Colleen L. Barry |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 36% |
| Germany | 1 | 9% |
| France | 1 | 9% |
| Norway | 1 | 9% |
| Italy | 1 | 9% |
| Unknown | 3 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 55% |
| Scientists | 3 | 27% |
| Practitioners (doctors, other healthcare professionals) | 1 | 9% |
| Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 526 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | <1% |
| United Kingdom | 2 | <1% |
| Spain | 1 | <1% |
| Nicaragua | 1 | <1% |
| Unknown | 519 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 130 | 25% |
| Researcher | 63 | 12% |
| Student > Master | 62 | 12% |
| Student > Doctoral Student | 39 | 7% |
| Professor > Associate Professor | 18 | 3% |
| Other | 72 | 14% |
| Unknown | 142 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 120 | 23% |
| Social Sciences | 71 | 13% |
| Medicine and Dentistry | 47 | 9% |
| Business, Management and Accounting | 34 | 6% |
| Nursing and Health Professions | 13 | 2% |
| Other | 64 | 12% |
| Unknown | 177 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 36. 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 29 February 2024.
All research outputs
#1,129,154
of 25,604,262 outputs
Outputs from Health Services and Outcomes Research Methodology
#3
of 121 outputs
Outputs of similar age
#10,995
of 241,959 outputs
Outputs of similar age from Health Services and Outcomes Research Methodology
#2
of 4 outputs
Altmetric has tracked 25,604,262 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 121 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 98% 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 241,959 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 95% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.