| Title |
Reducing and meta-analysing estimates from distributed lag non-linear models
|
|---|---|
| Published in |
BMC Medical Research Methodology, January 2013
|
| DOI | 10.1186/1471-2288-13-1 |
| Pubmed ID | |
| Authors |
Antonio Gasparrini, Ben Armstrong |
| Abstract |
The two-stage time series design represents a powerful analytical tool in environmental epidemiology. Recently, models for both stages have been extended with the development of distributed lag non-linear models (DLNMs), a methodology for investigating simultaneously non-linear and lagged relationships, and multivariate meta-analysis, a methodology to pool estimates of multi-parameter associations. However, the application of both methods in two-stage analyses is prevented by the high-dimensional definition of DLNMs. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 165 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Canada | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 162 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 31 | 19% |
| Student > Ph. D. Student | 28 | 17% |
| Researcher | 23 | 14% |
| Student > Bachelor | 8 | 5% |
| Student > Postgraduate | 7 | 4% |
| Other | 19 | 12% |
| Unknown | 49 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 28 | 17% |
| Environmental Science | 27 | 16% |
| Mathematics | 9 | 5% |
| Computer Science | 8 | 5% |
| Earth and Planetary Sciences | 8 | 5% |
| Other | 27 | 16% |
| Unknown | 58 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 31 May 2022.
All research outputs
#3,047,802
of 22,691,736 outputs
Outputs from BMC Medical Research Methodology
#472
of 2,001 outputs
Outputs of similar age
#32,984
of 282,271 outputs
Outputs of similar age from BMC Medical Research Methodology
#5
of 28 outputs
Altmetric has tracked 22,691,736 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
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We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.