| Title |
A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer
|
|---|---|
| Published in |
BMC Medical Research Methodology, October 2013
|
| DOI | 10.1186/1471-2288-13-129 |
| Pubmed ID | |
| Authors |
David I Hastie, Silvia Liverani, Lamiae Azizi, Sylvia Richardson, Isabelle Stücker |
| Abstract |
A common characteristic of environmental epidemiology is the multi-dimensional aspect of exposure patterns, frequently reduced to a cumulative exposure for simplicity of analysis. By adopting a flexible Bayesian clustering approach, we explore the risk function linking exposure history to disease. This approach is applied here to study the relationship between different smoking characteristics and lung cancer in the framework of a population based case control study. |
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 % |
|---|---|---|
| Unknown | 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 7 | 26% |
| Student > Ph. D. Student | 4 | 15% |
| Student > Master | 4 | 15% |
| Researcher | 3 | 11% |
| Professor | 2 | 7% |
| Other | 4 | 15% |
| Unknown | 3 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 11% |
| Psychology | 3 | 11% |
| Computer Science | 3 | 11% |
| Agricultural and Biological Sciences | 3 | 11% |
| Engineering | 2 | 7% |
| Other | 7 | 26% |
| Unknown | 6 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 27 November 2013.
All research outputs
#20,710,927
of 23,310,485 outputs
Outputs from BMC Medical Research Methodology
#1,919
of 2,057 outputs
Outputs of similar age
#186,435
of 213,472 outputs
Outputs of similar age from BMC Medical Research Methodology
#31
of 31 outputs
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