| Title |
External validation of a Cox prognostic model: principles and methods
|
|---|---|
| Published in |
BMC Medical Research Methodology, March 2013
|
| DOI | 10.1186/1471-2288-13-33 |
| Pubmed ID | |
| Authors |
Patrick Royston, Douglas G Altman |
| Abstract |
A prognostic model should not enter clinical practice unless it has been demonstrated that it performs a useful role. External validation denotes evaluation of model performance in a sample independent of that used to develop the model. Unlike for logistic regression models, external validation of Cox models is sparsely treated in the literature. Successful validation of a model means achieving satisfactory discrimination and calibration (prediction accuracy) in the validation sample. Validating Cox models is not straightforward because event probabilities are estimated relative to an unspecified baseline function. |
X Demographics
The data shown below were collected from the profiles of 17 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 Kingdom | 3 | 18% |
| Netherlands | 2 | 12% |
| United States | 2 | 12% |
| Philippines | 1 | 6% |
| Sweden | 1 | 6% |
| Korea, Republic of | 1 | 6% |
| France | 1 | 6% |
| Unknown | 6 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 53% |
| Scientists | 5 | 29% |
| Practitioners (doctors, other healthcare professionals) | 3 | 18% |
Mendeley readers
The data shown below were compiled from readership statistics for 668 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | <1% |
| United Kingdom | 3 | <1% |
| Australia | 2 | <1% |
| Germany | 1 | <1% |
| Vietnam | 1 | <1% |
| Netherlands | 1 | <1% |
| Iceland | 1 | <1% |
| Canada | 1 | <1% |
| Japan | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 650 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 138 | 21% |
| Student > Ph. D. Student | 123 | 18% |
| Student > Master | 64 | 10% |
| Other | 54 | 8% |
| Student > Doctoral Student | 38 | 6% |
| Other | 117 | 18% |
| Unknown | 134 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 209 | 31% |
| Agricultural and Biological Sciences | 47 | 7% |
| Mathematics | 46 | 7% |
| Biochemistry, Genetics and Molecular Biology | 26 | 4% |
| Computer Science | 25 | 4% |
| Other | 128 | 19% |
| Unknown | 187 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 14 September 2022.
All research outputs
#1,532,172
of 26,017,215 outputs
Outputs from BMC Medical Research Methodology
#182
of 2,327 outputs
Outputs of similar age
#11,666
of 212,016 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 32 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,327 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done particularly well, scoring higher than 92% of its peers.
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We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.