| Title |
Longevity and concentration in survival times: the log-scale-location family of failure time models
|
|---|---|
| Published in |
Lifetime Data Analysis, February 2016
|
| DOI | 10.1007/s10985-016-9356-1 |
| Pubmed ID | |
| Authors | |
| Abstract |
Evidence suggests that the increasing life expectancy levels at birth witnessed over the past centuries are associated with a decreasing concentration of the survival times. The purpose of this work is to study the relationships that exist between longevity and concentration measures for some regression models for the evolution of survival. In particular, we study a family of survival models that can be used to capture the observed trends in longevity and concentration over time. The parametric family of log-scale-location models is shown to allow for modeling different trends of expected value and concentration of survival times. An extension towards mixture models is also described in order to take into account scenarios where a fraction of the population experiences short term survival. Some results are also presented for such framework. The use of both the log-scale-location family and the mixture model is illustrated through an application to period life tables from the Human Mortality Database. |
Login to access the Attention Digest and the Sentiment Analysis related to this output.
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 3 | 27% |
| Germany | 3 | 27% |
| France | 1 | 9% |
| South Africa | 1 | 9% |
| Spain | 1 | 9% |
| United Kingdom | 1 | 9% |
| Unknown | 1 | 9% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 73% |
| Scientists | 3 | 27% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 18% |
| Student > Master | 2 | 18% |
| Student > Doctoral Student | 1 | 9% |
| Student > Bachelor | 1 | 9% |
| Professor | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 3 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Mathematics | 1 | 9% |
| Business, Management and Accounting | 1 | 9% |
| Agricultural and Biological Sciences | 1 | 9% |
| Economics, Econometrics and Finance | 1 | 9% |
| Other | 2 | 18% |
| Unknown | 4 | 36% |