[MARMAM] New publication - Flexible parametric modeling of survival from age at death data: A mixed linear regression framework (Etienne Rouby ; Vincent Ridoux ; Matthieu Authier)

Etienne Rouby etienne.rouby at univ-lr.fr
Thu Nov 5 03:31:27 PST 2020

Dear colleagues,

We are pleased to share our recent publication with

Rouby E, Ridoux V, and Authier M. (2020) Flexible parametric
modeling of survival from age at death data: A mixed linear regression
framework. Population Ecology. 2020;1-15 doi : 10.1002/1438-390X.12069

Abstract : 

Many long‐lived vertebrate species are under threat in
the Anthropocene, but their conservation is hampered by a lack of
demographic information to assess population long‐term viability. When
longitudinal studies (e.g., Capture‐Mark‐Recapture design) are not
feasible, the only available data may be cross‐sectional, for example,
stranding for marine mammals. Survival analysis deals with age at death
(i.e., time to event) data and allows to estimate survivorship and
hazard rates assuming that the cross‐sectional sample is representative.
Accommodating a bathtub‐shaped hazard, as expected in wild populations,
was historically difficult and required specific models. We identified a
simple linear regression model with individual frailty that can fit a
bathtub‐shaped hazard, take into account covariates, allow
goodness‐of‐fit assessments and give accurate estimates of survivorship
in realistic settings. We first conducted a Monte Carlo study and
simulated age at death data to assess the accuracy of estimates with
respect to sample size. Secondly, we applied this framework on a handful
of case studies from published studies on marine mammals, a group with
many threatened and data‐deficient species. We found that our framework
is flexible and accurate to estimate survivorship with a sample size of
300. This approach is promising for obtaining important demographic
information on data‐poor species. 

Please feel free to contact me with

King Regards, 

Etienne Rouby

Etienne Rouby
PhD Student /
Observatoire PELAGIS (UMS 3462)
Centre d'Etudes Biologiques de
Chizé (UMR 7372)
tel : 05 16 49 67 20 

Observatoire PELAGIS
Centre commun d'analyse
5 allée de l'océan
17000 La
www.observatoire-pelagis.cnrs.fr [1] 

univ-larochelle.fr [2]

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[1] http://www.observatoire-pelagis.cnrs.fr
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