Assessing the robustness of time‐to‐event models for estimating unmarked wildlife abundance using remote cameras

2021 ◽  
Author(s):  
Kenneth E. Loonam ◽  
Paul M. Lukacs ◽  
David E. Ausband ◽  
Michael S. Mitchell ◽  
Hugh S. Robinson
Keyword(s):  
Time To Event ◽  
Remote Cameras ◽  
Event Models

A comparison of estimators to evaluate the discriminatory power of time-to-event models

2012 ◽  
Vol 31 (23) ◽  
pp. 2588-2609 ◽  
Author(s):  
Matthias Schmid ◽  
Sergej Potapov
Keyword(s):  
Discriminatory Power ◽  
Time To Event ◽  
Event Models

scholarly journals Quantifying the predictive accuracy of time-to-event models in the presence of competing risks

2011 ◽  
Vol 53 (1) ◽  
pp. 88-112 ◽  
Author(s):  
Rotraut Schoop ◽  
Jan Beyersmann ◽  
Martin Schumacher ◽  
Harald Binder
Keyword(s):  
Competing Risks ◽  
Predictive Accuracy ◽  
Time To Event ◽  
Event Models

scholarly journals Semiparametric regression for discrete time-to-event data

2018 ◽  
Vol 18 (3-4) ◽  
pp. 322-345 ◽  
Author(s):  
Moritz Berger ◽  
Matthias Schmid
Keyword(s):  
Semiparametric Regression ◽  
Outcome Variable ◽  
Nonlinear Functions ◽  
Time To Event ◽  
Regression Methods ◽  
Time To Event Data ◽  
Duration Of Unemployment ◽  
Event Models ◽  
Analyse Data ◽  
Event Times

Abstract: Time-to-event models are a popular tool to analyse data where the outcome variable is the time to the occurrence of a specific event of interest. Here, we focus on the analysis of time-to-event outcomes that are either intrinsically discrete or grouped versions of continuous event times. In the literature, there exists a variety of regression methods for such data. This tutorial provides an introduction to how these models can be applied using open source statistical software. In particular, we consider semiparametric extensions comprising the use of smooth nonlinear functions and tree-based methods. All methods are illustrated by data on the duration of unemployment of US citizens.

scholarly journals Hydrothermal-time-to-event models for seed germination

2018 ◽  
Vol 101 ◽  
pp. 129-139 ◽  
Author(s):  
Andrea Onofri ◽  
Paolo Benincasa ◽  
Mohsen B. Mesgaran ◽  
Christian Ritz
Keyword(s):  
Seed Germination ◽  
Hydrothermal Time ◽  
Time To Event ◽  
Event Models

Analysing adverse events by time-to-event models: the CLEOPATRA study

2016 ◽  
Vol 15 (4) ◽  
pp. 306-314 ◽  
Author(s):  
Tanja Proctor ◽  
Martin Schumacher
Keyword(s):  
Adverse Events ◽  
Time To Event ◽  
Event Models
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