[ABE-L] Fwd: CONVITE PPGEST - Webinar - Profa. Vera Tomazella (EST/UFSCar) - 01/04/2021 - 16:00h

[Helton Saulo]

O Programa de Pós-Graduação em Estatística da Universidade de Brasília
convida para:

*WEBINAR: *Zero-adjusted defective regression models for modeling lifetime
data

*Palestrante: *Profa. Vera Tomazella (EST/UFSCar)

*DATA: *01/04/2021 (quinta-feira)

*HORÁRIO: *16:00h (horário local de Brasília)

O seminário é público e poderá ser assistido pelo Link
<https://teams.microsoft.com/l/meetup-join/19%3ad2849304d2874ded840766128e676bb7%40thread.tacv2/1617116281389?context=%7b%22Tid%22%3a%22ec359ba1-630b-4d2b-b833-c8e6d48f8059%22%2c%22Oid%22%3a%226698d81b-6b87-4349-a6dc-5ccfddfaaf3f%22%7d>
.

*Resumo: *

In this talk, we introduce a defective regression model for survival data
> modeling with a proportion of early failures or zero-adjusted. Our approach
> enables us to accommodate three types of units, that is, patients with
> 'zero' survival times (early failures) and those who are susceptible or not
> susceptible to the event of interest. Defective distributions are obtained
> from standard distributions by changing the domain of the parameters of the
> latter in such a way that their survival functions are limited to p∈ (0,
> 1)$. We consider the Gompertz and inverse Gaussian defective distributions,
> which allow modeling of data containing a cure fraction. Parameter
> estimation is performed by maximum likelihood estimation, and Monte Carlo
> simulation studies are conducted to evaluate the performance of the
> proposed models. We illustrate the practical relevance of the proposed
> models on one real data set on insulin use in pregnant women diagnosed with
> gestational diabetes performed at São Paulo University Medical School, São
> Paulo, Brazil

*O QR Code *para acesso à palestra encontra-se neste Link
<https://drive.google.com/file/d/1OSD9Fg6v4rlzG5B1eewOLdyNBJBZA8dr/view?fbclid=IwAR3b-_rOnoAZJyGz_dTkQAyDCi6VgjXSvcFWyvBzlFM3BxaGwA3lYcEFc3s>
.
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