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Universidade Federal de São Carlos (UFSCAR). Centro de Ciências Exatas e de Tecnologia (CCET) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Vera Tomazella is a Full Professor at the Federal University of São Carlos-UFSCar. She holds a degree in Mathematics from the Federal University of Maranhão, a Master's in Computer Science and Computational Mathematics from the University of São Paulo (1994) and a PhD in Computer Science and Computational Mathematics from the University of São Paulo (2003). She has a postdoctoral degree from the University of Valencia-Spain and a postdoctoral degree from the University of Manchester-UK. Elected member of the International Statistical Institute (ISI) and member of the IBS Education Committee. President of the Brazilian Region of the International Society of Biometrics (RBras). She works mainly in the following areas: Survival and Reliability Analysis, Risk Models, Diagnostic Analysis, Bayesian Inference, Non-Linear Models. (Source: Lattes Curriculum)
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One of the challenges in survival analysis is modeling heterogeneous populations, which can be addressed by including frailty terms to capture unobserved variability between individuals or groups. The cure model in survival analysis is used to describe situations where part of the population never experiences the event of interest, such as failures or deaths, due to a "cure" process. This…
In industries composed of complex equipment, arranged in series or in parallel, a simple failure can mean the shutdown of the production line as a whole, generating huge financial losses and inconvenience. The methodologies for detecting failures and analyzing their effects have great applicability in the industry, for example to improve the performance of products, to optimize their reso…
(Only some records are available in English at this moment)
The models of cure fraction in survival data studies have become an important research field within the area, attracting researchers' attention. Cure fraction models through defective distributions have the advantage of modeling the proportion of cured individuals without adding extra parameters to a model, contrary to what happens in the main models in the literature. In the literature, …
In studies involving the time until the occurrence of some event of interest (failure) there is a possibility that not always all study subjects experiment the event of interest even if these individuals is observed a very long time. These individuals are said to be cured or immune to the event of interest and, consequently, its population has a proportion of cure. Generally the time unti…
Item Response Theory (IRT) provides sets of models that represent certain characteristics unobservable (latent traits) of individuals (or companies, schools, etc.). This modeling is based on the probability of response of the individual items (or attributes of the latent trait) conditional on latent traits and characteristics of measuring instruments, such as level of difficulty of an ite…
Several authors have preferred modeling survival data in the presence of covariates by the risk function, which is related to its interpretation. It describes how the instantaneous probability of failure is changing with time. In this context, one of the most used models is the Cox model (Cox, 1972) where the basic assumption for its use is that the failure rates are proportional. However…
(Only some records are available in English at this moment)
Models based on hazard function have achieved great prominence in the survival analysis from the construction of the proportional hazards model of Cox (1972). One of the reasons this model has become so popular is its interpretative power and ease with which the technical difficulties arising from the censures were circumvented. Naturally, the construction of the model allows the covariat…
| 1 / 1 | Ongoing grants |
| 14 / 10 | Completed research grants |
| 1 / 1 | Ongoing scholarships in Brazil |
| 5 / 4 | Completed scholarships in Brazil |
| 2 / 1 | Completed scholarships abroad |
| 23 / 17 | All research grants and scholarships |
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