A general hazard model for lifetime data in the presence of cure rate

Historically, the cure rate model has been used for modeling time-to-event data within which a significant proportion of patients are assumed to be cured of illnesses, including breast cancer, non-Hodgkin lymphoma, leukemia, prostate cancer, melanoma, and head and neck cancer. Perhaps the most popular type of cure rate model is the mixture model introduced by Berkson and Gage [1]. In this model, it is assumed that a certain proportion of the patients are cured, in the sense that they do not present the event of interest during a long period of time and can found to be immune to the cause of failure under study. In this paper, we propose a general hazard model which accommodates comprehensive families of cure rate models as particular cases, including the model proposed by Berkson and Gage. The maximum-likelihood-estimation procedure is discussed. A simulation study analyzes the coverage probabilities of the asymptotic confidence intervals for the parameters. A real data set on children exposed to HIV by vertical transmission illustrates the methodology.

Knowledge about a species' conservation status and funding for its preservation: Analysis

Using a species’ population to measure its conservation status, this note explores how an increase in knowledge about this status would change the public’s willingness to donate funds for its conservation. This is done on the basis that the relationship between the level of donations and a species’ conservation status satisfies stated general mathematical properties. This level of donation increases, on average, with greater knowledge of a species’ conservation status if it is endangered, but falls if it is secure. Game theory and other theory is used to show how exaggerating the degree of endangerment of a species can be counterproductive for conservation.