Nonparametric estimation of the survival function for ordered multivariate failure time data: a comparative study

In longitudinal studies of disease, patients may experience several events through a follow-up period. In these studies, the sequentially ordered events are often of interest and lead to problems that have received much attention recently. Issues of interest include the estimation of bivariate survival, marginal distributions and the conditional distribution of gap times. In this work we consider the estimation of the survival function conditional to a previous event. Different nonparametric approaches will be considered for estimating these quantities, all based on the Kaplan-Meier estimator of the survival function. We explore the finite sample behavior of the estimators through simulations. The different methods proposed in this article are applied to a data set from a German Breast Cancer Study. The methods are used to obtain predictors for the conditional survival probabilities as well as to study the influence of recurrence in overall survival.

Firm innovation and co-location in Portugal

This paper investigates the geographical distribution and concentration of firms’ innovation persistence and innovation type (product and process) based on three waves of the Portuguese Community Innovation Survey data covering the period 1998–2006. The main findings are: 1) both innovation persistence and innovation type are asymmetrically distributed across Portuguese regions, 2) the degree of correlation between geographical location and innovative output varies with the innovation type, and 3) the correlation between geographical unit and innovation increases when the spatial unit of analysis is narrower. The results suggest that the firms’ choices of geographical location have a long-lasting effect, engendering no equal probabilities of being persistently innovative.

On the length of bank-firm relationships: an empirical application to a major French bank

NIPE - WP 01/ 2016

Ki-67 expression in CRC lymph node metastasis does not predict survival

Colorectal cancer is one of the most common malignancies and a leading cause of cancer death worldwide. Molecular markers may improve clinicopathologic staging and provide a basis to guide novel therapeutic strategies which target specific tumourassociated molecules according to individual tumour biology; however, so far, no ideal molecular marker has been found to predict disease progression. We tested Ki-67 proliferation marker in primary and lymph node metastasis of CRC. We observed a statistical significant difference between the positive rates of neoplastic cells positively stained byKi-67 in both sites, with remarkable increased number of Ki-67 positive cells in primary tumor cells compared to cancer cells that invaded lymph nodes. We can speculate that the metastatic CRC in lymph node can be more resistant to the drugs that target cellular division.

Joint modelling of longitudinal and survival data on breast cancer

Tese de Doutoramento em Ciências (Especialidade em Matemática)

Determination of the importance of iron acquisition for Staphylococcus epidermidis biofilm survival in human blood

Dissertação de mestrado em Bioengenharia