[PDF] Top 20 Parametric Estimation in a Recurrent Competing Risks Model

... Cause 1. Individual curves represent a different rate (2, 1, 1/2, 1/5, and 1/10, respectively from top to bottom) associated with an exponential censoring distribution. As the rate increases (which results in a decrease ... See full document

... Markov model for competing risks and we studied the transition probabilities from first to second tumour varying in ...increased risks during the observed ...possible parametric or non- ... See full document

... A competing risks model based on exponential distribution is considered under adaptive type-I progressive hybrid censoring ...likelihood estimation and Bayesian estimation for the ... See full document

... are competing events; meanwhile it is not possible to reach an accurate estimation of survival of patients with pulmonary TB irrespective of both disease relapse and death ...accurate estimation of ... See full document

... handle competing risks have been developed by several ...regression model introduced by Fine and Gray (1999) has its significance in terms of one-to-one correspondence between its hazard function for ... See full document

... Competing risks analysis for cluster data is a special type of competing risk analysis, where there is a correlation between the time-to-event outcomes within cluster (Zhou et ...frailty-based ... See full document

... the competing risks model are robust to the specification of a permissible gap length, the relative proportion of noncompliant and nonpersis- tent events does ...the competing risks ... See full document

... in competing risks analysis. In this paper, we study a competing risks model in the presence of covariates when the causes of failures follow generalized Weibull ...the model ... See full document

... to model the length of registration at university and its associated academic outcome for undergraduate students at the Pontificia Universidad Cat´olica de ...a competing risks model is ... See full document

... The second paper looking at clustered survival data we compare our results to is a sim- ulation by Xiao and Abrahamowicz (2010). They performed a simulation applying the two bootstrap methods we considered to study the ... See full document

... applications, recurrent competing risks observed from the same unit are often ...different recurrent competing risks described in section ...the model is identical to the ... See full document

... It is clear that the likelihood ratio statistics plays an important role in theories of asymptotical estimation and hypothesis testing. The aim of the paper is to investigate the asymptotic properties of ... See full document

... a model for π(W ) and %(W ...regression model that includes ER-status as a covariate to fit the π model or the % model as the MLE does not ...regression model for π using the subset of ... See full document

... make model fitting practically ...BCAR model when compared with the GMCAR model that has been shown to perform better than other proposed models for multivariate areal ... See full document

... The construction and the main features of the PUC dataset are summarized in Section 2, showing high heterogeneity (in terms of academic outcomes and the student population char- acteristics) among programmes. Section 3 ... See full document

... for model (2), where controlling the degree of central bank independence (CBI) generates a negative coefficient for the volatility of output in the orderly-exit ... See full document

... described as: elimination of the j-th cause would lead to increased mortal- ity with respect to the k-th cause and hence, to decreased overall survival. Clearly, this is of little practical relevance since removal of a ... See full document

... for estimation valuation multiples for the forestry ...accurate estimation of location parameter for the multiples value in comparison with the value of publicly traded stock on capital ... See full document

... effort estimation model. This model integrates change effort estimation with impact analysis for the software development ...effort estimation results; which will help the software ... See full document

... the conditional likelihood function. An adjusted impor- tance sampling method was used to compute the marginal likelihood function, where the MLEs for the regression coefficients were obtained by an iterative ... See full document