Nonparametric estimation of quality adjusted lifetime distribution in a simple illness-death model

In this work, we consider the nonparametric estimation of quality adjusted lifetime (QAL) distribution in a simple illness-death model. We first derive the expression of QAL distribution in terms of the distribution of sojourn time in each health state. Next we substitute the estimate of sojourn time distributions in the expression of QAL distribution to obtain its estimate. Consistency and asymptotic normality of the proposed nonparametric estimator are established. Estimation in the presence of some missing data on the transition time to illness is also discussed. We conduct a simulation study to investigate the performance of the proposed estimator. For illustration, we analyse a data set of the Stanford Heart Transplant program. Extension to multistate progressive model is discussed along with an analysis of International Breast Cancer Study Group (IBCSG) Trial V data.     

BinNor: An R Package for Concurrent Generation of Binary and Normal Data

This article describes the package BinNor, which is designed for generating multiple binary and normal variables simultaneously given marginal characteristics and association structure via combining well-established results from the random number generation literature, based on the methodology proposed by Demirtas and Doganay.     

Nonparametric estimation of the number of components of a superposition of renewal processes

Suppose all events occurring in an unknown number (ν)$(\nu )$ of iid renewal processes, with a common renewal distribution F  , are observed for a fixed time τ$\tau$, where both ν$\nu$ and F   are unknown. The individual processes are not known a priori, but for each event, the process that generated it is identified. For example, in software reliability application, the errors (or bugs) in a piece of software are not known a priori, but whenever the software fails, the error causing the failure is identified. We present a nonparametric method for estimating ν$\nu$ and investigate its properties. Our results show that the proposed estimator performs well in terms of bias and asymptotic normality, while the MLE of ν$\nu$ derived assuming that the common renewal distribution is exponential may be seriously biased if that assumption does not hold.     

A Stochastic Two-Stage Model for Cancer Risk Assessment. I. The Hazard Function and the Probability of Tumor

We present a mathematical treatment of a two-mutation model for carcinogenesis with time-dependent parameters. This model has previously been shown to be consistent with epidemiologic and experimental data. An approximate hazard function used in previous papers is critically evaluated.