8 documents found, page 1 of 1
Nonparametric regression with doubly truncated data
Moreira, Carla; Uña Álvarez, Jacobo de; Machado, Luís MeiraNonparametric regression with a doubly truncated response is introduced. Local constant and local linear kernel-type estimators are proposed. Asymptotic expressions for the bias and the variance of the estimators are obtained, showing the deterioration provoked by the random truncation. To solve the crucial problem of bandwidth choice, two different bandwidth selectors based on plug-in and cross-validation idea...
Nonparametric regression with doubly truncated data
Moreira, Carla; Uña Álvarez, Jacobo de; Machado, Luís MeiraIn this paper nonparametric regression with a doubly truncated response is introduced. Local constant and local linear kernel-type estimators are proposed. Asymptotic expressions for the bias and the variance of the estimators are obtained, showing the deterioration provoked by the random truncation. To solve the crucial problem of bandwidth choice, two different bandwidth selectors based on plug-in and cross-v...
Conditional transition probabilities in a non-Markov illness-death model
Machado, Luís Meira; Uña Álvarez, Jacobo de; Datta, SomnathOne important goal in multi-state modeling is the estimation of transition probabilities. In longitudinal medical studies these quantities are particularly of interest since they allow for long-term predictions of the process. In recent years significant contributions have been made regarding this topic. However, most of the approaches assume independent censoring and do not account for the influence of covaria...
A semiparametric estimator of the bivariate distribution function for censored ...
Uña Álvarez, Jacobo de; Amorim, Ana PaulaLet (T1, T2) be gap times corresponding to two consecutive events, which are observed subject to random right-censoring. In this paper, a semiparametric estimator of the bivariate distribution function of (T1, T2) and, more generally, of a functional E[$\phi$(T1,T2)] is proposed. We assume that the probability of censoring for T2 given the (possibly censored) gap times belongs to a parametric family of binary r...
Presmoothing the transition probabilities in the illness-death model
Amorim, Ana Paula; Uña Álvarez, Jacobo de; Machado, Luís MeiraOne major goal in clinical applications of multi-state models is the estimation of transition probabilities. In a recent paper, Meira-Machado et al. (2006) introduce a substitute for the Aalen–Johansen estimator in the case of a non-Markov illness–death model. The idea behind their estimator is to weight the data by the Kaplan–Meier weights pertaining to the distribution of the total survival time of the proces...
Nonparametric location-scale models for censored successive survival times
Keilegom, Ingrid van; Uña Álvarez, Jacobo de; Machado, Luís MeiraLet (T1,T2) be gap times corresponding to two consecutive events,which are observed subject to (univariate) random right-censoring.The censoring variable corresponding to the second gap time T2 will in general depend on this gap time. Suppose the vector (T1,T2) satisfies the non parametric location-scale regression model T2=m(T1)+σ(T1)ɛ, where the functions m and σ are ‘smooth’, and ɛ is independent of T1. The ...
Kernel density estimation with doubly truncated data
Moreira, Carla; Uña Álvarez, Jacobo deIn some applications with astronomical and survival data, doubly truncated data are sometimes encountered. In this work we introduce kernel-type density estimation for a random variable which is sampled under random double truncation. Two different estimators are considered. As usual, the estimators are defined as a convolution between a kernel function and an estimator of the cumulative distribution function, ...
Alternatives to the Cox model in multi-state models
Machado, Luís Meira; Cadarso-Suárez, Carmen; Uña Álvarez, Jacobo deThe introduction of time-dependent covariates in the survival process can make the patients survival change from one time point to the next as the values of the covariate change. A popular choice for the analysis of this data is the timedependent Cox regression model. In the present work we present multi-state models as an alternative for the analysis of such data.