*Correspondence: [email protected] 3Departamento de Estatística, Universidade Federal de Pernambuco, PE 50740-540, Recife, Brazil Full list of author information is available at the end of the article Abstract We propose and study a new compounded model to extend the half-Cauchy and power-Cauchy distributions, which offers more flexibility in modeling lifetime data. The proposed model is ...

Interval-censored failure time data often occur, for example, in clinical trials or longitudinal studies. For the regression analysis of such data, there have been a number of methods proposed based on continuous regression models such as Cox's proportional hazards model. In practice, however, observed interval-censored data that arise from clinical trials are often given in a discrete scale du...

In a recent paper, Kooperberg, Stone, and Truong (1995a) introduced hazard regression (HARE), in which linear splines and their tensor products are used to estimate the conditional log-hazard function based on possibly censored, positive response data and one or more covariates. Model selection is carried out in an adaptive fashion using maximum likelihood estimation of the unknown coefficients...

This article suggests very simple three-step estimators for censored quantile regression models with a separation restriction on the censoring probability. The estimators are theoretically attractive (i.e., asymptotically as efŽ cient as the celebrated Powell’s censored least absolute deviation estimator). At the same time, they are conceptually simple and have trivial computational expenses. T...

Genetic and environmental influences on variance in phenotypic traits may be estimated with normal theory Maximum Likelihood (ML). However, when the assumption of multivariate normality is not met, this method may result in biased parameter estimates and incorrect likelihood ratio tests. We simulated multivariate normal distributed twin data under the assumption of three different genetic model...

We propose a non-parametric multiple imputation scheme, NPMLE imputation, for the analysis of interval censored survival data. Features of the method are that it converts interval-censored data problems to complete data or right censored data problems to which many standard approaches can be used, and that measures of uncertainty are easily obtained. In addition to the event time of primary int...

This software fits a multivariate proportional hazards model to interval censored event data by a Bayesian approach. Right and interval censored data and a lognormal or gamma frailty term can be fitted. An example is studied and the output analysed. 1 The basic model The data, based on a sample of size n, consists of the triple (ti, δi,xi), i = 1, . . . , n where ti is the time on study for sub...

Interval censored outcomes arise when a silent event of interest is known to have occurred within a specific time period determined by the times of the last negative and first positive diagnostic tests. There is a rich literature on parametric and non-parametric approaches for the analysis of interval-censored outcomes. A commonly used strategy is to use a proportional hazards (PH) model with t...

Statistical inference based on right-censored data for the proportional hazards (PH) model with missing covariates has received considerable attention, but interval-censored or current status data with missing covariates has not yet been investigated. Our study is partly motivated by the analysis of fracture data from the 2005 National Health Interview Survey Original Database in Taiwan, where ...

We extend Wei and Tanner's (1991) multiple imputation approach in semi-parametric linear regression for univariate censored data to clustered censored data. The main idea is to iterate the following two steps: 1) using the data augmentation to impute for censored failure times; 2) fitting a linear model with imputed complete data, which takes into consideration of clustering among failure times...