This paper develops a censored generalized Poisson regression model that can be used to predict a response variable that is a2ected by one or more explanatory variables. The censored generalized Poisson regression model is suitable for modeling count data that exhibit either overor under-dispersion. The regression parameters are estimated by the method of maximum likelihood and approximate test...

Sun, Liao, and Pagano (1999) proposed an interesting estimating equation approach to Cox regression with doubly censored data. Here we point out that a modification of their proposal leads to a multiple imputation approach, where the double censoring is reduced to single censoring by imputing for the censored initiating times. For each imputed data set one can take advantage of many existing te...

This paper proposes minimum distance estimation procedures for the slope coefficients and location parameter in randomly censored regression models that are used in duration and competing risk models. The proposed procedure generalizes existing work in terms of weakening the restrictions imposed on the distribution of the error term and the censoring variable. Examples of such generalizations i...

Under a conditional quantile restriction, randomly censored regression models can be written in terms of conditional moment inequalities. We study the identified features of these moment inequalities with respect to the regression parameters. These inequalities restrict the parameters to a set. We then show regular point identification can be achieved under a set of interpretable sufficient con...

Censoring models are frequently employed in reliability analysis to reduce experimental time. There are three censoring model: type-I, type-II and random censoring. In this study, we focus on the right-random censoring model. In the previous literature, an imputation of the censored observation is considered as the censoring time (Miller (1981), Lawless (1982), Lee (1992) and among others). Cle...

Consider repeated measures data with many zeros. For the case with one grouping factor and one repeated measure, we examine several models, assuming that the nonzero data are roughly lognormal. One of the simplest approaches is to model the zeros as left-censored observations from the lognormal distribution. A random effect is assumed for subjects. The censored model makes a strong assumption a...

In survival analysis, proportional hazards model is the most commonly used and the Cox model is the most popular. These models are developed to facilitate statistical analysis frequently encountered in medical research or reliability studies. In analyzing real data sets, checking the validity of the model assumptions is a key component. However, the presence of complicated types of censoring su...

Analysis of gene quantities measured by quantitative real-time PCR (qPCR) can be complicated by observations that are below the limit of quantification (LOQ) of the assay. A hierarchical model estimated using MCMC methods was developed to analyze qPCR data of genes with observations that fall below the LOQ (censored observations). Simulated datasets with moderate to very high levels of censorin...

The reliability data is getting used to monitor and improve the quality of products or services. Nowadays, most of products or services are the results of processes with dependent stages referred to as multi-stage process. In these processes, the quality characteristics are affected by the quality characteristics in the previous stages, called as cascade property. In some cases, it is not possi...

We analyze households' joint investment decisions for nancial wealth and homes. We use a bivariate censored regression model with endogenous switching. Fixed costs or transaction costs are captured by an unobserved nonzero censoring threshold. The model allows for spill{over e ects of a binding threshold for one asset on the demand for the other asset. We nd that tenure choice a ects the level ...