SUMMARY Cause-specific hazard and cumulative incidence function are of practical importance in competing risks studies. Inferential procedures for these quantities are well developed and can be applied to semi-competing risks data, where a terminating event censors a non-terminating event, after coercing the data into the competing risks format. Complications arise when there is left truncation...

protein a is a commercially important protein in biotechnological and medicinal applications. the great value of this protein and its applications in genetic and protein engineering and microbial researches as well as the growing use in biochemical industries, biotechnology, medicine and pharmacology, highlight the importance of the present study. in this survey the encoding genes of full-lengt...

Left truncation and right censoring arise naturally in lifetime data. Left truncation arises because in many situations, failure of a unit is observed only if it fails after a certain period. Often, the units under study may not be followed until all of them fail and the experimenter may have to stop at a certain time when some of the units may still be working. This introduces right censoring ...

Survival data collected from a prevalent cohort are subject to left truncation and the analysis is challenging. Conditional approaches for left-truncated data could be inefficient as they ignore the information in the marginal likelihood of the truncation times. Length-biased sampling methods may improve the estimation efficiency but only when the underlying truncation time is uniform; otherwis...

In this paper, we propose a frailty model for statistical inference in the case where we are faced with arbitrarily censored and truncated data. Our results extend those of Alioum and Commenges (1996), who developed a method of fitting a proportional hazards model to data of this kind. We discuss the identifiability of the regression coefficients involved in the model which are the parameters o...

The permutation test is one of the oldest techniques for making statistical inferences. Monte Carlo methods and asymptotic formulas have been used to approximate the associated p-values. When data are truncated, however, the permutation null distribution is difficult to handle. We describe here an efficient sequential importance sampling strategy for generating permutations with restricted posi...

Traditional inferential procedures often fail with censored and truncated data, especially when sample sizes are small. In this paper we evaluate the performances of the double and single bootstrap interval estimates by comparing the double percentile (DB-p), double percentile-t (DB-t), single percentile (B-p), and percentile-t (B-t) bootstrap interval estimation methods via a coverage probabil...

The problem of estimating the tail index from truncated data is addressed in ?. In that paper, a sample based (and hence random) choice of k is suggested, and it is shown that the choice leads to a consistent estimator of the inverse of the tail index. In this paper, the second order behavior of the Hill estimator with that choice of k is studied, under some additional assumptions. In the untru...

Truncated multivariate survival models are proposed for the analysis of data from the South Australian Methadone Program. Injecting drug users may have several entries to and exists from the program. A marginal approach for recurrent events is found to provide a useful and simplified basis for modeling the retention of injecting drug users on methadone. The likelihoods and results of fitting tw...

UNLABELLED It is common, even with new SPECT/CT systems, that the transmission data are truncated. This paper develops a method that obtains exact attenuation correction with truncated transmission data. The emission object (e.g., the heart) is assumed to have a finite, convex support, whose emission projections are not truncated. The transmission measurements over the support are available, bu...