The Cox model with time-dependent coefficients has been studied by a number of authors recently. In this paper, we develop empirical likelihood (EL) pointwise confidence regions for the time-dependent regression coefficients via local partial likelihood smoothing. The EL simultaneous confidence bands for a linear combination of the coefficients are also derived based on the strong approximation...

The composite likelihood method has been proposed and systematically discussed by Besag (1974), Lindsay (1988), and Cox and Reid (2004). This method has received increasing interest in both theoretical and applied aspects. Compared to the traditional likelihood method, the composite likelihood method may be less statistically efficient, but it can be designed so as to be significantly faster to...

grapes are among the world most planted horticultural crops. since the last century, attempts have been made to improve the quality of grapes in the world. meanwhile, the necessity of having knowledge about the history of progenies families led to the link between genealogy and breeding. considering some previous mislabeling, in order to find out the accuracy of the controlled crosses as well a...

A general simulation procedure is described to validate model fitting algorithms for complex likelihood functions that are utilized in periodic cancer screening trials. Although screening programs have existed for a few decades, there are still many unsolved problems, such as how age or hormone affects the screening sensitivity, the sojourn time in the preclinical state, and the transition prob...

The likelihood ratio approach for DNA typing in criminal cases is described. It is shown how this approach uses both the sizes and pattern of discrepancies between the crime scene profile of fragment lengths and the suspect profile for quantifying the strength of the evidence. In contrast to the current match-binning approach, it avoids an initial decision about whether the two profiles match. ...

BACKGROUND Likelihood ratios offer important advantages over sensitivity and specificity for characterizing diagnostic tests. They can capture the magnitude of abnormality of test results, whereas sensitivity and specificity require that the test results be dichotomized into positive or negative. This is an important advantage because many diagnostic tests are measured on continuous or ordinal ...