Maximum-relevance weighted likelihood estimator: application to the continual reassessment method

Maximum Weighted Likelihood Estimator in Logistic Regression

The least weighted squares estimator is a well known technique in robust regression. Its likelihood analogy in logistic regression is the maximum weighted likelihood estimator, proposed in Vandev and Neykov (1998) and Mueller and Neykov (2003). This article mentions already proved properties, shows its inconsistency and compare it to the other estimators by an extensive simulation. Introduction...

An Application of Continual Reassessment Method Using SAS System

The Bayesian technique, Continual Reassessment Method (CRM), introduced by O’Quigley et al. (1990) is a new design for phase I trials in cancer. The goal of this design is to reduce the number of patients who receive lower doses, which are not expected to be effective, and to obtain a more accurate estimate of the maximum tolerated dose (MTD). The CRM has a couple of attractive characters, whic...

The flexible bivariate continual reassessment method

Two-group time-to-event continual reassessment method using likelihood estimation.

The presence of patient heterogeneity in dose finding studies is inherent (i.e. groups with different maximum tolerated doses). When this type of heterogeneity is not accounted for in the trial design, subjects may be exposed to toxic or suboptimal doses. Options to handle patient heterogeneity include conducting separate trials or splitting the trial into arms. However, cost and/or lack of res...

Continual reassessment method with multiple toxicity constraints.

This paper addresses the dose-finding problem in cancer trials in which we are concerned with the gradation of severe toxicities that are considered dose limiting. In order to differentiate the tolerance for different toxicity types and grades, we propose a novel extension of the continual reassessment method that explicitly accounts for multiple toxicity constraints. We apply the proposed meth...