David Azriel

TL;DR: In this article, a randomized design that assigns the MTD with probability that approaches one as the size of the experiment goes to infinity and estimates the maximum tolerated dose (MTD) consistently was proposed.

TL;DR: This work provides a necessary and sufficient condition for convergence of the empirical cumulative distribution function (ecdf) of standard normal random variables under arbitrary correlation, and shows that the ecdf limit is a random, possible infinite, mixture of normal distribution functions that depends on a number of latent variables and can serve as an asymptotic approximation to the ecDF in high dimensions.

TL;DR: It is suggested that examination of convergence is a necessary quality check for dose-finding designs, and a new convergence proof for a nonparametric family of methods called “interval designs,” under certain conditions on the toxicity-frequency function F.

TL;DR: GreedyExperimentalDesign as mentioned in this paper is an experimental design procedure that divides a set of experimental units into two groups so that the two groups are balanced on a prespecified set of covariates and being almost as random as complete randomization.

TL;DR: In this article, the authors study a regression problem where for some part of the data, the label variable (Y) and the predictors (X ) are observed, while for other part, the predicted variables are not observed.