Analyzing continuous randomized response data with an indifference-zone selection procedure

A review of the randomized response model introduced by Warner (1965) is given, then a randomized response model applicable to continuous data that considers a mixture of two normal distributions is considered. The target here is not to estimate any parameter, but rather to select the population with the best parameter value. This article provides a study on how to choose the best population between k distinct populations using an indifference-zone procedure. Also, this article includes tables for the required sample size needed in order to have a probability of correct selection higher than some specified value in the preference zone for the randomized response model considered.     

Supply Chain Strategies for Perishable Products: The Case of Fresh Produce

This paper examines supply chain design strategies for a specific type of perishable product—fresh produce—using melons and sweet corn as examples. Melons and other types of produce reach their peak value at the time of harvest; product value deteriorates exponentially post‐harvest until the product is cooled to dampen the deterioration. Using the product's marginal value of time (MVT), the rate at which the product loses value over time in the supply chain, we show that the appropriate model to minimize lost value in the supply chain is a hybrid of a responsive model from post‐harvest to cooling, followed by an efficient model in the remainder of the chain. We also show that these two segments of the supply chain are only loosely linked, implying that little coordination is required across the chain to achieve value maximization. The models we develop also provide insights into the use of a product's MVT to develop supply chain strategies for other perishable products.     

EFFICIENT TUITION FEES AND EXAMINATIONS

We assume that students observe only a private, noisy signal of their ability and that universities can condition admission decisions on the results of noisy tests. If the university observes a private signal of each student's ability, which is soft information, then asymmetries of information are two‐sided, and the optimal admission policy involves a mix of pricing and pre‐entry selection, based on the university's private information. In contrast, if all test results are public knowledge, then there is no sorting on the basis of test scores: Tuition alone does the job of implementing an optimal degree of student self‐selection. These results do not depend on the existence of peer effects. The optimal tuition follows a classic marginal social‐cost pricing rule. (JEL: D82, H42, I22, J24)     

Methods for one-sided testing of the difference between proportions and sample size considerations related to non-inferiority clinical trials

Assessment of non-inferiority is often performed using a one-sided statistical test through an analogous one-sided confidence limit. When the focus of attention is the difference in success rates between test and active control proportions, the lower confidence limit is computed, and many methods exist in the literature to address this objective. This paper considers methods which have been shown to be popular in the literature and have surfaced in this research as having good performance with respect to controlling type I error at the specified level. Performance of these methods is assessed with respect to power and type I error through simulations. Sample size considerations are also included to aid in the planning stages of non-inferiority trials focusing on the difference in proportions. Results suggest that the appropriate method to use depends on the sample size allocation of subjects in the test and active control groups.