Model-Based Stratification in Inventory Cost Estimation

Abstract

This article describes a method for developing an efficiently stratified sampling design for a generalized difference estimator, using a superpopulation model. The effectiveness of model-based stratification is compared to several conventional designs, using a data base from a complete audit of an inventory of 8,069 items. In this application, model-based designs reduce the required sample size from 9% to 40%, compared to the conventional designs.