Inference in Cutoff Sampling

Alan H. Dorfman

Abstract

In cutoff sampling, inference -— for example, interval estimates with associated alpha-levels —- is problematic. Design-based samplers do not find an adequate random design on which to base variance estimates. Model-based samplers worry that gaps in information can lead to biases. We nonetheless describe some schemes for inference in cutoff sampling.