Abstract
Small samples with censored data, when analyzed by large-sample methods, yield confidence intervals that are too short. This article presents tables for exact confidence limits for the parameters of a normal or lognormal distribution, using maximum likelihood (ML) estimates from singly censored samples. The tables, based on Monte Carlo simulation, cover selected sample sizes up to n = 100 with various r ≤ n observed and (n − r) censored observations; r ranges from 2 to n. The exact ML method is compared to large-sample ML and exact best linear unbiased estimation methods. The tables are used in considering sample sizes for designing life tests.