Confidence Intervals Based on Rounded Data from the Balanced One-Way Normal Random Effects Model

Abstract

In standard statistical analyses, data are assumed to be essentially exact. But indeed they are often obtained from a relatively crude gaging method and are thus intrinsically “rounded” to some nearest unit. The discussions in Lee and Vardeman (Lee, Chiang-Sheng, Vardeman, Stephen B. (2001). Interval estimation of a normal process mean from rounded data. Journal of Quality Technology 33:335–348.) and Lee and Vardeman (Lee, Chiang-Sheng, Vardeman, Stephen B. (2002). Interval estimation of a normal process standard deviation from rounded data. Communications in Statistics 31:13–34.) for a rounded sample from a single normal distribution established that nominal confidence levels of standard intervals for μ and σ are much larger than actual coverage probabilities when the rounding is severe. In this article we consider interval estimation in the balanced normal one-way random effects model. We demonstrate the deficiency of standard interval estimators in the presence of rounding and show how likelihood-based results from Lee and Vardeman (Lee, Chiang-Sheng, Vardeman, Stephen B. (2002). Interval estimation of a normal process standard deviation from rounded data. Communications in Statistics 31:13–34.) can be used to produce reliable confidence procedures for the two variance components.

Keywords:

• Coverage probability
• Gaging