Confidence Intervals for Common Mean of Lognormal Distributions

This paper presents new confidence intervals for the common mean of lognormal distributions by transforming the lognormal data. Three approaches were based on generalized confidence intervals (GCI) and adjusted method of variance estimates recovery (adjusted MOVER). A Monte Carlo simulation was used to assess the coverage probability and average length. The simulation study found that the adjusted MOVER approach based on Angus’s conservative method (AM2) is appropriate and had the smallest coverage error in all of the scenarios. The generalized confidence interval approach (GCI) had the second smallest coverage error and had the smallest average lengths among the three approaches when the coverage probabilities were close to nominal level 0.95. Real data examples illustrate this approach.

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