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Tests for an upper percentile of a lognormal distribution based on samples with multiple detection limits and sample-size calculation.
Krishnamoorthy K; Mathew T; Xu Z
Ann Occup Hyg 2013 Nov; 57(9):1200-1212
The problem of determining sample size for testing an upper percentile of a lognormal distribution based on samples with multiple detection limits is considered. Two tests, the signed likelihood ratio test and another test based on a pivotal statistic, are outlined. These tests are very satisfactory in controlling type I error rates and comparable in terms of powers. Procedures and R codes for calculating sample sizes for these tests to attain a specified power are given. It is noted that for guaranteeing a given power, increased sample size is necessary due to the presence of detection limits, and the required sample size goes up as the proportion of non-detects goes up. It is also noted that in the multiple detection limit scenario, sample-size determination does not require knowledge of the proportions of non-detects that are expected to be below the individual detection limits; rather, what is required is a knowledge of the overall percentage of non-detects that is to be expected in the entire sample. Sample-size calculation is illustrated using a practical situation.
Sampling; Mathematical-models; Statistical-analysis; Author Keywords: maximum likelihood estimates; non-central t distribution; pivotal test; powers; signed likelihood ratio test
Kalimuthu Krishnamoorthy, Department of Mathematics, University of Louisiana at Lafayette, Lafayette, LA 70508-1010
Issue of Publication
Annals of Occupational Hygiene
LA; MD; TX
University of Maryland, Baltimore
Page last reviewed: April 8, 2022
Content source: National Institute for Occupational Safety and Health Education and Information Division