Inferences on the common mean of several log-normal populations: the generalized variable approach.
This paper proposes a novel approach for the confidence interval estimation and hypothesis testing of the common mean of several log-normal populations using the concept of generalized variable. Simulation studies demonstrate that the proposed approach can provide confidence intervals with satisfying coverage probabilities and can perform hypothesis testing with satisfying type-I error control even at small sample sizes. Overall, it is superior to the large sample approach. The proposed method is illustrated using two examples.
Department of Biostatistics, University at Buffalo, 249 Farber Hall, 3435 Main St. Bldg. 26, Buffalo, NY 142 14, USA. ltian@buffalo.edu
Lili
L
Tian
Jianrong
J
Wu
D000428:Alcohol Drinking / Q000378:metabolism; D044383:Black People; D003198:Computer Simulation; D016001:Confidence Intervals; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D017048:Health Care Costs; D006801:Humans; D008297:Male; D004364:Pharmaceutical Preparations / Q000378:metabolism; D011897:Random Allocation; D044465:White People
D004364:Pharmaceutical Preparations