title: Methods for comparing the means of two independent log-normal samples.
abstract: Standard methods of using the t-test and the Wilcoxon test have deficiencies for comparing the means of two skewed log-normal samples. In this paper, we propose two new methods to overcome these deficiencies: (1) a likelihood-based approach and (2) a bootstrap-based approach. Our simulation study shows that the likelihood-based approach is the best in terms of the type I error rate and power when data follow a log-normal distribution.
authors.affiliation: Department of Medicine, Indiana University School of Medicine, Indianapolis 46202-5200, USA.
authors.forename: X H
authors.initials: XH
authors.lastname: Zhou
authors.forename: S
authors.initials: S
authors.lastname: Gao
authors.forename: S L
authors.initials: SL
authors.lastname: Hui
mesh_terms: D001699:Biometry / Q000379:methods; D003365:Costs and Cost Analysis; D003627:Data Interpretation, Statistical; D003922:Diabetes Mellitus, Type 1 / Q000188:drug therapy / Q000191:economics; D007297:Inpatients; D008499:Medical Records; D015233:Models, Statistical; D010045:Outpatients; D011336:Probability; D012016:Reference Values; D015203:Reproducibility of Results; D012107:Research Design; D014481:United States