Improved Small Sample Inference on the Ratio of Two Coefficients of Variation of Two Independent Lognormal Distributions
Joint Authors
Wong, Augustine C. M.
Jiang, L.
Source
Journal of Probability and Statistics
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-03
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Without the ability to use research tools and procedures that yield consistent measurements, researchers would be unable to draw conclusions, formulate theories, or make claims about generalizability of their results.
In statistics, the coefficient of variation is commonly used as the index of reliability of measurements.
Thus, comparing coefficients of variation is of special interest.
Moreover, the lognormal distribution has been frequently used for modeling data from many fields such as health and medical research.
In this paper, we proposed a simulated Bartlett corrected likelihood ratio approach to obtain inference concerning the ratio of two coefficients of variation for lognormal distribution.
Simulation studies show that the proposed method is extremely accurate even when the sample size is small.
American Psychological Association (APA)
Wong, Augustine C. M.& Jiang, L.. 2019. Improved Small Sample Inference on the Ratio of Two Coefficients of Variation of Two Independent Lognormal Distributions. Journal of Probability and Statistics،Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1186862
Modern Language Association (MLA)
Wong, Augustine C. M.& Jiang, L.. Improved Small Sample Inference on the Ratio of Two Coefficients of Variation of Two Independent Lognormal Distributions. Journal of Probability and Statistics No. 2019 (2019), pp.1-7.
https://search.emarefa.net/detail/BIM-1186862
American Medical Association (AMA)
Wong, Augustine C. M.& Jiang, L.. Improved Small Sample Inference on the Ratio of Two Coefficients of Variation of Two Independent Lognormal Distributions. Journal of Probability and Statistics. 2019. Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1186862
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186862