Increased Statistical Efficiency in a Lognormal Mean Model
Within the context of clinical and other scientific research, a substantial need exists for an accurate determination of the point estimate in a lognormal mean model, given that highly skewed data are often present. As such, logarithmic transformations are often advocated to achieve the assumptions...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | Journal of Probability and Statistics |
| Online Access: | http://dx.doi.org/10.1155/2014/964197 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832562727738933248 |
|---|---|
| author | Grant H. Skrepnek Ashok Sahai |
| author_facet | Grant H. Skrepnek Ashok Sahai |
| author_sort | Grant H. Skrepnek |
| collection | DOAJ |
| description | Within the context of clinical and other scientific research, a substantial need exists for an accurate determination of the point estimate in a lognormal mean model, given that highly skewed data are often present. As such, logarithmic transformations are often advocated to achieve the assumptions of parametric statistical inference. Despite this, existing approaches that utilize only a sample’s mean and variance may not necessarily yield the most efficient estimator. The current investigation developed and tested an improved efficient point estimator for a lognormal mean by capturing more complete information via the sample’s coefficient of variation. Results of an empirical simulation study across varying sample sizes and population standard deviations indicated relative improvements in efficiency of up to 129.47 percent compared to the usual maximum likelihood estimator and up to 21.33 absolute percentage points above the efficient estimator presented by Shen and colleagues (2006). The relative efficiency of the proposed estimator increased particularly as a function of decreasing sample size and increasing population standard deviation. |
| format | Article |
| id | doaj-art-4184c93cff134c1e84e13a001ea80093 |
| institution | Kabale University |
| issn | 1687-952X 1687-9538 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Probability and Statistics |
| spelling | doaj-art-4184c93cff134c1e84e13a001ea800932025-02-03T01:21:51ZengWileyJournal of Probability and Statistics1687-952X1687-95382014-01-01201410.1155/2014/964197964197Increased Statistical Efficiency in a Lognormal Mean ModelGrant H. Skrepnek0Ashok Sahai1College of Pharmacy & Peggy and Charles Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, 1110 North Stonewall Avenue, Oklahoma City, OK 73126-0901, USADepartment of Mathematics & Statistics, Faculty of Science and Technology, The University of the West Indies, St. Augustine Campus, Debe, Trinidad and TobagoWithin the context of clinical and other scientific research, a substantial need exists for an accurate determination of the point estimate in a lognormal mean model, given that highly skewed data are often present. As such, logarithmic transformations are often advocated to achieve the assumptions of parametric statistical inference. Despite this, existing approaches that utilize only a sample’s mean and variance may not necessarily yield the most efficient estimator. The current investigation developed and tested an improved efficient point estimator for a lognormal mean by capturing more complete information via the sample’s coefficient of variation. Results of an empirical simulation study across varying sample sizes and population standard deviations indicated relative improvements in efficiency of up to 129.47 percent compared to the usual maximum likelihood estimator and up to 21.33 absolute percentage points above the efficient estimator presented by Shen and colleagues (2006). The relative efficiency of the proposed estimator increased particularly as a function of decreasing sample size and increasing population standard deviation.http://dx.doi.org/10.1155/2014/964197 |
| spellingShingle | Grant H. Skrepnek Ashok Sahai Increased Statistical Efficiency in a Lognormal Mean Model Journal of Probability and Statistics |
| title | Increased Statistical Efficiency in a Lognormal Mean Model |
| title_full | Increased Statistical Efficiency in a Lognormal Mean Model |
| title_fullStr | Increased Statistical Efficiency in a Lognormal Mean Model |
| title_full_unstemmed | Increased Statistical Efficiency in a Lognormal Mean Model |
| title_short | Increased Statistical Efficiency in a Lognormal Mean Model |
| title_sort | increased statistical efficiency in a lognormal mean model |
| url | http://dx.doi.org/10.1155/2014/964197 |
| work_keys_str_mv | AT granthskrepnek increasedstatisticalefficiencyinalognormalmeanmodel AT ashoksahai increasedstatisticalefficiencyinalognormalmeanmodel |