| dc.contributor |
Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, MI 48109, U.S.A. |
|
| dc.contributor |
Department of Biostatistics, St Jude Children's Research Hospital, 332 North Lauderdale St., Memphis, TN 38105, U.S.A. ; Department of Biostatistics, St Jude Children's Research Hospital, 332 North Lauderdale Street, Memphis, TN 38105, U.S.A. |
|
| dc.contributor |
SASIT, Atkinson Faculty of Liberal and Professional Studies, York University, 4700 Keele St., North York, Ontario, Canada M3J 1P3 |
|
| dc.creator |
Wu, Jianrong |
|
| dc.creator |
Wong, A. C. M. |
|
| dc.creator |
Wei, Wei |
|
| dc.date |
2007-07-11T18:15:43Z |
|
| dc.date |
2007-07-11T18:15:43Z |
|
| dc.date |
2006-06-30 |
|
| dc.date.accessioned |
2022-05-19T13:29:40Z |
|
| dc.date.available |
2022-05-19T13:29:40Z |
|
| dc.identifier |
Wu, Jianrong; Wong, A. C. M.; Wei, Wei (2006). "Interval estimation of the mean response in a log-regression model." Statistics in Medicine 25(12): 2125-2135. <http://hdl.handle.net/2027.42/55233> |
|
| dc.identifier |
0277-6715 |
|
| dc.identifier |
1097-0258 |
|
| dc.identifier |
http://hdl.handle.net/2027.42/55233 |
|
| dc.identifier |
http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=16220472&dopt=citation |
|
| dc.identifier |
16220472 |
|
| dc.identifier |
http://dx.doi.org/10.1002/sim.2329 |
|
| dc.identifier |
Statistics in Medicine |
|
| dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/117281 |
|
| dc.description |
A standard approach to the analysis of skewed response data with concomitant information is to use a log-transformation to normalize the distribution of the response variable and then conduct a log- regression analysis. However, the mean response at original scale is often of interest. El-Shaarawi and Viveros developed an interval estimation of the mean response of a log-regression model based on large sample theory. There is however very little information available in the literature on constructing such estimates when the sample size is small. In this paper, we develop a small-sample corrected interval by using the likelihood-based inference method developed by Barndorff-Nielson and Fraser et al . Simulation results show that the proposed interval provides almost exact coverage probability, even for small samples. Copyright © 2005 John Wiley & Sons, Ltd. |
|
| dc.description |
Peer Reviewed |
|
| dc.description |
http://deepblue.lib.umich.edu/bitstream/2027.42/55233/1/2329_ftp.pdf |
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| dc.format |
115491 bytes |
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| dc.format |
3118 bytes |
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| dc.format |
application/pdf |
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| dc.format |
text/plain |
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| dc.format |
application/pdf |
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| dc.publisher |
John Wiley & Sons, Ltd. |
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| dc.rights |
IndexNoFollow |
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| dc.subject |
Mathematics and Statistics |
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| dc.subject |
Medicine (General) |
|
| dc.subject |
Statistics and Numeric Data |
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| dc.subject |
Public Health |
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| dc.subject |
Health Sciences |
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| dc.subject |
Science |
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| dc.subject |
Social Sciences |
|
| dc.title |
Interval estimation of the mean response in a log-regression model |
|
| dc.type |
Article |
|