Score tests in a generalized linear model with surrogate covariates
dc.contributor.author | Sepanski, J. H. | en_US |
dc.date.accessioned | 2006-04-10T15:05:17Z | |
dc.date.available | 2006-04-10T15:05:17Z | |
dc.date.issued | 1992-09-03 | en_US |
dc.identifier.citation | Sepanski, J. H. (1992/09/03)."Score tests in a generalized linear model with surrogate covariates." Statistics & Probability Letters 15(1): 1-10. <http://hdl.handle.net/2027.42/29852> | en_US |
dc.identifier.uri | http://www.sciencedirect.com/science/article/B6V1D-45DHJ6H-22/2/1a002c214429195d88ff7606ec3241f2 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/29852 | |
dc.description.abstract | We consider generalized linear models where a predictor is measured with error. The efficient score test for the effect of that predictor depends on the regression of the true predictor on its observed surrogate. Using validation data, we estimate the regression by nonparametric techniques. The resulting semiparametric score test is shown to be nearly asymptotically efficient. | en_US |
dc.format.extent | 655685 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Elsevier | en_US |
dc.title | Score tests in a generalized linear model with surrogate covariates | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Statistics and Numeric Data | en_US |
dc.subject.hlbsecondlevel | Mathematics | en_US |
dc.subject.hlbtoplevel | Social Sciences | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Statistics and Management Science, School of Business Administration, University of Michigan, Ann Arbor, MI, USA | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/29852/1/0000199.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/0167-7152(92)90277-C | en_US |
dc.identifier.source | Statistics & Probability Letters | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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