dc.contributor.author | Steinsland, Ingelin | |
dc.contributor.author | Larsen, Camilla Thorrud | |
dc.contributor.author | Roulin, Alexandre | |
dc.contributor.author | Jensen, Henrik | |
dc.date.accessioned | 2017-11-01T07:27:00Z | |
dc.date.available | 2017-11-01T07:27:00Z | |
dc.date.created | 2014-04-25T20:23:52Z | |
dc.date.issued | 2014 | |
dc.identifier.citation | Evolution. 2014, 68 (6), 1735-1747. | nb_NO |
dc.identifier.issn | 0014-3820 | |
dc.identifier.uri | http://hdl.handle.net/11250/2463309 | |
dc.description.abstract | Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Wiley | nb_NO |
dc.title | Quantitative genetic modeling and inference in the presence of nonignorable missing data | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.pagenumber | 1735-1747 | nb_NO |
dc.source.volume | 68 | nb_NO |
dc.source.journal | Evolution | nb_NO |
dc.source.issue | 6 | nb_NO |
dc.identifier.doi | 10.1111/evo.12380 | |
dc.identifier.cristin | 1129986 | |
dc.relation.project | Norges forskningsråd: 191847 | nb_NO |
dc.relation.project | Norges forskningsråd: 221956 | nb_NO |
dc.relation.project | Norges forskningsråd: 223257 | nb_NO |
dc.description.localcode | This is the peer reviewed version of the following article: [Quantitative genetic modeling and inference in the presence of nonignorable missing data], which has been published in final form at [http://onlinelibrary.wiley.com/doi/10.1111/evo.12380/abstract]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. | nb_NO |
cristin.unitcode | 194,63,15,0 | |
cristin.unitcode | 194,63,20,0 | |
cristin.unitcode | 194,66,10,0 | |
cristin.unitname | Institutt for matematiske fag | |
cristin.unitname | Institutt for elkraftteknikk | |
cristin.unitname | Institutt for biologi | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |