Show simple item record

dc.contributor.authorOnyango, Nelson Owuor
dc.date.accessioned2013-06-23T12:19:48Z
dc.date.available2013-06-23T12:19:48Z
dc.date.issued2009
dc.identifier.citationNelson Owuor Onyango (2009). On the Linear Mixed Effects Regression (lmer) R Function for Nested Animal Breeding Data. CS-BIGS 4(1): 44-58en
dc.identifier.urihttp://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/38574
dc.description.abstractThis work highlights aspects of the R lmer function for a case where the dataset is nested, highly unbalanced, involves mixed effects and repeated measurements. The lmer function is part of the lme4 package of the statistical software R. The dataset used in the study is simulated from a survey of cow milk off takes from a group of Herds in Uganda, Africa. The purpose of the survey was to identify quality breeds of African Indigenous cattle for purposes of genetic breeding following the difficulties involved in implantation of foreign breeds of cattle in Africa. The work highlights the use of mixed model analysis in the context of animal breed selection. The exposition is accessible to readers with an intermediate background in statistics. Some previous exposure to R is helpful as well as some familiarity with mixed models.en
dc.language.isoenen
dc.titleOn the Linear Mixed Effects Regression (lmer) R Function for Nested Animal Breeding Dataen
dc.typeArticleen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record