Show simple item record

dc.contributor.authorWalker, Neff
dc.contributor.authorCatrambone, Richard
dc.date.accessioned2004-12-01T16:14:33Z
dc.date.available2004-12-01T16:14:33Z
dc.date.issued1992
dc.identifier.urihttp://hdl.handle.net/1853/3662
dc.description.abstractRegression analysis is increasingly being used to provide confirmatory evidence for models of human performance. The amount of information made available to judge these models is reduced because clearly established standards in the techniques of performing and reporting regression analysis is lacking. This paper addresses two primary problems in regression analysis: (1) aggregation of data and (2) the aggregation of variables into composite models. The paper provides examples of the misuse of regression techniques and recommends ways that the amount of information made available to evaluate the model being tested can be maximized in analysis and reporting.en
dc.format.extent3340564 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technologyen
dc.relation.ispartofseriesGVU Technical Report;GIT-GVU-92-07
dc.subjectRegressionen
dc.subjectPerformance modelsen
dc.subjectAggregation biasen
dc.titleAggregation Bias and the Use of Regression in Evaluating Models of Human Performanceen
dc.typeTechnical Reporten


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record