Predicting participation in higher education: a comparative evaluation of the performance of geodemographic classifications

$48.00 plus tax (Refund Policy)

Download / Buy Article:

Abstract:

Summary. 

Participation in UK higher education is modelled by using Poisson regression techniques. Models using geodemographic classifications of neighbourhoods of varying levels of detail are compared with those using variables that are directly derived from the census, using a cross-validation approach. Increasing the detail of geodemographic classifiers appears to be justified in general, although the degree of improvement becomes more marginal as the level of detail is increased. The census variable approach performs comparably, although it is argued that this depends heavily on an appropriate choice of predictors. The paper concludes by discussing these results in a broader practice-oriented and pedagogic context.

Keywords: Geodemographics; Higher education; Participation; Poisson regression; Postcodes

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1467-985X.2010.00641.x

Affiliations: 1: University of Leicester, UK 2: University College London, UK 3: Dr Foster Research, London, UK

Publication date: January 1, 2011

Related content

Tools

Favourites

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more