Multivariate methods in historical data: An Optimal Scaling Analysis with Missing Categorical Data

  1. Cecilio Mar Molinero 1
  2. Fabiola Portillo 2
  1. 1 University of Kent, UK, and Universitat Autonoma de Barcelona, Spain,
  2. 2 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Actes de conférence:
ASMDA 2013 Book of Abstracts. 15th Applied Stochastic Models and Data Analysis International Conference With Demographics 2013 Workshop. 25 – 28 June 2013 Mataró (Barcelona), Spain
  1. Christos H. Skiadas (ed. lit.)

Éditorial: ISAST: International Society for the Advancement of Science and Technology

ISBN: 978-618-80698-2-4

Année de publication: 2013

Pages: 151

Congreso: 15th Applied Stochastic Models and Data Analysis International Conference With Demographics 2013 Workshop. 25 – 28 June 2013 Mataró (Barcelona), Spain

Type: Communication dans un congrès

Dépôt institutionnel: lock_openAccès ouvert Editor

Résumé

The information contained in a database from the Spanish railwaycompany MZA for the period 1882-1889 is explored by means of OptimalScaling methods. The sample includes 992 employees who joined theMadrid-Atocha workshop during that period and contains missingqualitative values. A technique that combines correspondence analysiswith the k-means clustering algorithm is implemented to impute thesevalues, maximizing internal consistency as measured by Guttman’ssquared correlation ratio. The results show two characteristics observedin other studies of labour relations: the existence of «ports of entry» forworkers at low levels of qualification and long-term labour relations