Skip to main content

Part of the book series: Monte Verità ((MV))

  • 120 Accesses

Abstract

Some of the surveys conducted by the Swiss Federal Statistical Office (SFSO) are of a longitudinal nature, i.e. surveys where the units of a sample are observed repeatedly through time, one of the focuses of interest being change in the characteristics of a population. Typically, simple estimates of change are calculated for the population and for a large number of sub-populations. In general this is unsatisfactory, as the estimates for the sub-populations are often not accurate enough to detect changes of practical relevance.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Binder, D.A. (1983). On the Variances of Asymptotically Normal Estimators from Complex Surveys. International Statistical Review, 51, 279–292.

    Article  MathSciNet  MATH  Google Scholar 

  • Comment, T., Hulliger, B. and Ries, A. (1996). Gewichtungsverfahren für die Schweizerische Arbeitskräfteerhebung (1991–1995). Methodenbericht KPS. Bundesamt für Statistik, Bern, Schweiz.

    Google Scholar 

  • Diggle, P.J., Liang, K.-Y. and Zeger, S.L. (1994). Analysis of Longitudinal Data, Oxford: Oxford University Press.

    Google Scholar 

  • Glonek, G.F.V. and McCullagh, P. (1994). Multivariate logistic models. Technical Report 94–31. School of Information Science and Technology, Flinders University of South Australia, Adelaide.

    Google Scholar 

  • Glonek, G.F.V. and McCullagh, P. (1995). Multivariate logistic models. Journal of the Royal Statistical Society, Series B, 57, 533–546.

    MATH  Google Scholar 

  • Lang, J.B. (1996). Maximum likelihood methods for a generalized class of log-linear models. Annals of Statistics, 24, 726–752.

    Article  MathSciNet  MATH  Google Scholar 

  • McCullagh, P. and Nelder, J.A. (1989). Generalized Linear Models, 2nd edn. London: Chapman and Hall.

    MATH  Google Scholar 

  • Wolter, K.M. (1985). Introduction to variance estimation, New York: Springer-Verlag.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer Basel AG

About this paper

Cite this paper

Salamin, PA. (1997). Longitudinal Analysis of Swiss Labour Force Survey Data. In: Malaguerra, C., Morgenthaler, S., Ronchetti, E. (eds) Conference on Statistical Science Honouring the Bicentennial of Stefano Franscini’s Birth. Monte Verità. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-8930-8_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-0348-8930-8_14

  • Publisher Name: Birkhäuser, Basel

  • Print ISBN: 978-3-0348-9832-4

  • Online ISBN: 978-3-0348-8930-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics