IDEAS home Printed from https://ideas.repec.org/a/spr/eurpop/v16y2000i4d10.1023_a1006493723125.html
   My bibliography  Save this article

Multilevel Models in the Study of Dynamic Household Structures

Author

Listed:
  • Harvey Goldstein

    (University of London)

  • Jon Rasbash

    (University of London)

  • William Browne

    (University of London)

  • Geoffrey Woodhouse

    (University of London)

  • Michel Poulain

    (Université catholique de Louvain)

Abstract

A modelling procedure is proposed for complex, dynamic household data structures where households change composition over time. Multilevel multiple membership models are presented for such data and their application is discussed with an example.

Suggested Citation

  • Harvey Goldstein & Jon Rasbash & William Browne & Geoffrey Woodhouse & Michel Poulain, 2000. "Multilevel Models in the Study of Dynamic Household Structures," European Journal of Population, Springer;European Association for Population Studies, vol. 16(4), pages 373-387, December.
    • Handle: RePEc:spr:eurpop:v:16:y:2000:i:4:d:10.1023_a:1006493723125
    DOI: 10.1023/A:1006493723125
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1023/A:1006493723125
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1023/A:1006493723125?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ian H. Langford & Alistair H. Leyland & Jon Rasbash & Harvey Goldstein, 1999. "Multilevel Modelling of the Geographical Distributions of Diseases," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(2), pages 253-268.
    2. Geoffrey Woodhouse & Min Yang & Harvey Goldstein & Jon Rasbash, 1996. "Adjusting for Measurement Error in Multilevel Analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(2), pages 201-212, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Donata Marasini & Piero Quatto & Enrico Ripamonti, 2016. "Intuitionistic fuzzy sets in questionnaire analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 767-790, March.
    2. Harvey Goldstein & Simon Burgess & Brendon McConnell, 2006. "Modelling the Impact of Pupil Mobility on School Differences in Educational Achievement," The Centre for Market and Public Organisation 06/156, The Centre for Market and Public Organisation, University of Bristol, UK.
    3. Karl, Andrew T. & Yang, Yan & Lohr, Sharon L., 2013. "Efficient maximum likelihood estimation of multiple membership linear mixed models, with an application to educational value-added assessments," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 13-27.
    4. A., Rjumohan, 2017. "Multi-Dimensional Development – An Application of Fuzzy Set Theory to the Indian States," MPRA Paper 99208, University Library of Munich, Germany.
    5. William J. Browne, 2022. "A celebration of Harvey Goldstein’s lifetime contributions: Memories of working with Harvey Goldstein on multilevel modelling methods and applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 753-758, July.
    6. Steele, Fiona & Clarke, Paul & Kuha, Jouni, 2019. "Modeling within-household associations in household panel studies," LSE Research Online Documents on Economics 88162, London School of Economics and Political Science, LSE Library.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sehyeong Kim & Youngho Kim, 2019. "Spatially Filtered Multilevel Analysis on Spatial Determinants for Malaria Occurrence in Korea," IJERPH, MDPI, vol. 16(7), pages 1-11, April.
    2. Georges Kone & Richard Lalou & Martine Audibert & Hervé Lafarge & Stéphanie dos Santos & Jean-Yves Le Hesran, 2013. "Use of health care among the urban poor in Africa: Does the neighbourhood have an impact?," CERDI Working papers halshs-00878946, HAL.
    3. Dougal Hutchison, 2004. "The Effect of Measurement Errors on Apparent Group Level Effects in Educational Progress," Quality & Quantity: International Journal of Methodology, Springer, vol. 38(4), pages 407-424, August.
    4. Fabio Divino & Viviana Egidi & Michele Antonio Salvatore, 2009. "Geographical mortality patterns in Italy," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 20(18), pages 435-466.
    5. Darren J. Mayne & Geoffrey G. Morgan & Bin B. Jalaludin & Adrian E. Bauman, 2018. "Does Walkability Contribute to Geographic Variation in Psychosocial Distress? A Spatial Analysis of 91,142 Members of the 45 and Up Study in Sydney, Australia," IJERPH, MDPI, vol. 15(2), pages 1-24, February.
    6. Ngianga-Bakwin Kandala & Samuel O.M. Manda & William W. Tigbe & Henry Mwambi & Saverio Stranges, 2014. "Geographic distribution of cardiovascular comorbidities in South Africa: a national cross-sectional analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1203-1216, June.
    7. Peter Congdon, 2022. "Measuring Obesogenicity and Assessing Its Impact on Child Obesity: A Cross-Sectional Ecological Study for England Neighbourhoods," IJERPH, MDPI, vol. 19(17), pages 1-17, August.
    8. Stephen W. Raudenbush & Robert Sampson, 1999. "Assessing Direct and Indirect Effects in Multilevel Designs with Latent Variables," Sociological Methods & Research, , vol. 28(2), pages 123-153, November.
    9. Congdon, Peter, 2006. "A model for non-parametric spatially varying regression effects," Computational Statistics & Data Analysis, Elsevier, vol. 50(2), pages 422-445, January.
    10. Maaike Jappens & Jan Van Bavel, 2012. "Regional family cultures and child care by grandparents in Europe," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 27(4), pages 85-120.
    11. Salule Masangwi & Neil Ferguson & Anthony Grimason & Tracy Morse & Lawrence Kazembe, 2015. "The Pattern of Variation between Diarrhea and Malaria Coexistence with Corresponding Risk Factors in, Chikhwawa, Malawi: A Bivariate Multilevel Analysis," IJERPH, MDPI, vol. 12(7), pages 1-16, July.
    12. Moraga, Paula & Lawson, Andrew B., 2012. "Gaussian component mixtures and CAR models in Bayesian disease mapping," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1417-1433.
    13. Artur Pokropek, 2015. "Phantom Effects in Multilevel Compositional Analysis," Sociological Methods & Research, , vol. 44(4), pages 677-705, November.
    14. William J. Browne, 2022. "A celebration of Harvey Goldstein’s lifetime contributions: Memories of working with Harvey Goldstein on multilevel modelling methods and applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 753-758, July.
    15. Glory Chidumwa & Innocent Maposa & Paul Kowal & Lisa K. Micklesfield & Lisa J. Ware, 2021. "Bivariate Joint Spatial Modeling to Identify Shared Risk Patterns of Hypertension and Diabetes in South Africa: Evidence from WHO SAGE South Africa Wave 2," IJERPH, MDPI, vol. 18(1), pages 1-12, January.
    16. Keenan A. Pituch, 1999. "Describing School Effects with Residual Terms," Evaluation Review, , vol. 23(2), pages 190-211, April.
    17. Francisca Richter & B. Brorsen, 2006. "Aggregate Versus Disaggregate Data in Measuring School Quality," Journal of Productivity Analysis, Springer, vol. 25(3), pages 279-289, June.
    18. Micklewright, John & Schnepf, Sylke V. & Silva, Pedro N., 2012. "Peer effects and measurement error: The impact of sampling variation in school survey data (evidence from PISA)," Economics of Education Review, Elsevier, vol. 31(6), pages 1136-1142.
    19. Joel Karlsson & Jonas Månsson, 2014. "Getting a full-time job as a part-time unemployed: How much does spatial context matter?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 179-195, August.
    20. Georges Kone & Richard Lalou & Martine Audibert & Hervé Lafarge & Stéphanie dos Santos & Jean-Yves Le Hesran, 2013. "Use of health care among the urban poor in Africa: Does the neighbourhood have an impact?," Working Papers halshs-00878946, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:eurpop:v:16:y:2000:i:4:d:10.1023_a:1006493723125. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.