IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v39y2010i1p83-108.html
   My bibliography  Save this article

Fitting Log-Linear Models to Contingency Tables From Surveys With Complex Sampling Designs: An Investigation of the Clogg-Eliason Approach

Author

Listed:
  • Chris Skinner

    (University of Southampton, Southampton, United Kingdom)

  • Louis-André Vallet

    (CNRS & CREST, Paris, France)

Abstract

Clogg and Eliason (1987) proposed a simple method for taking account of survey weights when fitting log-linear models to contingency tables. This article investigates the properties of this method. A rationale is provided for the method when the weights are constant within the cells of the table. For more general cases, however, it is shown that the standard errors produced by the method are invalid, contrary to claims in the literature. The method is compared to the pseudo maximum likelihood method both theoretically and through an empirical study of social mobility relating daughter’s class to father’s class using survey data from France. The method of Clogg and Eliason is found to underestimate standard errors systematically. The article concludes by recommending against the use of this method, despite its simplicity. The limitations of the method may be overcome by using the pseudo maximum likelihood method.

Suggested Citation

  • Chris Skinner & Louis-André Vallet, 2010. "Fitting Log-Linear Models to Contingency Tables From Surveys With Complex Sampling Designs: An Investigation of the Clogg-Eliason Approach," Sociological Methods & Research, , vol. 39(1), pages 83-108, August.
    • Handle: RePEc:sae:somere:v:39:y:2010:i:1:p:83-108
    DOI: 10.1177/0049124110366239
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124110366239
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124110366239?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
    ---><---

    References listed on IDEAS

    as
    1. Lumley, Thomas, 2004. "Analysis of Complex Survey Samples," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 9(i08).
    2. Patterson B.H. & Dayton C.M. & Graubard B.I., 2002. "Latent Class Analysis of Complex Sample Survey Data: Application to Dietary Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 721-741, September.
    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. Skinner, Chris J., 2018. "Analysis of categorical data for complex surveys," LSE Research Online Documents on Economics 89707, 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. Skinner, Chris J. & Vallet, L.-A., 2010. "Fitting log-linear models to contingency tables from surveys with complex sampling designs: an investigation of the Clogg-Eliason approach," LSE Research Online Documents on Economics 39118, London School of Economics and Political Science, LSE Library.
    2. Maciej Berk{e}sewicz & Herman Cherniaiev & Robert Pater, 2021. "Estimating the number of entities with vacancies using administrative and online data," Papers 2106.03263, arXiv.org.
    3. J. Michael Brick & Michael E. Jones, 2008. "Propensity to respond and nonresponse bias," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 51-73.
    4. Jacques Muthusi & Samuel Mwalili & Peter Young, 2019. "%svy_logistic_regression: A generic SAS macro for simple and multiple logistic regression and creating quality publication-ready tables using survey or non-survey data," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-14, September.
    5. Bas Donkers & Richard Paap & Jedid‐Jah Jonker & Philip Hans Franses, 2006. "Deriving target selection rules from endogenously selected samples," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 549-562, July.
    6. Jonathan Wakefield & Taylor Okonek & Jon Pedersen, 2020. "Small Area Estimation for Disease Prevalence Mapping," International Statistical Review, International Statistical Institute, vol. 88(2), pages 398-418, August.
    7. Alex Fenton, 2013. "Small-area measures of income poverty," CASE Papers case173, Centre for Analysis of Social Exclusion, LSE.
    8. repec:cep:sticas:/173 is not listed on IDEAS
    9. Mei‐Chih Meg Tseng & Yi‐Ping Lin & Fu‐Chang Hu & Tsun‐Jen Cheng, 2013. "Risks Perception of Electromagnetic Fields in Taiwan: The Influence of Psychopathology and the Degree of Sensitivity to Electromagnetic Fields," Risk Analysis, John Wiley & Sons, vol. 33(11), pages 2002-2012, November.
    10. Raphael Nishimura & James Wagner & Michael Elliott, 2016. "Alternative Indicators for the Risk of Non-response Bias: A Simulation Study," International Statistical Review, International Statistical Institute, vol. 84(1), pages 43-62, April.
    11. Jeroen K. Vermunt & Jay Magidson, 2007. "Latent Class Analysis With Sampling Weights," Sociological Methods & Research, , vol. 36(1), pages 87-111, August.
    12. Camelia Herman & Colleen M. Leonard & Perpetua Uhomoibhi & Mark Maire & Delynn Moss & Uwem Inyang & Ado Abubakar & Abiodun Ogunniyi & Nwando Mba & Stacie M. Greby & McPaul I. Okoye & Nnaemeka C. Iriem, 2023. "Non-falciparum malaria infection and IgG seroprevalence among children under 15 years in Nigeria, 2018," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    13. Elijah O. Onsomu & DaKysha Moore & Benta A. Abuya & Peggy Valentine & Vanessa Duren-Winfield, 2013. "Importance of the Media in Scaling-Up HIV Testing in Kenya," SAGE Open, , vol. 3(3), pages 21582440134, July.
    14. Vinas-Forcade, Jennifer & Seijas, María Noé, 2021. "To teach or not to teach: Negative selection into the teaching profession in Uruguay," International Journal of Educational Development, Elsevier, vol. 84(C).
    15. Lenis, David & Ackerman, Benjamin & Stuart, Elizabeth A., 2018. "Measuring model misspecification: Application to propensity score methods with complex survey data," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 48-57.
    16. Sofia Gil-Clavel & Emilio Zagheni & Valeria Bordone, 2022. "Close Social Networks Among Older Adults: The Online and Offline Perspectives," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(3), pages 1111-1135, June.
    17. Matthew R. Williams & Terrance D. Savitsky, 2021. "Uncertainty Estimation for Pseudo‐Bayesian Inference Under Complex Sampling," International Statistical Review, International Statistical Institute, vol. 89(1), pages 72-107, April.
    18. Jeanna Parsons Leigh & Kirsten Fiest & Rebecca Brundin-Mather & Kara Plotnikoff & Andrea Soo & Emma E Sypes & Liam Whalen-Browne & Sofia B Ahmed & Karen E A Burns & Alison Fox-Robichaud & Shelly Kupsc, 2020. "A national cross-sectional survey of public perceptions of the COVID-19 pandemic: Self-reported beliefs, knowledge, and behaviors," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-18, October.
    19. Wang, Jianqiang C., 2012. "Sample distribution function based goodness-of-fit test for complex surveys," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 664-679.
    20. Alejandro Aybar-Flores & Alvaro Talavera & Elizabeth Espinoza-Portilla, 2023. "Predicting the HIV/AIDS Knowledge among the Adolescent and Young Adult Population in Peru: Application of Quasi-Binomial Logistic Regression and Machine Learning Algorithms," IJERPH, MDPI, vol. 20(7), pages 1-29, March.
    21. Joseph R Starnes & Chiara Di Gravio & Rebecca Irlmeier & Ryan Moore & Vincent Okoth & Ash Rogers & Daniele J Ressler & Troy D Moon, 2021. "Characterizing multidimensional poverty in Migori County, Kenya and its association with depression," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-10, November.

    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:sae:somere:v:39:y:2010:i:1:p:83-108. 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: SAGE Publications (email available below). General contact details of provider: .

    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.