IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v28y1999i2p123-153.html

Assessing Direct and Indirect Effects in Multilevel Designs with Latent Variables

Author

Listed:
  • STEPHEN W. RAUDENBUSH

    (University of Michigan)

  • ROBERT SAMPSON

    (University of Chicago)

Abstract

Researchers commonly ask whether relationships between exogenous predictors, X, and outcomes, Y, are mediated by a third set of variables, Z. Simultaneous equations decompose the relationship between X and Y into an indirect component, operating through Z, and a direct component, the relationship between X and Y given Z. Often, X, Y, and/or Z are measured with error. Structural equation modeling is widely used in this scenario. However, sociological data commonly have a nested structure (students within schools, residents within local areas). Hierarchical linear models represent such multilevel data well and can handle errors of measurement, but have not incorporated simultaneous equations for direct and indirect effects. This article incorporates the study of such mediated effects into the hierarchical linear model, naturally extending the analysis to include unbalanced, multilevel designs and missing data. The authors illustrate the approach by examining the extent to which neighborhood social control mediates the relationship between neighborhood social composition and violence in Chicago.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:somere:v:28:y:1999:i:2:p:123-153
    DOI: 10.1177/0049124199028002001
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124199028002001
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124199028002001?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. Roderick McDonald, 1993. "A general model for two-level data with responses missing at random," Psychometrika, Springer;The Psychometric Society, vol. 58(4), pages 575-585, December.
    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.
    3. Francisco L. Rivera-Batiz, 1992. "Quantitative Literacy and the Likelihood of Employment among Young Adults in the United States," Journal of Human Resources, University of Wisconsin Press, vol. 27(2), pages 313-328.
    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. Glass, Thomas A. & McAtee, Matthew J., 2006. "Behavioral science at the crossroads in public health: Extending horizons, envisioning the future," Social Science & Medicine, Elsevier, vol. 62(7), pages 1650-1671, April.
    2. Joop J. Hox & Cora J. M. Maas & Matthieu J. S. Brinkhuis, 2010. "The effect of estimation method and sample size in multilevel structural equation modeling," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(2), pages 157-170, May.

    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. 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.
    2. Ünal, Zehra E. & Kartal, Gamze & Ulusoy, Serra & Ala, Aslı M. & Yilmaz, Munube & Geary, David C., 2023. "Relative contributions of g and basic domain-specific mathematics skills to complex mathematics competencies," Intelligence, Elsevier, vol. 101(C).
    3. David A Green & W Craig Riddell, "undated". "Literacy, Numeracy and Labour Market Outcomes in Canada," Canadian International Labour Network Working Papers 47, McMaster University.
    4. 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.
    5. Piotr Tarka, 2018. "An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 313-354, January.
    6. Garcia-Aracil, Adela & Winter, Carolyn, 2006. "Gender and ethnicity differentials in school attainment and labor market earnings in Ecuador," World Development, Elsevier, vol. 34(2), pages 289-307, February.
    7. 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.
    8. 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.
    9. Lorenzo Cappellari & Claudio Lucifora & Dario Pozzoli, 2012. "Determinants of grades in maths for students in economics," Education Economics, Taylor & Francis Journals, vol. 20(1), pages 1-17, February.
    10. Fortin, Nicole & Parent, Daniel, 2009. "Employee Training in Canada," CLSSRN working papers clsrn_admin-2009-10, Vancouver School of Economics, revised 02 Feb 2009.
    11. Barry T. Hirsch & David A. Macpherson, 2004. "Wages, Sorting on Skill, and the Racial Composition of Jobs," Journal of Labor Economics, University of Chicago Press, vol. 22(1), pages 189-210, January.
    12. Finnie, Ross & Meng, Ronald, 2006. "The Importance of Functional Literacy: Reading and Math Skills and Labour Market Outcomes of High School Drop-outs," Analytical Studies Branch Research Paper Series 2006275e, Statistics Canada, Analytical Studies Branch.
    13. John Micklewright & Sylke V. Schnepf & Pedro N. Silva, 2010. "Peer effects and measurement error: the impact of sampling variation in school survey data," DoQSS Working Papers 10-13, Quantitative Social Science - UCL Social Research Institute, University College London.
    14. 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.
    15. H. J. Holzer, "undated". "Employer skill needs and labor market outcome by race and gender," Institute for Research on Poverty Discussion Papers 1087-96, University of Wisconsin Institute for Research on Poverty.
    16. Peter W. Schuhmann & KimMarie McGoldrick & Robert T. Burrus, 2005. "Student Quantitative Literacy: Importance, Measurement, and Correlation with Economic Literacy," The American Economist, Sage Publications, vol. 49(1), pages 49-65, March.
    17. Jiajuan Liang & Peter Bentler, 2004. "An EM algorithm for fitting two-level structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 69(1), pages 101-122, March.
    18. Fabra, M. Eugenia & Camisón, Cesar, 2009. "Direct and indirect effects of education on job satisfaction: A structural equation model for the Spanish case," Economics of Education Review, Elsevier, vol. 28(5), pages 600-610, October.
    19. Wößmann, Ludger, 2001. "New Evidence on the Missing Resource-Performance Link in Education," Kiel Working Papers 1051, Kiel Institute for the World Economy.

    More about this item

    Statistics

    Access and download statistics

    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:28:y:1999:i:2:p:123-153. 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.