IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v39y2014i3p167-179.html
   My bibliography  Save this article

Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models

Author

Listed:
  • Amy E. Wagler

    (The University of Texas at El Paso)

Abstract

Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for estimating the heterogeneity due to clustering on a scale that is easy to interpret. The performance of the proposed asymptotic intervals and percentile bootstrap intervals are compared by simulations and in an application.

Suggested Citation

  • Amy E. Wagler, 2014. "Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models," Journal of Educational and Behavioral Statistics, , vol. 39(3), pages 167-179, June.
    • Handle: RePEc:sae:jedbes:v:39:y:2014:i:3:p:167-179
    DOI: 10.3102/1076998614529159
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/1076998614529159
    Download Restriction: no
    File URL: https://libkey.io/10.3102/1076998614529159?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. Schenker N. & Gentleman J. F., 2001. "On Judging the Significance of Differences by Examining the Overlap Between Confidence Intervals," The American Statistician, American Statistical Association, vol. 55, pages 182-186, August.
    2. Klaus Larsen & Jørgen Holm Petersen & Esben Budtz-Jørgensen & Lars Endahl, 2000. "Interpreting Parameters in the Logistic Regression Model with Random Effects," Biometrics, The International Biometric Society, vol. 56(3), pages 909-914, 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. Cristiano C. Santos & Rosangela H. Loschi, 2017. "Maximum likelihood estimation and parameter interpretation in elliptical mixed logistic regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 209-230, March.

    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. Alejandra Tapia & Victor Leiva & Maria del Pilar Diaz & Viviana Giampaoli, 2019. "Influence diagnostics in mixed effects logistic regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 920-942, September.
    2. Domínguez-Torreiro, Marcos & Soliño, Mario, 2011. "Provided and perceived status quo in choice experiments: Implications for valuing the outputs of multifunctional rural areas," Ecological Economics, Elsevier, vol. 70(12), pages 2523-2531.
    3. Tim Goedemé & Karel Van den Bosch & Lina Salanauskaite & Gerlinde Verbist, 2013. "Testing the Statistical Significance of Microsimulation Results: Often Easier than You Think. A Technical Note," ImPRovE Working Papers 13/10, Herman Deleeck Centre for Social Policy, University of Antwerp.
    4. Yao Xiao & Chengzhen Meng & Suli Huang & Yanran Duan & Gang Liu & Shuyuan Yu & Ji Peng & Jinquan Cheng & Ping Yin, 2021. "Short-Term Effect of Temperature Change on Non-Accidental Mortality in Shenzhen, China," IJERPH, MDPI, vol. 18(16), pages 1-14, August.
    5. Thomas Yee & Alfian Hadi, 2014. "Row–column interaction models, with an R implementation," Computational Statistics, Springer, vol. 29(6), pages 1427-1445, December.
    6. Henry R. Scharf & Xinyi Lu & Perry J. Williams & Mevin B. Hooten, 2022. "Constructing Flexible, Identifiable and Interpretable Statistical Models for Binary Data," International Statistical Review, International Statistical Institute, vol. 90(2), pages 328-345, August.
    7. Andrew Kerner & Morten Jerven & Alison Beatty, 2017. "Does it pay to be poor? Testing for systematically underreported GNI estimates," The Review of International Organizations, Springer, vol. 12(1), pages 1-38, March.
    8. McKendree, Melissa G.S. & Olynk Widmar, Nicole & Ortega, David L. & Foster, Kenneth A., 2013. "Consumer Preferences for Verified Pork-Rearing Practices in the Production of Ham Products," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(3), pages 1-21.
    9. Agne Ulyte & Wenjia Wei & Holger Dressel & Oliver Gruebner & Viktor von Wyl & Caroline Bähler & Eva Blozik & Beat Brüngger & Matthias Schwenkglenks, 2020. "Variation of colorectal, breast and prostate cancer screening activity in Switzerland: Influence of insurance, policy and guidelines," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-15, April.
    10. Kumar, Santosh & Nahlen, Bernard, 2023. "Intergenerational persistence of health: Evidence from India," Economics Letters, Elsevier, vol. 224(C).
    11. Paul Mwebaze & Jeff Bennett & Nigel W. Beebe & Gregor J. Devine & Paul Barro, 2018. "Economic Valuation of the Threat Posed by the Establishment of the Asian Tiger Mosquito in Australia," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(2), pages 357-379, October.
    12. Sulaimon T Adedokun & Victor T Adekanmbi & Olalekan A Uthman & Richard J Lilford, 2017. "Contextual factors associated with health care service utilization for children with acute childhood illnesses in Nigeria," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-14, March.
    13. Diaz, Rafael E., 2007. "Comparison of PQL and Laplace 6 estimates of hierarchical linear models when comparing groups of small incident rates in cluster randomised trials," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2871-2888, March.
    14. Laura Lindberg & Kathryn Kost & Isaac Maddow-Zimet & Sheila Desai & Mia Zolna, 2020. "Abortion Reporting in the United States: An Assessment of Three National Fertility Surveys," Demography, Springer;Population Association of America (PAA), vol. 57(3), pages 899-925, June.
    15. Tobias Keller & Martin Glaum & Andreas Bausch & Thorsten Bunz, 2023. "The “CEO in context” technique revisited: A replication and extension of Hambrick and Quigley (2014)," Strategic Management Journal, Wiley Blackwell, vol. 44(4), pages 1111-1138, April.
    16. Jae Hong Kim & Jongho Won, 2024. "Exploring variations in local land use regulations in the U.S.: What matters and at what level?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 73(3), pages 1071-1095, October.
    17. Yuqing Feng & Jing Wei & Maogui Hu & Chengdong Xu & Tao Li & Jinfeng Wang & Wei Chen, 2022. "Lagged Effects of Exposure to Air Pollutants on the Risk of Pulmonary Tuberculosis in a Highly Polluted Region," IJERPH, MDPI, vol. 19(9), pages 1-13, May.
    18. Bir, Courtney & Wolf, Christopher A. & Widmar, Nicole Olynk, 2020. "Dog and Cat Owner Demand for Veterinary Service Payment Plans," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 46(2), August.
    19. Sabine D Klein & Loredana Torchetti & Martin Frei-Erb & Ursula Wolf, 2015. "Usage of Complementary Medicine in Switzerland: Results of the Swiss Health Survey 2012 and Development Since 2007," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-10, October.
    20. Franceschini, Fiorenzo & Maisano, Domenico & Mastrogiacomo, Luca, 2014. "Scientific journal publishers and omitted citations in bibliometric databases: Any relationship?," Journal of Informetrics, Elsevier, vol. 8(3), pages 751-765.

    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:jedbes:v:39:y:2014:i:3:p:167-179. 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.