IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v55y2011i4p1815-1827.html

Laplace random effects models for interlaboratory studies

Author

Listed:
  • Rukhin, Andrew L.
  • Possolo, Antonio

Abstract

A model is introduced for measurements obtained in collaborative interlaboratory studies, comprising measurement errors and random laboratory effects that have Laplace distributions, possibly with heterogeneous, laboratory-specific variances. Estimators are suggested for the common median and for its standard deviation. We provide predictors of the laboratory effects, and of their pairwise differences, along with the standard errors of these predictors. Explicit formulas are given for all estimators, whose sampling performance is assessed in a Monte Carlo simulation study.

Suggested Citation

  • Rukhin, Andrew L. & Possolo, Antonio, 2011. "Laplace random effects models for interlaboratory studies," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1815-1827, April.
    • Handle: RePEc:eee:csdana:v:55:y:2011:i:4:p:1815-1827
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(10)00444-5
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, Enero-Abr.
    2. Davies, Laurie, 1991. "A stochastic model for interlaboratory tests," Computational Statistics & Data Analysis, Elsevier, vol. 12(2), pages 201-209, September.
    3. Wilcox, Rand R., 2006. "Comparing medians," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1934-1943, December.
    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. Andrew L. Rukhin, 2013. "Estimating heterogeneity variance in meta-analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(3), pages 451-469, June.

    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. Benjamin Hofner & Andreas Mayr & Nikolay Robinzonov & Matthias Schmid, 2014. "Model-based boosting in R: a hands-on tutorial using the R package mboost," Computational Statistics, Springer, vol. 29(1), pages 3-35, February.
    2. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    3. Otto-Sobotka, Fabian & Salvati, Nicola & Ranalli, Maria Giovanna & Kneib, Thomas, 2019. "Adaptive semiparametric M-quantile regression," Econometrics and Statistics, Elsevier, vol. 11(C), pages 116-129.
    4. Narisetty, Naveen & Koenker, Roger, 2022. "Censored quantile regression survival models with a cure proportion," Journal of Econometrics, Elsevier, vol. 226(1), pages 192-203.
    5. Fan, Yanqin & Liu, Ruixuan, 2016. "A direct approach to inference in nonparametric and semiparametric quantile models," Journal of Econometrics, Elsevier, vol. 191(1), pages 196-216.
    6. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    7. Klaus Friesenbichler, 2013. "Firm Growth in Conflict Countries: Some Evidence from South Asia," Review of Economics & Finance, Better Advances Press, Canada, vol. 3, pages 33-44, May.
    8. Park, Beum-Jo & Kim, Myung-Joong, 2017. "A Dynamic Measure of Intentional Herd Behavior in Financial Markets," MPRA Paper 82025, University Library of Munich, Germany.
    9. Andrés Barge-Gil & Alberto López, 2015. "R versus D: estimating the differentiated effect of research and development on innovation results," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 24(1), pages 93-129.
    10. Kleopatra Nikolaou, 2007. "The behaviour of the real exchange rate: Evidence from regression quantiles," Money Macro and Finance (MMF) Research Group Conference 2006 46, Money Macro and Finance Research Group.
    11. Chen, Xiaohong & Pouzo, Demian, 2009. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," Journal of Econometrics, Elsevier, vol. 152(1), pages 46-60, September.
    12. Jean-Marc Fournier & Isabell Koske, 2012. "The determinants of earnings inequality: evidence from quantile regressions," OECD Journal: Economic Studies, OECD Publishing, vol. 2012(1), pages 7-36.
    13. Michael D. Bordo & Pierre L. Siklos, 2017. "Central Bank Credibility before and after the Crisis," Open Economies Review, Springer, vol. 28(1), pages 19-45, February.
    14. Feng, Zhenghui & Wang, Tao & Zhu, Lixing, 2014. "Transformation-based estimation," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 186-205.
    15. Kangning Wang & Lu Lin, 2017. "Robust and efficient direction identification for groupwise additive multiple-index models and its applications," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 22-45, March.
    16. Zhao, Lili & Lin, Yutong & Liu, Zhenhao & Yang, Guozheng, 2026. "Examining climate risk attention in stock markets: insights from quantile-on-quantile regression," The North American Journal of Economics and Finance, Elsevier, vol. 81(C).
    17. Zhang, Yaowu & Zhou, Yeqing & Zhu, Liping, 2025. "Interval quantile correlations with applications to testing high-dimensional quantile effects," Journal of Econometrics, Elsevier, vol. 249(PA).
    18. Ossi Korkeamäki & Jukka Appelqvist & Tomi Kyyrä, 2007. "Quantile Regression Estimates of the Earnings Losses of Displaced Workers," EcoMod2007 23900045, EcoMod.
    19. Miroslava Federicova, 2014. "The Impact of High-Stakes School-Admission Exams on Study Effort and Achievements: Quasi-experimental Evidence from Slovakia," Investigaciones de Economía de la Educación volume 9, in: Adela García Aracil & Isabel Neira Gómez (ed.), Investigaciones de Economía de la Educación 9, edition 1, volume 9, chapter 27, pages 515-532, Asociación de Economía de la Educación.

    More about this item

    Keywords

    ;

    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:eee:csdana:v:55:y:2011:i:4:p:1815-1827. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.