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A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest

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  • Halekoh, Ulrich
  • Højsgaard, Søren

Abstract

When testing for reduction of the mean value structure in linear mixed models, it is common to use an asymptotic χ2 test. Such tests can, however, be very poor for small and moderate sample sizes. The pbkrtest package implements two alternatives to such approximate χ2 tests: The package implements (1) a Kenward-Roger approximation for performing F tests for reduction of the mean structure and (2) parametric bootstrap methods for achieving the same goal. The implementation is focused on linear mixed models with independent residual errors. In addition to describing the methods and aspects of their implementation, the paper also contains several examples and a comparison of the various methods.

Suggested Citation

  • Halekoh, Ulrich & Højsgaard, Søren, 2014. "A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i09).
    • Handle: RePEc:jss:jstsof:v:059:i09
    DOI: http://hdl.handle.net/10.18637/jss.v059.i09
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    Cited by:

    1. Martin, Manon & Govaerts, Bernadette, 2019. "LiMM-PCA : combining ASCA+ and linear mixed models to analyse high dimensional designed data," LIDAM Discussion Papers ISBA 2019021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. James Simpson & Megan Freeth & Kimberley Jayne Simpson & Kevin Thwaites, 2022. "Street edge subdivision: Structuring ground floor interfaces to stimulate pedestrian visual engagement," Environment and Planning B, , vol. 49(6), pages 1775-1791, July.
    3. Waseem Alnosaier & David Birkes, 2019. "Inner workings of the Kenward–Roger test," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(2), pages 195-223, March.
    4. Rúna Í. Magnússon & Alexandra Hamm & Sergey V. Karsanaev & Juul Limpens & David Kleijn & Andrew Frampton & Trofim C. Maximov & Monique M. P. D. Heijmans, 2022. "Extremely wet summer events enhance permafrost thaw for multiple years in Siberian tundra," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    5. Paul E. Rose & James E. Brereton & Lewis J. Rowden & Ricardo Lemos Figueiredo & Lisa M. Riley, 2019. "What’s new from the zoo? An analysis of ten years of zoo-themed research output," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-10, December.
    6. Lenth, Russell V., 2016. "Least-Squares Means: The R Package lsmeans," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i01).
    7. García-Callejas, David & Araújo, Miguel B., 2016. "The effects of model and data complexity on predictions from species distributions models," Ecological Modelling, Elsevier, vol. 326(C), pages 4-12.
    8. Gesche Janzarik & Daniel Wollschläger & Michèle Wessa & Klaus Lieb, 2022. "A Group Intervention to Promote Resilience in Nursing Professionals: A Randomised Controlled Trial," IJERPH, MDPI, vol. 19(2), pages 1-18, January.
    9. Sebastian Loth & Katharina Jettka & Manuel Giuliani & Stefan Kopp & Jan P de Ruiter, 2018. "Confidence in uncertainty: Error cost and commitment in early speech hypotheses," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-30, August.
    10. King, K.W. & Hanrahan, B.R. & Stinner, J. & Shedekar, V.S., 2022. "Field scale discharge and water quality response, to drainage water management," Agricultural Water Management, Elsevier, vol. 264(C).
    11. Haoyang Lu & Li Yi & Hang Zhang, 2019. "Autistic traits influence the strategic diversity of information sampling: Insights from two-stage decision models," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-29, December.
    12. Blake B. Anderson & Andrew Scott & Reuven Dukas, 2016. "Social behavior and activity are decoupled in larval and adult fruit flies," Behavioral Ecology, International Society for Behavioral Ecology, vol. 27(3), pages 820-828.
    13. Joren Raymenants & Caspar Geenen & Lore Budts & Jonathan Thibaut & Marijn Thijssen & Hannelore Mulder & Sarah Gorissen & Bastiaan Craessaerts & Lies Laenen & Kurt Beuselinck & Sien Ombelet & Els Keyae, 2023. "Indoor air surveillance and factors associated with respiratory pathogen detection in community settings in Belgium," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    14. Byron C. Jaeger & Lloyd J. Edwards & Kalyan Das & Pranab K. Sen, 2017. "An statistic for fixed effects in the generalized linear mixed model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(6), pages 1086-1105, April.
    15. László Zsolt Garamszegi & Magdalena Zagalska-Neubauer & David Canal & Gábor Markó & Eszter Szász & Sándor Zsebők & Eszter Szöllősi & Gábor Herczeg & János Török, 2015. "Malaria parasites, immune challenge, MHC variability, and predator avoidance in a passerine bird," Behavioral Ecology, International Society for Behavioral Ecology, vol. 26(5), pages 1292-1302.
    16. Govaerts, B. & Francq, B. & Marion, R. & Martin, M. & Thiel, M., 2020. "The essentials on linear regression, ANOVA, general linear and linear mixed models for the chemist," LIDAM Discussion Papers ISBA 2020012, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

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