IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v39y2012i8p1781-1795.html
   My bibliography  Save this article

Many-to-one comparison of nonlinear growth curves for Washington's Red Delicious apple

Author

Listed:
  • Nairanjana Dasgupta
  • Monte J. Shaffer

Abstract

In this article, we are interested in comparing growth curves for the Red Delicious apple in several locations to that of a reference site. Although such multiple comparisons are common for linear models, statistical techniques for nonlinear models are not prolific. We theoretically derive a test statistic, considering the issues of sample size and design points. Under equal sample sizes and same design points, our test statistic is based on the maximum of an equi-correlated multivariate chi-square distribution. Under unequal sample sizes and design points, we derive a general correlation structure, and then utilize the multivariate normal distribution to numerically compute critical points for the maximum of the multivariate chi-square. We apply this statistical technique to compare the growth of Red Delicious apples at six locations to a reference site in the state of Washington in 2009. Finally, we perform simulations to verify the performance of our proposed procedure for Type I error and marginal power. Our proposed method performs well in regard to both.

Suggested Citation

  • Nairanjana Dasgupta & Monte J. Shaffer, 2012. "Many-to-one comparison of nonlinear growth curves for Washington's Red Delicious apple," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(8), pages 1781-1795, April.
  • Handle: RePEc:taf:japsta:v:39:y:2012:i:8:p:1781-1795
    DOI: 10.1080/02664763.2012.683168
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2012.683168
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02664763.2012.683168?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. F. Bretz & J. C. Pinheiro & M. Branson, 2005. "Combining Multiple Comparisons and Modeling Techniques in Dose-Response Studies," Biometrics, The International Biometric Society, vol. 61(3), pages 738-748, September.
    2. Hester, Susan M. & Cacho, Oscar, 2003. "Modelling apple orchard systems," Agricultural Systems, Elsevier, vol. 77(2), pages 137-154, August.
    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. Herberich Esther & Hassler Christine & Hothorn Torsten, 2014. "Multiple Curve Comparisons with an Application to the Formation of the Dorsal Funiculus of Mutant Mice," The International Journal of Biostatistics, De Gruyter, vol. 10(2), pages 289-302, November.

    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. Kathrin Möllenhoff & Frank Bretz & Holger Dette, 2020. "Equivalence of regression curves sharing common parameters," Biometrics, The International Biometric Society, vol. 76(2), pages 518-529, June.
    2. Beibei Guo & Ying Yuan, 2023. "DROID: dose‐ranging approach to optimizing dose in oncology drug development," Biometrics, The International Biometric Society, vol. 79(4), pages 2907-2919, December.
    3. Cittadini, E.D. & Lubbers, M.T.M.H. & de Ridder, N. & van Keulen, H. & Claassen, G.D.H., 2008. "Exploring options for farm-level strategic and tactical decision-making in fruit production systems of South Patagonia, Argentina," Agricultural Systems, Elsevier, vol. 98(3), pages 189-198, October.
    4. Cook, David & Carrasco, Luis Roman & Paini, Dean & Fraser, Rob, 2011. "Estimating the social welfare effects of New Zealand apple imports," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(4), pages 1-22.
    5. Soto-Silva, Wladimir E. & Nadal-Roig, Esteve & González-Araya, Marcela C. & Pla-Aragones, Lluis M., 2016. "Operational research models applied to the fresh fruit supply chain," European Journal of Operational Research, Elsevier, vol. 251(2), pages 345-355.
    6. Dette, Holger & Scheder, Regine, 2008. "A finite sample comparison of nonparametric estimates of the effective dose in quantal bioassay," Technical Reports 2008,05, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    7. Yu, Jun & Kong, Xiangshun & Ai, Mingyao & Tsui, Kwok Leung, 2018. "Optimal designs for dose–response models with linear effects of covariates," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 217-228.
    8. Dette, Holger & Bretz, Frank, 2007. "Optimal designs for dose finding studies," Technical Reports 2007,01, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    9. Frank Schaarschmidt & Christian Ritz & Ludwig A. Hothorn, 2022. "The Tukey trend test: Multiplicity adjustment using multiple marginal models," Biometrics, The International Biometric Society, vol. 78(2), pages 789-797, June.
    10. Björn Bornkamp & Katja Ickstadt, 2009. "Bayesian Nonparametric Estimation of Continuous Monotone Functions with Applications to Dose–Response Analysis," Biometrics, The International Biometric Society, vol. 65(1), pages 198-205, March.
    11. Bornkamp, Björn & Pinheiro, José & Bretz, Frank, 2009. "MCPMod: An R Package for the Design and Analysis of Dose-Finding Studies," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i07).
    12. Georg Gutjahr & Björn Bornkamp, 2017. "Likelihood ratio tests for a dose-response effect using multiple nonlinear regression models," Biometrics, The International Biometric Society, vol. 73(1), pages 197-205, March.
    13. Bregaglio, Simone & Orlando, Francesca & Forni, Emanuela & De Gregorio, Tommaso & Falzoi, Simone & Boni, Chiara & Pisetta, Michele & Confalonieri, Roberto, 2016. "Development and evaluation of new modelling solutions to simulate hazelnut (Corylus avellana L.) growth and development," Ecological Modelling, Elsevier, vol. 329(C), pages 86-99.
    14. Wenqing Jiang & Jiangjie Zhou & Baosheng Liang, 2023. "An Improved Dunnett’s Procedure for Comparing Multiple Treatments with a Control in the Presence of Missing Observations," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
    15. Jiajing Xu & Guosheng Yin & David Ohlssen & Frank Bretz, 2016. "Bayesian two-stage dose finding for cytostatic agents via model adaptation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(3), pages 465-482, April.
    16. Stephen Senn & Dipti Amin & Rosemary A. Bailey & Sheila M. Bird & Barbara Bogacka & Peter Colman & Andrew Garrett & Andrew Grieve & Peter Lachmann, 2007. "Statistical issues in first‐in‐man studies," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(3), pages 517-579, July.
    17. Ying Yuan & Guosheng Yin, 2011. "Dose–Response Curve Estimation: A Semiparametric Mixture Approach," Biometrics, The International Biometric Society, vol. 67(4), pages 1543-1554, December.
    18. Eric Gibson & Frank Bretz & Michael Looby & Bjoern Bornkamp, 2018. "Key Aspects of Modern, Quantitative Drug Development," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(2), pages 283-296, August.
    19. John T. Chen, 2008. "A Two-Stage Stepwise Estimation Procedure," Biometrics, The International Biometric Society, vol. 64(2), pages 406-412, June.
    20. Bretz, Frank & Dette, Holger & Pinheiro, José, 2008. "Practical considerations for optimal designs in clinical dose finding studies," Technical Reports 2008,22, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    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:taf:japsta:v:39:y:2012:i:8:p:1781-1795. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.