IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v56y2012i12p3865-3875.html

The use of historical controls in estimating simultaneous confidence intervals for comparisons against a concurrent control

Author

Listed:
  • Kitsche, A.
  • Hothorn, L.A.
  • Schaarschmidt, F.

Abstract

In a typical toxicity bioassay, an untreated control group and several groups of increasing dosage are studied. The use of historical control data from previous trials provides additional information for statistical analysis. It is assumed that dichotomous response variables (e.g., dead/alive) can be suitably analyzed through the comparison of binomial proportions, where any confounding effects on the observed rates are presumed to be absent. Binomial proportions from historical control groups are used to estimate the parameters of a beta prior distribution. Using this beta prior allows knowledge from the historical control data to be applied to a current bioassay. Although trend tests for this situation have been proposed, our main focus is directed towards the construction of simultaneous confidence intervals allowing for an interpretation both in terms of statistical significance and biological relevance. The performance of the proposed approach was investigated in simulation studies for a wide range of potential scenarios. In many cases, the new approach is more powerful and less conservative than a common approach. The method is illustrated by evaluating a long-term carcinogenicity example from the literature.

Suggested Citation

  • Kitsche, A. & Hothorn, L.A. & Schaarschmidt, F., 2012. "The use of historical controls in estimating simultaneous confidence intervals for comparisons against a concurrent control," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3865-3875.
    • Handle: RePEc:eee:csdana:v:56:y:2012:i:12:p:3865-3875
    DOI: 10.1016/j.csda.2012.05.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947312002095
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2012.05.010?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Smythe, Robert T. & Krewski, Daniel & Murdoch, Duncan, 1986. "The use of historical control information in modelling dose response relationships in carcinogenesis," Statistics & Probability Letters, Elsevier, vol. 4(2), pages 87-93, March.
    2. Klingenberg, Bernhard, 2012. "Simultaneous score confidence bounds for risk differences in multiple comparisons to a control," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1079-1089.
    3. Bretz, Frank, 2006. "An extension of the Williams trend test to general unbalanced linear models," Computational Statistics & Data Analysis, Elsevier, vol. 50(7), pages 1735-1748, April.
    4. Chen, D.G., 2010. "Incorporating historical control information into quantal bioassay with Bayesian approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1646-1656, June.
    5. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    Full references (including those not matched with items on IDEAS)

    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. Yixuan Wang & Jianzhu Li & Ping Feng & Rong Hu, 2015. "A Time-Dependent Drought Index for Non-Stationary Precipitation Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5631-5647, December.
    2. Auteri, Monica & Cremaschini, Alessandro, 2024. "Ownership or procurement, which matters? exploring asymmetries in local public transportation in Italy through a semi-parametric approach," The Journal of Economic Asymmetries, Elsevier, vol. 30(C).
    3. Nathaniel Geiger & Bryan McLaughlin & John Velez, 2021. "Not all boomers: temporal orientation explains inter- and intra-cultural variability in the link between age and climate engagement," Climatic Change, Springer, vol. 166(1), pages 1-20, May.
    4. Gauss Cordeiro & Josemar Rodrigues & Mário Castro, 2012. "The exponential COM-Poisson distribution," Statistical Papers, Springer, vol. 53(3), pages 653-664, August.
    5. Wanting He & Wenyuan Li & Yunran Wei, 2025. "Periodic evaluation of defined-contribution pension fund: A dynamic risk measure approach," Papers 2508.05241, arXiv.org.
    6. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    7. Chen, Shu & Shao, Dongguo & Tan, Xuezhi & Gu, Wenquan & Lei, Caixiu, 2017. "An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition," Agricultural Water Management, Elsevier, vol. 191(C), pages 98-112.
    8. Riccardo De Bin & Vegard Grødem Stikbakke, 2023. "A boosting first-hitting-time model for survival analysis in high-dimensional settings," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 420-440, April.
    9. Matteo Malavasi & Gareth W. Peters & Pavel V. Shevchenko & Stefan Truck & Jiwook Jang & Georgy Sofronov, 2021. "Cyber Risk Frequency, Severity and Insurance Viability," Papers 2111.03366, arXiv.org, revised Mar 2022.
    10. Joanna Baj-Korpak & Marian Jan Stelmach & Kamil Zaworski & Piotr Lichograj & Marek Wochna, 2022. "Assessment of Motor Abilities and Physical Fitness in Youth in the Context of Talent Identification—OSF Test," IJERPH, MDPI, vol. 19(21), pages 1-19, November.
    11. Simon Hirsch, 2025. "Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting," Papers 2504.02518, arXiv.org, revised Oct 2025.
    12. Youxin Wang & Tao Peng & Qingxia Lin & Vijay P. Singh & Xiaohua Dong & Chen Chen & Ji Liu & Wenjuan Chang & Gaoxu Wang, 2022. "A New Non-stationary Hydrological Drought Index Encompassing Climate Indices and Modified Reservoir Index as Covariates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2433-2454, May.
    13. Lucio Masserini & Matilde Bini & Monica Pratesi, 2017. "Effectiveness of non-selective evaluation test scores for predicting first-year performance in university career: a zero-inflated beta regression approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 693-708, March.
    14. Hötte, Kerstin, 2023. "Demand-pull, technology-push, and the direction of technological change," Research Policy, Elsevier, vol. 52(5).
    15. Simon N. Wood & Natalya Pya & Benjamin Säfken, 2016. "Smoothing Parameter and Model Selection for General Smooth Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1548-1563, October.
    16. Wu, Guojun & Song, Ge & Lv, Xiaoxiang & Luo, Shikai & Shi, Chengchun & Zhu, Hongtu, 2023. "DNet: distributional network for distributional individualized treatment effects," LSE Research Online Documents on Economics 122895, London School of Economics and Political Science, LSE Library.
    17. Dominique Guegan & Bertrand K. Hassani, 2011. "Operational risk: a Basel II++ step before Basel III," Documents de travail du Centre d'Economie de la Sorbonne 11053, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    18. Tong, Edward N.C. & Mues, Christophe & Thomas, Lyn, 2013. "A zero-adjusted gamma model for mortgage loan loss given default," International Journal of Forecasting, Elsevier, vol. 29(4), pages 548-562.
    19. Alexander Silbersdorff & Kai Sebastian Schneider, 2019. "Distributional Regression Techniques in Socioeconomic Research on the Inequality of Health with an Application on the Relationship between Mental Health and Income," IJERPH, MDPI, vol. 16(20), pages 1-28, October.
    20. Menghao Wang & Shanhu Jiang & Liliang Ren & Chong-Yu Xu & Linyong Wei & Hao Cui & Fei Yuan & Yi Liu & Xiaoli Yang, 2022. "The Development of a Nonstationary Standardised Streamflow Index Using Climate and Reservoir Indices as Covariates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1377-1392, March.

    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:56:y:2012:i:12:p:3865-3875. 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.