Simultaneous score confidence bounds for risk differences in multiple comparisons to a control
AbstractAsymptotic simultaneous lower (upper) confidence bounds for risk differences arising from comparing several treatments to a common control are constructed by inverting the maximum (minimum) of score statistics. With a few exceptions, these bounds perform better in terms of simultaneous coverage probability than procedures based on adjusted Wald methods (e.g., adding pseudo-observations), especially over relevant parts of the parameter space in superiority or inferiority studies. A further improvement is realized by using an appropriate multiplicity adjusted critical value that takes advantage of the correlation information in the score statistics estimated under the null instead of a regular plug-in estimate. Simulation results and a worked example show a gain in terms of the precision of the lower bounds and their power; however, not too much is lost when using the straightforward Sidak multiplicity adjustment when the number of comparisons is small. All methods discussed are implemented and reproducible with general and publicly available R code.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 56 (2012)
Issue (Month): 5 ()
Contact details of provider:
Web page: http://www.elsevier.com/locate/csda
Multiple comparisons; Difference of proportion; Dunnett test; Maximum test; Simultaneous inference; Non-inferiority; Superiority;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Andersson, Per GÃ¶sta, 2009. "A Simple Correlation Adjustment Procedure Applied to Confidence Interval Construction," The American Statistician, American Statistical Association, vol. 63(3), pages 258-262.
- Santner, Thomas J. & Pradhan, Vivek & Senchaudhuri, Pralay & Mehta, Cyrus R. & Tamhane, Ajit, 2007. "Small-sample comparisons of confidence intervals for the difference of two independent binomial proportions," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5791-5799, August.
- Zou, Guang Yong & Huang, Wenyi & Zhang, Xiaohe, 2009. "A note on confidence interval estimation for a linear function of binomial proportions," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1080-1085, February.
- Pan, Wei, 2002. "Approximate confidence intervals for one proportion and difference of two proportions," Computational Statistics & Data Analysis, Elsevier, vol. 40(1), pages 143-157, July.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wendy Shamier).
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.