Mathematics Human health sciences: Multidisciplinary, general & others
Author, co-author :
Desmet, L.; ISBA, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
Venet, D.; IRIDIA, Université Libre de Bruxelles, Brussels, Belgium and Breast Cancer Translational Research Lab, Institut Bordet, Université Libre de Bruxelles, Belgium
Bloomfield, P., (2000), Fourier Analysis of Time Series (2nd ed.), New York:Wiley.
Chuang-Stein, C., (1993), “An Application of the Beta-Binomial Model to Combine and Monitor Medical Event Rates in Clinical Trials,” Drug Information Journal, 27, 515.
Desmet, L., Venet, D., Doffagne, E., Timmermans, C., Burzykowski, T., Legrand, C., and Buyse, M., (2014), “Linear Mixed-Effects Models for Central Statistical Monitoring of Multicenter Trials,” Statistics in Medicine, 33, 5265–5279.
Griffiths, D. A., (1973), “Maximum Likelihood Estimation for the Beta-Binomial Distribution and an Application to the Household Distribution of the Total Number of Cases of a Disease,” Biometrics, 29, 637–648.
Kirkwood, A. A., Cox, T., and Hackshaw, A., (2013), “Application of Methods for Central Statistical Monitoring in Clinical Trials,” Clinical Trials, 10, 783–806.
Kleinman, J. C., (1973), “Proportions With Extraneous Variance:Single and Independent Samples,” Journal of the American Statistical Association, 68, 46–54.
Kulinskaya, E., (2008), “On Two-Sided p-Values for Non-Symmetric Distributions,” arXiv:0810.2124v1.
Lindblad, A. S., Manukyan, Z., Purohit-Sheth, T., Gensler, G., Okwesili, P., Meeker-O’Connell, A., Ball, L., and Marler, J. R., (2014), “Central Site Monitoring:Results From a Test of Accuracy in Identifying Trials and Sites Failing Food and Drug Administration Inspection,” Clinical Trials, 11, 205–17.
Pogue, J. M., Devereaux, P. J., Thorlund, K., and Yusuf, S., (2013), “Central Statistical Monitoring:Detecting Fraud in Clinical Trials,” Clinical Trials, 10, 225–35.
R Development Core Team (2011), R:A Language and Environment for Statistical Computing, Vienna, Austria:R Foundation for Statistical Computing, ISBN 3-900051-07-0, available at http://www.R-project.org/.
Tarone, R. E., (1979), “Testing the Goodness of Fit of the Binomial Distributions,” Biometrika, 66, 585–590.
Timmermans, C., Doffagne, E., Desmet, L., Venet, D., Legrand, C., Burzykowski, T., and Buyse, M., (2015), “Using Central Statistical Monitoring to Assess Data Quality and Consistency in the Stomach Cancer Adjuvant Multi-Institutional Group Trial (SAMIT),” Gastric Cancer, DOI:10.1007/s10120-015-0533-9.
Timmermans, C., Venet, D., and Burzykowski, T., (2015), “Data-Driven Risk Identification in Phase III Clinical Trials Using Central Statistical Monitoring,” International Journal of Clinical Oncology, DOI:10.1007/s10147-015-0877-5.
Tripathi, R. C., Gupta, R. C., and Gurland, J., (1994), “Estimation of Parameters in the Beta Binomial Model,” Annals of the Institute of Statistical Mathematics, 46, 317–331.
Venet, D., Doffagne, E., Burzykowski, T., Beckers, F., Tellier, Y., Genevois-Marlin, E., Becker, U., Bee, V., Wilson, V., Legrand, C., and Buyse, M., (2012), “A Statistical Approach to Central Monitoring of Data Quality in Clinical Trials,” Clinical Trials, 9, 705–713.
Williams, D. A., (1975), “The Analysis of Binary Responses From Toxicological Experiments Involving Reproduction and Teratogenecity,” Biometrics, 31, 949–952.
Yee, T. M., (2004), “VGAM Family Functions for Univariate Distributions,” available at https://www.stat.auckland.ac.nz/yee/VGAM/doc/univar.pdf.
——— (2012), “VGAM:Vector Generalized Linear and Additive Models,” R package version 0.8-7. Available at http://CRAN.R-project.org/package=VGAM.
Young-Chu, Y., and Chan, K., (2008), “Pooling Overdispersed Binomial Data to Estimate Event Rate,” BMC Medical Research Methodology, 8, 58.