An Oral Contraceptive Drug Interaction Study

References

• Bradstreet, T. E. (1991), “Some Favorite Datasets from Early Phase of Drug Research,” in Proceedings of the Section on Statistical Education, American Statistical Association, pp. 190–195.
   Google Scholar
• Bradstreet, T. E. (1992), “Favorite Datasets from Early Phases of Drug Research – Part 2,” in Proceedings of the Section on Statistical Education, American Statistical Association, pp. 219–223.
   Google Scholar
• Bradstreet, T. E. (1993), “Statistical Applications in the Pharmaceutical Industry – Part III: Phase I and II Clinical Pharmacology Studies,” Stats, 10, pp. 20–23.
   Google Scholar
• Bradstreet, T. E. (1994), “Favorite Datasets from Early Phases of Drug Research – Part 3,” in Proceedings of the Section on Statistical Education, American Statistical Association, pp. 247–252.
   Google Scholar
• Bradstreet, T. E. (2000), “Food and Drug Interaction: What Role Does Statistics Play?” The College Mathematics Journal, 31, pp. 268–273.
   Google Scholar
• Bradstreet, T. E., and Dobbins, T. W. (1996), “When Are Two Drug Formulations Interchangeable?” Teaching Statistics, 18, pp. 45–48.
   Google Scholar
• Bradstreet, T. E., and Liss, C. L. (1995), “Favorite Datasets from Early (and Late) Phases of Drug Research – Part 4,” in Proceedings of the Section on Statistical Education, American Statistical Association, pp. 335–340.
   Google Scholar
• Bradstreet, T. E., and Short, T. H. (2001), “Favorite Datasets From Early Phases of Drug Research – Part 5,” in Proceedings of the Section on Statistical Education, American Statistical Association, CD-ROM.
   Google Scholar
• Chow, S.-C., and Liu, J. P. (2000), Design and Analysis of Bioavailability and Bioequivalence Studies (2nd ed., revised and expanded), New York: Marcel Dekker.
   Google Scholar
• Daniel, C., and Wood, F. S. (1980), Fitting Equations to Data (2nd ed.), New York: John Wiley and Sons.
   Google Scholar
• Drug Information Journal (1995), 29(3).
   Google Scholar
• Food and Drug Administration (1999), “Draft Guidance for Industry: Average, Population, and Individual Approaches to Establishing Bioequivalence” [Online]. (www.fda.gov/cder/guidance/guidance.htm)
   Google Scholar
• Food and Drug Administration (2000), “Guidance for Industry: Bioavailability and Bioequivalence Studies for Orally Administered Drug Products – General Considerations” [Online]. (www.fda.gov/cder/guidance/guidance.htm)
   Google Scholar
• Gibaldi, M., and Perrier, D. (1982), Pharmacokinetics (2nd ed.), New York: Marcel Dekker.
   Google Scholar
• Hollander, M. and Wolfe, D. A. (1973), Nonparametric Statistical Methods, New York: John Wiley and Sons.
   Google Scholar
• Jones, B., and Kenward, M. G. (1989), Design and Analysis of Cross-Over Trials, New York: Chapman and Hall.
   Google Scholar
• Journal of Biopharmaceutical Statistics (1997), 7(1).
   Google Scholar
• Koch, G. G. (1972), “The Use of Non-Parametric Methods in the Statistical Analysis of the Two-Period Change-Over Design,” Biometrics, 28, pp. 577–584.
   PubMed Web of Science ®Google Scholar
• Mood, A., Graybill, F. A., and Boes, D. C. (1974), Introduction to the Theory of Statistics (3rd ed.), New York: McGraw-Hill.
   Google Scholar
• Morris, A., and Bradstreet, T. E. (2000), “From Data to Study Report in One Step: A SAS™ Macro for the 2,2,2 Crossover Design,” in Proceedings of PharmaSUG 2000, pp. 317–321.
   Google Scholar
• Pikounis, B., Bradstreet, T. E., and Millard, S. P. (2001), “Graphical Insight and Data Analysis for the 2,2,2 Crossover Study,” in Applied Statistics in the Pharmaceutical Industry With Case Studies Using S-PLUS, eds. S.P Millard and A. Krause, New York: Springer-Verlag, pp. 153–179.
   Google Scholar
• Senn, S. (1993), Cross-over Trials in Clinical Research, New York: John Wiley and Sons.
   Google Scholar
• Senn, S. (1997), Statistical Issues in Drug Development, New York: John Wiley and Sons.
   Google Scholar
• Statistics in Medicine (2000), 19(20).
   Google Scholar