Chiu, S. T., Tsai, P. Y. & Liu, J. P. (2010). Statistical evaluation of non-profile analyses for the in vitro bioequivalence. Journal of Chemometrics
Codex Alimentarius Commission (2009). Foods Derived from Modern Biotechnology, 2nd edn, Rome: Joint FAO/WHO Food Standards Programme.
Davit, B. M., Chen, M. L., Conner, D. P., Haidar, S. H., Kim, S., Lee, C. H., Lionberger, R. A., Maklouf, F. T., Nwakama, P. E., Patel, D. T., Schuirmann, D. J. & Yu, L. X. (2012). Implementation of a reference-scaled average bioequivalence approach for highly variable generic drug products by the US Food and Drug Administration. The AAPS Journal
Dragalin, V., Fedorov, V., Patterson, S. & Jones, B. (2003). Kullback-Leibler divergence for evaluating bioequivalence. Statistics in Medicine
EFSA (2010). Scientific opinion on statistical considerations for the safety evaluation of GMOs. EFSA panel on GMOs. EFSA Journal
8(1), 1250. doi: 10.2903/j.efsa.2010.1250.
EFSA (2014). Explanatory statement for the applicability of the Guidance of the EFSA Scientific Committee on conducting repeated-dose 90-day oral toxicity study in rodents on whole food/feed for GMO risk assessment. EFSA Journal
12(10), 3871. doi: 10.2903/j.efsa.2014.3871.
a). Outcome of the Public Consultation on the Draft Guidance on the Agronomic and Phenotypic Characterization of Genetically Modified Plants. EFSA supporting publication 2015: EN-829. Parma, Italy: EFSA.
b). Guidance on the agronomic and phenotypic characterization of genetically modified plants. EFSA Journal
13(6), 4128. doi: 10.2903/j.efsa.2015.4128.
Endrenyi, L., Taback, N. & Tothfalusi, L. (2000). Properties of the estimated variance component for subject-by-formulation interaction in studies of individual bioequivalence. Statistics in Medicine
Graybill, F. A. & Wang, C. M. (1980). Confidence intervals on nonnegative linear combinations of variances. Journal of the American Statistical Association
Hannig, J., Iyer, H. & Patterson, P. (2006). Fiducial generalized confidence intervals. Journal of the American Statistical Association
Harrigan, G. G., Culler, A. H., Culler, M., Breeze, M. L., Berman, K. H., Halls, S. C. & Harrison, J. M. (2013). Investigation of biochemical diversity in a soybean lineage representing 35 years of breeding. Journal of Agricultural and Food Chemistry
Harrison, J. M., Howard, D., Malven, M., Halls, S. C., Culler, A. H., Harrigan, G. G. & Wolfinger, R. D. (2013). Principle variance component analysis of crop composition data: a case study on herbicide-tolerant cotton. Journal of Agricultural and Food Chemistry
Herman, R. A., Scherer, P. N., Phillips, A. M., Storer, N. P. & Krieger, M. (2010). Safe composition levels of transgenic crops assessed via a clinical medicine model. Biotechnology Journal
Hothorn, L. A. & Oberdoerfer, R. (2006). Statistical analysis used in the nutritional assessment of novel food using the proof of safety. Regulatory Toxicology and Pharmacology
Howe, W. G. (1974). Approximate confidence limits on the mean of X + Y where X and Y are two tabled independent random variables. Journal of the American Statistical Association
Hyslop, T., Hsuan, F. & Holder, D. J. (2000). A small sample confidence interval approach to assess individual bioequivalence. Statistics in Medicine
John, J. A. & Mitchell, T. J. (1977). Optimal incomplete block designs. Journal of the Royal Statistical Society, Series B (Methodological)
Kang, Q. & Vahl, C. I. (2014). Statistical analysis in the safety evaluation of genetically modified crops: equivalence tests. Crop Science
Khuri, A. I., Mathew, T. & Sinha, B. K. (1998). Statistical Tests for Mixed Linear Models. New York: Wiley-Interscience.
König, A., Cockburn, A., Crevel, R. W. R., Debruyne, E., Grafstroem, R., Hammerling, U., Kimber, I., Knudsen, I., Kuiper, H. A., Peijnenburg, A. A. C. M., Penninks, A. H., Poulsen, M., Schauzu, M. & Wal, J. M. (2004). Assessment of the safety of foods derived from genetically modified (GM) crops. Food and Chemical Toxicology
Krishnamoorthy, K. & Lian, X. D. (2012). Closed-form approximate tolerance intervals for some general linear models and comparison studies. Journal of Statistical Computation and Simulation
Krishnamoorthy, K. & Mathew, T. (2004). One-sided tolerance limits in balanced and unbalanced one-way random models based on generalized confidence intervals. Technometrics
Krishnamoorthy, K. & Mathew, T. (2009). Statistical Tolerance Regions: Theory, Applications, and Computation. Hoboken, NJ: Wiley.
Lee, Y. H., Shao, J. & Chow, S. C. (2004). Modified large-sample confidence intervals for linear combinations of variance components: extension, theory, and application. Journal of the American Statistical Association
Liao, C. T., Lin, T. Y. & Iyer, H. K. (2005). One- and two-sided tolerance intervals for general balanced mixed models and unbalanced one-way random models. Technometrics
McNally, R. J., Iyer, H. & Mathew, T. (2003). Tests for individual and population bioequivalence based on generalized P values. Statistics in Medicine
OECD (1993). Safety Evaluation of Foods Derived by Modern Biotechnology: Concepts and Principles. Paris, France: Organization for Economic Cooperation and Development.
Park, D. J. & Burdick, R. K. (2003). Performance of confidence intervals in regression models with unbalanced one-fold nested error structures. Communication in Statistics – Simulation and Computation
Quiroz, J., Ting, N., Wei, G. C. G. & Burdick, R. K. (2002). Alternative confidence intervals for the assessment of bioequivalence in four-period cross-over designs. Statistics in Medicine
SAS Institute Inc. (2011). SAS/STAT® 9·3 User's Guide. Cary, NC: SAS Inst. Inc.
Schuirmann, D. J. (1987). A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. Journal of Pharmacokinetics and Biopharmaceutics
Searle, S. R. (1987). Linear Models for Unbalanced Data. New York: John Wiley and Sons.
Ting, N., Burdick, R. K., Graybill, F. A., Jeyaratnam, S. & Lu, T. F. C. (1990). Confidence interval on linear combinations of variance components that are unrestricted in sign. Journal of Statistical Computation and Simulation
Tsui, K. W. & Weerahandi, S. (1989). Generalized P values in significance testing of hypotheses in the presence of nuisance parameters. Journal of the American Statistical Association
Vahl, C. I. & Kang, Q. (2015). Equivalence criteria for the safety evaluation of a genetically modified crop – a statistical perspective. The Journal of Agricultural Science, Cambridge. doi: S0021859615000271.
Van der Voet, H., Perry, J. N., Amzal, B. & Paoletti, C. (2011). A statistical assessment of differences and equivalences between genetically modified and reference plant varieties. BMC Biotechnology
11, 15. doi: 10.1186/1472–6750-11-15.
Venkatesh, T. V., Breeze, M. L., Liu, K., Harrigan, G. G. & Culler, A. H. (2014). Compositional analysis of grain and forage from MON 87427, an inducible male sterile and tissue selective glyphosate-tolerant maize product for hybrid seed production. Journal of Agricultural and Food Chemistry
Ward, K. J., Nemeth, M. A., Brownie, C., Hong, B., Herman, R. A. & Oberdoerfer, R. (2012). Comments on the paper “A statistical assessment of differences and equivalences between genetically modified and reference plant varieties” by van der Voet et al. 2011. BMC Biotechnology
12, 13. doi: 10.1186/1472–6750-12-13.
Weerahandi, S. (1993). Generalized confidence intervals. Journal of the American Statistical Association
Whent, M., Hao, J. J., Slavin, M., Zhou, M., Song, J. Z., Kenworthy, W. & Yu, L. L. (2009). Effect of genotype, environment, and their interaction on chemical composition and antioxidant properties of low-linolenic soybeans grown in Maryland. Journal of Agricultural and Food Chemistry