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Current IssueEditorial BoardOnline First ArticlesArchive

Research Article

volume 35 issue 1-2 (march-june 2020) : 91-93,   Doi: 10.18805/BKAP202

Detection of Outlying Subjects in Bioequivalence Trials

S
Sumeet Saurav
C
Cini Varghese
S
Seema Jaggi
M
Mohd Harun
D
Devendra Kumar
1<div style="text-align: justify;">ICAR-Indian Agricultural Statistics Research Institute, PUSA, New Delhi &ndash; 110 012, India</div>

  • Submitted22-05-2020|

  • Accepted13-07-2020|

  • First Online 10-09-2020|

  • doi 10.18805/BKAP202

Cite article:- Saurav Sumeet, Varghese Cini, Jaggi Seema, Harun Mohd, Kumar Devendra (2020). Detection of Outlying Subjects in Bioequivalence Trials. Bhartiya Krishi Anusandhan Patrika. 35(1): 91-93. doi: 10.18805/BKAP202.

ABSTRACT

Evaluation of veterinary medicinal products is one of the important areas where bioequivalence trials are conducted. One of the problems commonly encountered in bioequivalence trials is outlying subjects. These outlying data may occur either as unexpected observations or as the unusual subject who has extremely high or low bioavailability with respect to the reference formulation and may have dramatic effects on the bioequivalence test. Therefore, it is important to examine the data carefully for identification of outlying observations in bioequivalence studies. In this study we have developed another general approach, termed the Estimated Distance (ED), to the outliers’ detection problem.

REFERENCES

  1. Bhar, L.M. and Gupta, V.K. (2001). A useful statistic for studying outliers in experimental designs. Sankhya. 63(3): 338-350.
  2. Box, G.E.P. and Draper, N.R.(1975). Robust Designs. Biometrika. 62: 347-352.
  3. Chow, S.C. and Liu, J.P. (1994). Design and Analysis of Bioavailability and Bioequivalence Studies. Marcel Decker Inc., New York.
  4. Gopalan, R. and Dey, A. (1976). On Robust Experi- -mental Designs. Sankhya B. 38: 297-299.
  5. Liu, J.P. and Chow, S.C. (2000). Design and Analysis of Bioavailability and Bioequivalence Studies. 2nd Edition, Marcel Dekker, New York.
  6. Mandallaz, D. and Mau, J. (1981). Comparison of different methods for decision making in bioequivalence assessment. Biometrics. 37 (2): 213-222.
  7. Oh, H.S., Ko, S.G and Oh, M.S. (2003). A Bayesian    approach to assessing population bioequiva-    -lence in a 2×2 crossover design. Journal of Applied Statistics. 30(8): 881-891.
  8. Rodda, B.E. (1986). ‘Bioequivalence of solid oral dosage forms’, presentation to the U.S. Food and Drug Administration hearing on bioequiva- -lence of solid oral dosage forms, Pharmaceu- -tical Manufacturers Association, 29 September to 1 October 1986.
  9. Sarker, S., Gupta, V.K. and Parsad, R. (2003). Robust block designs for making test treatments- control treatment comparisons against the presence of an outlier. Journal of the Indian Society of Agricultural Statistics. 56(1): 7-18.
  10. Singh, M., Gupta, S. and Singh, M. (1987). Robustness of row-column designs. Statistics & Probability Letters. 5: 421-424. 
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    Research Article

    volume 35 issue 1-2 (march-june 2020) : 91-93,   Doi: 10.18805/BKAP202

    Detection of Outlying Subjects in Bioequivalence Trials

    S
    Sumeet Saurav
    C
    Cini Varghese
    S
    Seema Jaggi
    M
    Mohd Harun
    D
    Devendra Kumar
    1<div style="text-align: justify;">ICAR-Indian Agricultural Statistics Research Institute, PUSA, New Delhi &ndash; 110 012, India</div>

    • Submitted22-05-2020|

    • Accepted13-07-2020|

    • First Online 10-09-2020|

    • doi 10.18805/BKAP202

    Cite article:- Saurav Sumeet, Varghese Cini, Jaggi Seema, Harun Mohd, Kumar Devendra (2020). Detection of Outlying Subjects in Bioequivalence Trials. Bhartiya Krishi Anusandhan Patrika. 35(1): 91-93. doi: 10.18805/BKAP202.

    ABSTRACT

    Evaluation of veterinary medicinal products is one of the important areas where bioequivalence trials are conducted. One of the problems commonly encountered in bioequivalence trials is outlying subjects. These outlying data may occur either as unexpected observations or as the unusual subject who has extremely high or low bioavailability with respect to the reference formulation and may have dramatic effects on the bioequivalence test. Therefore, it is important to examine the data carefully for identification of outlying observations in bioequivalence studies. In this study we have developed another general approach, termed the Estimated Distance (ED), to the outliers’ detection problem.

    REFERENCES

    1. Bhar, L.M. and Gupta, V.K. (2001). A useful statistic for studying outliers in experimental designs. Sankhya. 63(3): 338-350.
    2. Box, G.E.P. and Draper, N.R.(1975). Robust Designs. Biometrika. 62: 347-352.
    3. Chow, S.C. and Liu, J.P. (1994). Design and Analysis of Bioavailability and Bioequivalence Studies. Marcel Decker Inc., New York.
    4. Gopalan, R. and Dey, A. (1976). On Robust Experi- -mental Designs. Sankhya B. 38: 297-299.
    5. Liu, J.P. and Chow, S.C. (2000). Design and Analysis of Bioavailability and Bioequivalence Studies. 2nd Edition, Marcel Dekker, New York.
    6. Mandallaz, D. and Mau, J. (1981). Comparison of different methods for decision making in bioequivalence assessment. Biometrics. 37 (2): 213-222.
    7. Oh, H.S., Ko, S.G and Oh, M.S. (2003). A Bayesian    approach to assessing population bioequiva-    -lence in a 2×2 crossover design. Journal of Applied Statistics. 30(8): 881-891.
    8. Rodda, B.E. (1986). ‘Bioequivalence of solid oral dosage forms’, presentation to the U.S. Food and Drug Administration hearing on bioequiva- -lence of solid oral dosage forms, Pharmaceu- -tical Manufacturers Association, 29 September to 1 October 1986.
    9. Sarker, S., Gupta, V.K. and Parsad, R. (2003). Robust block designs for making test treatments- control treatment comparisons against the presence of an outlier. Journal of the Indian Society of Agricultural Statistics. 56(1): 7-18.
    10. Singh, M., Gupta, S. and Singh, M. (1987). Robustness of row-column designs. Statistics & Probability Letters. 5: 421-424. 
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