Skip to main content
Log in

Comparison of statistical methods for the analysis of limiting dilution assays

  • Regular Papers
  • Published:
In Vitro Cellular & Developmental Biology Aims and scope Submit manuscript

Summary

This study reports the results of a critical comparison of five statistical methods for estimating the density of viable cells in a limiting dilution assay (LDA). Artificial data were generated using Monte Carlo simulation. The performance of each statistical method was examined with respect to the accuracy of its estimator and, most importantly, the accuracy of its associated estimated standard error (SE). The regression method was found to perform at a level that is unacceptable for scientific research, due primarily to gross underestimation of the SE. The maximum likelihood method exhibited the best overall performance. A corrected version of Taswell's weighted-mean method, which provides the best performance among all noniterative methods examined, is also presented.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Berkson, J. Maximum likelihood and minimum chi-square estimates of the logistic function. J. Am. Stat. Assoc. 50:130–162; 1955.

    Article  Google Scholar 

  2. Berkson, J. Minimum chi-square, not maximum likelihood! Ann. Stat. 8:457–487; 1980.

    Google Scholar 

  3. Fazekas de St. Groth, S. The evaluation of limiting dilution assays. J. Immunol. Methods 49:R11-R23; 1982.

    Article  PubMed  CAS  Google Scholar 

  4. Goldstein, A. Biostatistics, an introductory text. New York: The Macmillan Company; 1964.

    Google Scholar 

  5. Hoel, P. G. Introduction to mathematical statistics, 3rd ed. New York: John Wiley & Sons; 1962:224.

    Google Scholar 

  6. Kynast, G.; Weber, E. Analysis of a limiting dilution assay by using the single-hit Poisson model—an APL computer program. EDV Med. Biol. 14:53–57; 1983.

    Google Scholar 

  7. Lefkovits, I.; Waldman, H. Statistical tests, limitations and reproducibility. In: Limiting dilution analysis of cells in the immune system. England: Cambridge University Press; 1979:93–113.

    Google Scholar 

  8. Schmehl, M. S.; Cobb, L.; Bank, H. L. Power analysis of statistical methods for comparing treatment differences from limiting dilution assays. In Vitro 25:69–75; 1989.

    CAS  Google Scholar 

  9. Smith, V. K. Monte Carlo methods: their role for economics. Lexington, MA: Lexington Books; 1972.

    Google Scholar 

  10. Taswell, C. Limiting dilution assays for the determination of immunocompetent cell frequencies. I: Data analysis. J. Immunol. 126:1614–1619; 1981.

    PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cobb, L., Cyr, L., Schmehl, M.K. et al. Comparison of statistical methods for the analysis of limiting dilution assays. In Vitro Cell Dev Biol 25, 76–81 (1989). https://doi.org/10.1007/BF02624414

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02624414

Key words

Navigation