The Ames Salmonella/Microsome Mutagenicity Assay: Issues of Inference and Validation

References

• Ames , B. N. 1979 . “Identifying Environmental Chemicals Causing Mutations and Cancer,” . Science , 204 : 587 – 593 .
   PubMed Web of Science ®Google Scholar
• Ames , B. N. , McCann , J. and Yamasaki , E. 1975 . “Methods for Detecting Carcinogens and Mutagens with the Salmonella/ Microsome Mutagenicity Test,” . Mutation Research , 31 : 347 – 364 .
   PubMed Web of Science ®Google Scholar
• Armitage , P. 1955 . “Tests for Linear Trends in Proportions and Frequencies,” . Biometrics , 11 : 374 – 386 .
   Web of Science ®Google Scholar
• Ashby , J. , De Serres , F. J. , Draper , M. , Ishidate , M. Jr. , Margolin , B. H. , Matter , B. and Shelby , M. D. 1985 . “Overview and Conclusions of the IPCS Collaborative Study on In Vitro Assay Systems,” . In Evaluation of Short-Term Tests for Carcinogens: Collaborative Study on In Vitro Assays , Edited by: Ashby , J. , de Serres , F. J. , Draper , M. , Ishidate , M. Jr. , Margolin , B. H. , Matter , B. and Shelby , M. D. 117 – 174 . Amsterdam : Elsevier/Science Publishers .
   Google Scholar
• Bernstein , L. , Kaldor , J. , McCann , J. and Pike , M. C. 1982 . “An Empirical Approach to the Statistical Analysis of Mutagenesis Data From the Salmonella Test,” . Mutation Research , 97 : 267 – 281 .
   PubMed Web of Science ®Google Scholar
• Boveri , T. 1914 . Zur Frage der Enstehung Maligner Tumoren , Jena , , East Germany : Gustov Fisher .
   Google Scholar
• Breslow , N. E. 1984 . “Extra-Poisson Variation in Log-Linear Models,” . Applied Statistics , 33 : 38 – 44 .
   Web of Science ®Google Scholar
• Breslow , N. E. and Kaldor , J. 1986 . “Statistical Analysis of Data From In-Vitro Assays of Mutagenesis,” . In Long-Term and Short-Term Assays for Carcinogens: A Critical Appraisal (Scientific Publication 83) , Edited by: Montesano , R. , Bartsch , H. , Vainio , H. , Wilbourn , J. and Yamasaki , H. 457 – 481 . Lyon , , France : International Agency for Research on Cancer .
   Google Scholar
• Carter , J. 1977 . “The President's Message on the Environment and Executive Orders,” . In Environmental Quality: Eighth Annual Report of the Council on Environmental Quality , 345 – 372 . Washington , DC : U.S. Government Printing Office .
   Google Scholar
• Chase , G. R. and Hoel , D. G. 1975 . “Serial Dilutions: Error Effects and Optimal Design,” . Biometrika , 62 : 329 – 334 .
   Web of Science ®Google Scholar
• Cochran , W. G. 1954 . “Some Methods for Strengthening the Common χ 2 Test,” . Biometrics , 10 : 417 – 451 .
   Web of Science ®Google Scholar
• Collings , B. J. 1981 . “The Negative Binomial Distribution: An Alternative to the Poisson,” , University of North Carolina at Chapel Hill, Dept. of Statistics . unpublished Ph.D. thesis
   Google Scholar
• Collings , B. J. , Margolin , B. H. and Oehlert , G. W. 1981 . “Analysis for Binomial Data, With Application to the Fluctuation Test for Mutagenicity,” . Biometrics , 37 : 775 – 794 .
   PubMed Web of Science ®Google Scholar
• Culliton , B. J. 1978 . “Toxic Substances Legislation: How Well Are Laws Being Implemented?” . Science , 201 : 1198 – 1199 .
   PubMed Web of Science ®Google Scholar
• Dempster , A. P. , Laird , N. M. and Rubin , D. B. 1977 . “Maximum Likelihood From Incomplete Data Via the EM Algorithm,” . Journal of the Royal Statistical Society , 39 : 1 – 38 . Ser. B
   Google Scholar
• Everitt , B. S. and Hand , D. J. 1981 . Finite Mixture Distributions , London : Chapman & Hall .
   Google Scholar
• Hasselblad , V. 1969 . “Estimation of Finite Mixtures of Distributions From the Exponential Family,” . Journal of the American Statistical Association , 64 : 1459 – 1471 .
   Web of Science ®Google Scholar
• Haynes , R. H. , Eckardt , F. and Kunz , B. A. 1984 . “The DNA Damage-Repair Hypothesis in Radiation Biology: Comparison With Classical Hit Theory,” . British Journal of Cancer , 49 : 81 – 90 . (Supp. 6)
   Web of Science ®Google Scholar
• Jonckheere , A. R. 1954 . “A Distribution Free k-Sample Test Against Ordered Alternatives,” . Biometrika , 41 : 133 – 145 .
   Web of Science ®Google Scholar
• Kim , B. S. 1984 . “Studies of Multinomial Mixture Models,” , University of North Carolina at Chapel Hill, Dept. of Statistics . unpublished Ph.D. thesis
   Google Scholar
• Louis , T. A. 1982 . “Finding the Observed Information Matrix When Using the EM Algorithm,” . Journal of the Royal Statistical Society , 44 : 226 – 233 . Ser. B
   Google Scholar
• Mantel , N. 1980 . “Assessing Laboratory Evidence for Neoplastic Activity,” . Biometrics , 36 : 381 – 399 .
   PubMed Web of Science ®Google Scholar
• Margolin , B. H. 1985 . “Statistical Studies in Genetic Toxicology: A Perspective From the National Toxicology Program (U.S.A.),” . Environmental Health Perspectives , 63 : 187 – 194 .
   PubMed Web of Science ®Google Scholar
• Margolin , B. H. , Kaplan , N. and Zeiger , E. 1981 . “Statistical Analysis of the Ames Salmonella/Microsome Test,” . Proceedings of the National Academy of Sciences , 78 : 3779 – 3783 .
   PubMed Web of Science ®Google Scholar
• Margolin , B. H. , Risko , K. J. , Shelby , M. D. and Zeiger , E. 1984 . “Sources of Variability in Ames Salmonella Typhimurium Tester Strains: Analysis of the International Collaborative Study on ‘Genetic Drift’,” . Mutation Research , 130 : 11 – 25 .
   PubMed Web of Science ®Google Scholar
• McCann , J. , Choi , E. , Yamasaki , E. and Ames , B. N. 1975 . “Detection of Carcinogens as Mutagens in the Salmonella/Microsome Test, Part I: Assay of 300 Chemicals,” . Proceedings of the National Academy of Sciences , 72 : 5135 – 5139 .
   PubMed Web of Science ®Google Scholar
• Pearson , K. 1915 . “On Certain Types of Compound Frequency Distributions in Which the Components Can Be Described by Binomial Series,” . Biometrika , 11 : 139 – 144 .
   Google Scholar
• Purchase , I. F. H. 1982 . “An Appraisal of Predictive Tests for Carcinogenicity,” . Mutation Research , 99 : 53 – 71 .
   PubMed Web of Science ®Google Scholar
• Simpson , D. G. and Margolin , B. H. 1986 . “Recursive Nonparametric Testing for Dose—Response Relationships Subject to Downturns at High Doses,” . Biometrika , 73 : 589 – 596 .
   Web of Science ®Google Scholar
• Snee , R. D. and Irr , J. D. 1984 . “A Procedure for the Statistical Evaluation of Ames Salmonella Assay Results: Comparison of Results Among Four Laboratories,” . Mutation Research , 128 : 115 – 125 .
   PubMed Web of Science ®Google Scholar
• Stead , A. G. , Hasselblad , V. , Creason , J. P. and Claxton , L. 1981 . “Modeling the Ames Test,” . Mutation Research , 85 : 13 – 27 .
   PubMed Web of Science ®Google Scholar
• Straus , D. S. 1981 . “Somatic Mutation, Cellular Differentiation, and Cancer Causation,” . Journal of the National Cancer Institute , 67 : 233 – 241 .
   PubMedGoogle Scholar
• Teicher , H. 1963 . “Identifiability of Finite Mixtures,” . The Annals of Mathematical Statistics , 34 : 1265 – 1269 .
   Google Scholar
• Tennant , R. W. , Margolin , B. H. , Shelby , M. D. , Zeiger , E. , Haseman , J. K. , Spalding , J. , Caspary , W. , Resnick , M. , Stasiewicz , S. , Anderson , B. and Minor , R. 1987 . “Prediction of Chemical Carcinogenicity in Rodents From In Vitro Genetic Toxicity Assays,” . Science , 236 : 933 – 941 .
   PubMed Web of Science ®Google Scholar
• Wu , C. F. J. 1983 . “On the Convergence Properties of the EM Algorithm,” . The Annals of Statistics , 11 : 95 – 103 .
   Web of Science ®Google Scholar