Statistical Analysis of Drug Disposition Data

References

• Aris R. Mathematical Modeling Techniques. Pitman Publishing Limited, London 1979
   Google Scholar
• Berman M, Weiss M F. SAAM-27: User's Manual. National Institutes of Health, Bethesda, MD 1978, NIH Publication No. 78–180
   Google Scholar
• Knott G D. MLAB-A mathematical modeling tool. Comp Programs Biomed 1979; 10: 271
   PubMedGoogle Scholar
• Jacquez J A. Compartmental Analysis in Biology and Medicine. Elsevier, Amsterdam 1972
   Google Scholar
• Yamaoka Y, Nakagawa T, Uno T. Statistical moments in Pharmacokinetics. J Pharmacokin Biopharm 1978; 6: 546–558
   Google Scholar
• Covell D G, Berman M, Delisi C. Mean residence time Theoretical development, experimental determination and practical usage in tracer analysis. Math Biosci 1984; 72: 213–244
   Web of Science ®Google Scholar
• Lawson C L, Hanson R J. Solving Least Squares Problems. Prentice Hall, Englewood Cliffs, NJ 1974
   Google Scholar
• Berman M. The formulation and testing of models. Ann NY Acad Sci 1963; 108: 182–194
   PubMed Web of Science ®Google Scholar
• Doob J L. Stochasic Process. John Wiley & Sons, Inc., New York 1953
   Google Scholar
• Lambrecht R M, Resigno A. Tracer Kinetics and Physiologic Modeling. Springerverlag, Berlin 1983
   Google Scholar
• Boston R C, Grief P C, Berman M. Conversational SAAM-An interactive program for kinetic analysis of biological systems. Computer Programs Biomed 1981; 13: 111–119
   PubMedGoogle Scholar
• Bard Y. Nonlinear Parameter Estimation. Academic Press, Inc., New York 1974
   Google Scholar
• Daniel C, Wood F S. Fitting Equations to Data. Wiley-Interscience, New York 1971
   Google Scholar
• Wilde D J, Beightler C S. Foundations of Optimization. Prentice-Hall, Englewood Cliffs, NJ 1967
   Google Scholar
• Marquardt D W. An algorithm for lease-squares estimation of nonlinear parameters. Society of Industrial and Applied Mathematics Journal 1963; 11: 431
   Web of Science ®Google Scholar
• Scheffe H. The Analysis of Variance. John Wiley & Sons, Inc, New York 1959
   Google Scholar
• Rodbard D, Lenox R H, Wray H L, Ramseth D. Statissical characterization of the random errors in the radioimmunoassay dose-response variable. Clin Chem 1976; 22(3)350–358
   PubMed Web of Science ®Google Scholar
• Finney D J, Phillips P. The form and estimation of a variance function with particular reference to radioimmunoassay. Appl Statist 1977; 26(3)312–320
   Google Scholar
• Jacquez J A, Norusis M. Sampling experiments on the estimation of parameters in heteroscedastic linear regression
   Google Scholar
• Nichols A I, Peck C C. ELSNLR-Users Manual. Division of Clinical Pharmacology. USUHS, Bethesda, MD 1981, Technical Report No 5
   Google Scholar
• Draper N R, Smith H. Applied Regression Analysis. John Wiley & Sons, Inc., New York 1963
   Google Scholar
• Netter J, Wasserman W. Applied Linear Statistical Models. RD Irwin, Homewood, IL 1974
   Google Scholar
• Berman M. Information Content of data with respect to models. Am J physical 1983; 245: 620–623
   Google Scholar
• Kramer W G, Lewis R P, Cobb T C, et al. Pharmacokinetics of digoxin: Comparison of a two and a three compartment model in man. J pharmacokin Biopharm 1974; 2: 123
   PubMedGoogle Scholar
• Rao C R. Estimation of heteroscedastic variances in linear models. J Am Stat Assoc 1970; 65: 161–172
   Web of Science ®Google Scholar
• Anscombe F J, Tukey J W. The examination and analysis of residuals. Technometrics 1963; 5: 141
   Web of Science ®Google Scholar
• Mosteller F, Tukey J W. Data Analysis and Regression. Addison-Wesley, Reading, MA 1977
   Google Scholar
• Siegel S. Noparametric Statistics for the Behavioral Sciences. McGraw-Hill, New York 1956
   Google Scholar
• Weber J E, Monarchi D E. Performance of the Durbin-Watson test and WLS estimation when the disturbance term includes serial dependence in addition to first order autocorrelation. J AM Stat Assoc 1982; 17: 117
   Google Scholar
• Wagner J G. Do you need a pharmacokinetic model, and if so, which one?. J Pharmacok Biopharm 1975; 3: 457–478
   PubMedGoogle Scholar
• Benet L Z. General treatment of linear mammillary models with elimination from any compartmental as used in pharmacokinetics. J Pharm Sci 1972; 61: 536–541
   PubMed Web of Science ®Google Scholar
• Mandel J. The statistical analysis of experimental data. Interscience, New York 1964
   Google Scholar
• Cobelli C, Di Stefano J J. Parameter and structural identifiability concepts and ambiguities: A critical review. Am J Physiol 1980; 239: R7–R24
   PubMed Web of Science ®Google Scholar
• Bharucha-Reid A T. Elements of the Theory of Markov Processes and Their Applications. McGraw Hill, New York 1960
   Google Scholar
• Feller W. An Introduction to Probability Theory and Its Applications. John Wiley & Sons, Inc., New York 1968; vol I
   Google Scholar
• Bailey N TJ. The Elements of Stochastic Processes with Applications to the Natural Sciences. John Wiley & Sons, Inc., New York 1964
   Google Scholar
• Matis J H. On the stochastic theory of compartments: Solution for n-compartment systems with irreversible time-dependent transition probabilities. Bull Math Biol 1974; 36(5/6)489–504
   Web of Science ®Google Scholar
• Purdue P. Variability in a single compartmental system: a note on SR Bernard's model. Bull Math Biol 1981; 43: 111–114
   Web of Science ®Google Scholar
• Rescigno A, Mathis J H. On the relevance of stochastic compartmental models to pharmacokinetic systems. Bull Math Biol 1981; 43: 245–255
   Web of Science ®Google Scholar
• Matis J H, Wehrly T E. Stochastic models of compartmental systems. Biometrics 1979; 35: 199–207
   Web of Science ®Google Scholar
• Robertson J S. Compartmental Distribution of Radiotracers. CRC Pres Inc, Boca Raton, FL 1983
   Google Scholar
• Sheiner L B, Rosenberg B, Marthae W. Estimation of population characteristics of pharmacokinetic parameters from routine clinical data. J Pharm Biopharm 1977; 5(5)445–479
   PubMedGoogle Scholar
• Stratonovich R L. A new representation for stochastic integrals and equations. Society of Industrial and Applied Mathematics Journal Control 1966; 4: 362–371
   Google Scholar
• Mortensen R E. Mathematical problems of modeling stochastic nonlinear dynamic systems. J Stat Physics 1969; 1(2)271–296
   Google Scholar
• Kalman R E. A new approach to linear filtering and prediction problems. Trans ASME (J Basic Eng) 1960; 82D: 35–45
   Google Scholar
• Gelb A. Applied Optimal Estimation. MIT Press, Cambridge, MA 1974
   Google Scholar
• Maybeck P S. Stochastic Models, Estimation and Control. Academic Press, Inc, New York 1979; vol 1
   Google Scholar
• McIntosh J A, McIntosh R P. Monographs on Endocrinology, vol 16: Mathematical Modeling and Computers in Endocrinology. Springer-Verlag, Heidelberg 1980; 95
   Google Scholar