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### 7 Cards in this Set

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 data analysis approach fit the data by a proper equation for a 3 compartment model: c= a1*e^-b1*t + a2*e^-b2*t + a3... data analysis: fitting procedure pharmacokinetic models are nonlinear with respect to optimized parameters, ie: the dependent variable c cannot be described as the sum of functions of independent variables (time t) multiplied by the optimized parameters initial estimates can be obtained by the: methods of risiduals (peeling, feathering) the best model is selected using statistical criteria that include the quality of the fit: --x^2, sum of squares of deviations (the smaller the better, but cannot be smaller than the experimental error. does not consider the number of parameters) --the correlation coefficient r (percentage of explained variance = r^2. the closer to 1 the better) --the F-test criterion another criterion: the deviations between the model and the experimental points need to be distributed: homogeneously see slide page 1 if several models are of equal quality, the simplest model (containing the smallest number of optimized parameters) is selected. The rule is called: Occam's Razor data analysis: summary - method of residuals used to get initial estimates of the model parameters - the parameter values are refined using nonlinear regression analysis - for single dose, number of exponentials = number of compartments if the exponents are sufficiently different.