An extensive survey of radioimmunoassay calibration data for prednisolone, prednisone and digoxin indicated that the common practice of preparing calibration curves with individual subject's pre-dose plasma or serum, and using this to estimate unknown concentrations for the same subject, is not supported by statistical considerations. Preparation of calibration plots from pooled data is better because this introduces less bias in estimated concentrations. Such a method also saves a great deal of time, since it is not necessary to repeat the calibration procedure each time, "unknowns" are being assayed. The data suggest that there is no optimum calibration plot for all radioimmunoassays. Rather, each antibody-drug combination should be investigated thoroughly to determine the best calibration plot for the particular combination. We found that the best calibration plots are: the logistic-logarithmic plot for prednisolone; nonlinear least squares fit to a polyexponential equation for nisolone; nonlinear least squares fit to a polyexponential equation for prednisone; and a weighted least squares regression of normalized % bound versus concentration for figoxin. The error in the radioimmunoassay is usually concentration-dependent, and, in certain regions of the standard curve, is larger than the literature indicates, since, frequently, the error has been gauged from % bound values, but should be guaged from inversely-estimated concentrations.