While the control data are used for normalization, statistical analyses recommended by the AGM do not explicitly include control data in curve fitting. The AGM goes into considerable detail about fitting the classical Hill equation to CRC data. Fitting to competitive binding and functional assay data is discussed in the chapter on "Assay Operations for SAR Support". Fitting to in vivo assay data is described in section 3.5 of the chapter on "In Vivo Assay Guidelines". In both chapters, the AGM suggests fitting the four-parameter logistic (4PL) model, in which all of θ is allowed to vary, to most CRC data. The control data are not included in the fit and therefore have no effect on estimated x 50 or H. For some data, the AGM recommends the three-parameter logistic fixed bottom (3PLFB) model, where R b is fixed at zero, or the three-parameter logistic fixed top (3PLFT) model, where R t is fixed at 100. Conceptually, three-parameter models make the most sense when control data can be reasonably construed as measurements of the minimal response R b or maximal response R t . For example, in an enzymatic inhibition assay, if the response is proportional to the concentration of a product, then the negative control without inhibitor is a measurement of R t .