4 parameter logistic curve graphpad prism

What you want is a curve that follows the data, and in some cases an asymmetrical five parameter model does so better than a four parameter model. It is very hard to fit both slope and asymmetry with tight confidence intervals. If your goal is just to interpolate unknowns from a standard curve, the width of the confidence intervals of the parameters doesn't really matter. If your goal is to obtain meaningful best-fit parameters, then you'll need lots of high quality data. Note that the logEC50 is not the same as the inflection point (which can be higher or lower than the logEC50 depending on the value of S). It is in the same units as the X values - the logarithm of concentration. The equation above fits the logEC50, which is the X value when Y is half-way between the Top and Bottom plateaus. If you have normalized the data, you may want to constrain these values to 100 and 0. Top and Bottom are the Y values at the top and bottom plateaus of the curve. S must be greater than zero, but can be less than, or greater than, 1.0. When s is not 1.0, the curve will be asymmetrical. If s=1.0, then this is the same as the four parameter equation. This equation assumes that X has been entered as (or transformed to) the logarithm of concentration, and that Y is the response in any convenient units. This is also called the generalized Hill equation. al.), which is built-in to the 'Dose-response - Special' group of equations in Prism 5 and later. Prism uses the RIchards version (from Giraldo et. Then the symmetrical variable slope equation has three (not four) parameters, and the asymmetrical form has four (not five) parameters.Īsymmetrical dose-response curves can be described by several equations. Some authors assume that any nonspecific signal is already subtracted off, so present the equations in a form where Bottom is defined to be zero and doesn't appear in the equation. Of course, an equation should not be referred to by its number of parameters. The standard curve is sometimes called a four-parameter logistic model, so the asymmetrical curve is called a five parameter logistical model. This can be modeled by including a fifth parameter that describes the asymmetry of the curve. In this curve, the top and bottom parts are mirror images of each other - the curve is symmetrical. response curve is defined by the bottom, top, EC50, and slope.

4 parameter logistic curve graphpad prism