When performing a dose-response curve, most investigators measure response at zero dose. Handling this data point is not straightforward because we recommend entering data with X equal to the logarithm of concentration, but the logarithm of zero is undefined. We suggest entering a low concentration (perhaps one or two log units lower than your lowest concentration) instead of zero. If you enter a concentration so low that is has essentially no effect on the response, this method works fine and gives the correct results. But some people are wary about analyzing data this way, feeling that it is 'cheating'.

I've come up with a user-defined equation that takes into account the zero value without 'cheating'.

Typically, confidence intervals are expressed as a two-sided range. You might state, for example, with 95% confidence, that the true value of a parameter such as mean, EC50, relative risk, difference, etc., lies in a range between two values. We call this range “two sided” because it is bounded by both lower and upper confidence limits. In some circumstances, it can make more sense to express the confidence interval in only one direction – to either the lower or upper confidence limit. In this short article, I explain the principles of one-sided confidence intervals and how to create them with Prism.