Alpha Spending Function:

In the interim monitoring of clinical trials, multiple looks are taken at the accruing results. In such circumstances, akin to multiple testing, the alpha-value at each look must be adjusted in order to preserve the overall Type-1 Error. Alpha spending functions, (the Pocock family is one such set; the Lan-Demets spending function a more specific case) establish these adjusted alpha-values for each interim monitoring point, given the overall alpha. Typically, they establish relatively high alpha-values for early looks, and lower alpha-values for later looks. Thus, they constitute "stopping boundaries," which, when crossed, indicate that statistical significance has been established. When graphed, a typical set of stopping boundaries looks like an inverted V pointing to the right. (horizontal axis represents number of events recorded, vertical axis the standardized value of the test statistic.)