The B-value: a tool for monitoring data.

This paper considers the problem of monitoring slowly accruing data from a nonsequentially designed experiment. We describe the use of the B-value, which is a transformed Z-value, for the calculation of conditional power. In data monitoring, interim Z-values do not allow simple projections to the end of the study. Moreover, because of their popular association with P-values, Z-values are often misinterpreted. If observed trends are viewed as the realization of a Brownian motion process, the B-value and its decomposition allow simple extrapolations to the end of the study under a variety of hypotheses. Applications are presented to one- and two-sample Z-tests, the two-sample Wilcoxon rank sum test, and the log-rank test.