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.
Lan
K K
KK
Biostatistics Research Branch, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20892.
Wittes
J
J
D001699:Biometry / Q000379:methods*; D002986:Clinical Trials as Topic / Q000379:methods*; D009203:Myocardial Infarction / Q000188:drug therapy / Q000401:mortality; D011336:Probability; D011433:Propranolol / Q000627:therapeutic use; D012107:Research Design
D011433:Propranolol