The area under the receiver operating characteristic curve (AUC) is commonly used to quantify the discriminative ability of tests with ordinal or continuous test data. When planning a study to evaluate a new test, it is important to determine a minimum sample size required to achieve a prespecified precision of estimating AUC. However, conventional sample size formulas do not consider the probability of achieving a prespecified precision, resulting in underestimation of sample sizes. To incorporate the assurance probability, asymptotic sample size formulas were derived using different variance estimators for AUC in this thesis. The precision of AUC estimations was quantified by either lower confidence limits or interval width. The performance of proposed sample size formulas was evaluated through simulation studies. Simulation results show that the formula based on lower limits with the nonparametric method performs best and can be used with both ordinal and continuous data. The methods are illustrated with examples from previously published data
