This book provides a systematic and organized approach to analyzing data for a RCT with noncompliance under the most frequently-encountered situations, including parallel sampling, stratified sampling, cluster sampling, parallel sampling with subsequent missing outcomes, and a series of dependent binomial sampling for repeated measurements. Consort-flow diagrams and numerical examples are used to illustrate the bias of commonly-used approaches such as AT analysis, AP analysis and ITT analysis for a RCT with noncompliance. The book also looks at testing the equality, non-inferiority, and equivalence between two treatments based on the different important indices, such as the proportion difference (PD), proportion ratio (PR) and odds ratio (OR).  Sample size calculation formulae for testing equality, non-inferiority and equivalence based on different indices under various sampling designs are also featured. The Author presents an instructive and easily-understood approach by using contingency tables to lay down the latent probability structure of observed data so that readers can easily appreciate the logics and the ideas behind the development of test procedures and estimators.