This paper explains how to handle three issues that policy evaluators may face in using RCT (randomized controlled trials). The first issue concerns the sampling design that increases precision in the estimate of the average treatment effect under a given budget constraint. The second issue is the problem of noncompliance. This problem arises when the assignments of study subjects to treatment groups and control groups does not completely match the presence/absence of actual treatments, and initial randomness in selection of treatment and control groups is compromised. While there is a standard solution to this problem based on the instrumental variable method, the precision of this estimator is usually not high. This paper introduces a recent study by Black et al. (2015) regarding a test on the presence/absence of endogeneity in the treatment variable under the presence of noncompliance, and the use of a more precise estimator when the test result indicates the absence of endogeneity. The third issue concerns the estimation of the average treatment effect under RCT when a mediator variable that indicates the truncation of observation, and thereby the truncation-by-death problem exists. Discovering better solutions to this problem is one of the recent topics in statistical causal inference. This paper explains why certain methods, such as difference-in-differences (DID) estimator, cannot be applied to this situation even when the outcome before the treatment assignment is measurable, and why an estimate for the average treatment effect for the untreated (ATU) is desirable. The paper also introduces an estimator of the ATU for the truncation-by-death problem, based on an ignorability assumption. This paper also demonstrates that the idea of "principal stratification" based on certain assumptions of latent classes in behavioral patterns has been usefully employed in obtaining a causal understanding of both the noncompliance issue and the truncation-by-death issue. An illustrative application of empirical data for handing noncompliance with the Black et al.'s endogeneity test is also presented.