Ranked set sampling (RSS) is known to be superior to the tradi tional simple random sampling (SRS) in the sense that it often leads to more efficient infere nce procedures. Basic version of RSS has been extensively modified to come up with schemes resulti ng in more accurate estimators of the population attributes. Multistage ranked set sampling (MSRSS) is such a variation surpassing RSS. Entropy has been instrumental in constructing criteri a for fitting of parametric models to the data. The goal of this article is to develop tests of uniformi ty based on sample entropy under RSS and MSRSS designs. A Monte Carlo simulation study is carried out to compare the power of the proposed tests under several alternative distributions wi th the ordinary test based on SRS. The results report that the new entropy tests have higher power t han the original one for nearly all sample sizes and under alternatives considered.

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