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Sequentially randomized designs, more recently known as sequential multiple assignment randomized trial (SMART) designs, are widely used in biomedical research, particularly in clinical trials, to assess and compare the effects of various treatment sequences. In such designs, patients are initially randomized to one of the rst-stage therapies. Then patients meeting some criteria (e.g., no relapse of disease) participate in the second-stage randomization to one of the second-stage therapies. The advantage of such a design is that it allows the investigator to study various treatment sequences where the patients' second-stage therapies can be adjusted based on their responses to the rst-stage therapies. In the past few years, substantial improvement has been made in the statistical methods for analyzing the data from SMARTs. Much of the proposed statistical approaches focus on estimating and comparing the survival outcomes of treatment sequences embedded in the SMART designs. In this article, we introduce the R package DTR, which provides a set of functions that can be used to estimate and compare the effects of different treatment sequences on survival outcomes using the newly proposed statistical approaches. The proposed package is also illustrated using simulated data from SMARTs.