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National Research University Higher School of EconomicsStudent ThesesComparative Analysis of Treatment Selection Methods for Quantitative Outcome

Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Mariia Maslennikova
Comparative Analysis of Treatment Selection Methods for Quantitative Outcome
Applied Mathematics and Information Science
(Bachelor’s programme)
2017
In medical practice, where several alternative treatment approaches for one disease exist, the choice of treatment for each patient should be held with the hypothesis on which of the available treatment options will be most effective for a particular individual depending on individual characteristics. Each of the treatments can be more effective for one group of patients, but less effective for another. Currently, many different methods were developed for identifying and describing subgroups of patients in which one treatment will most likely result in a better outcome for the patient than an alternative. In this connection, there is a need to determine the most accurate method for determining such subgroups, depending on the initial data. This paper considers some of the described methods using a quantitative outcome variable with an application to randomized clinical trial (RCT) data set, and presents a comparison of these methods. Key words: Subgroup analysis; Trees of solutions; Interaction of the type of treatment and subgroups of patients; Randomized clinical trials; Quantitative outcome variable

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