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The special case of binary treatment and continuous responses is studied in detail.
This article discusses and compares several methods for estimating the parameters of a latent regression model when one of the explanatory variables is an endogenous binary (treatment) variable.
We complement binary treatment analysis with continuous treatment analysis to understand not only the impact of being in the program but also the variability in impacts by the extent of treatment.
Binary grading systems are inherently superior to the more common three-grade systems because they are more reproducible and they correspond to the number of options in the binary treatment decision for which grade is considered important: the use of or withholding of chemotherapy.
Due to the complexity of a binary treatment like BNCT, the role of PET/CT is currently to design new criteria for patient enrolment in treatment protocols: the l-[18F]BPA/PET methodology could be considered as an important tool in newly designed clinical trials to better estimate the concentration ratio of BPA in the tumour as compared to neighbouring normal tissues.
where treatment group is either the binary treatment variable or the intensity treatment.
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In real life, individuals are often assigned to binary treatments according to existing treatment protocols.
We consider binary treatments by applying thresholds to the examined treatment variables.
However, we follow a suggestion by Imbens and Wooldridge (2009) in using two separate binary treatments, differing in their treatment intensity (more or less than 50% of the employees were affected by the minimum wage introduction).
However, in order to examine the impact of exercising and visiting socialization venues, the binary treatments are defined by considering only whether there was some exercising activity or a visit to a socialization place or not.
Most applications of propensity scores to date have involved simple cross-sectional studies with binary treatments.
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