Time-to-Optimal Control of Hypertension
Using Cox-proportional Hazard and Weibull Model
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Most statistical analysis methods do not include the length of time as a variable, and analysis is made only on the trial outcomes upon completion of the study period, as specified in the study protocol (In and Lee, 2018). However, in cases where the outcome yields different interpretations at different points in time, even over a range of only several hours or minutes, it is advantageous to use a statistical analysis method incorporating time as a variable (Kleinbaum and Klein, 2005). Survival methods apply when the focus is the time until an event, such as death or disease onset (Sowmya and ...
Most statistical analysis methods do not include the length of time as a variable, and analysis is made only on the trial outcomes upon completion of the study period, as specified in the study protocol (In and Lee, 2018). However, in cases where the outcome yields different interpretations at different points in time, even over a range of only several hours or minutes, it is advantageous to use a statistical analysis method incorporating time as a variable (Kleinbaum and Klein, 2005). Survival methods apply when the focus is the time until an event, such as death or disease onset (Sowmya and David, 2007). Survival analysis is a type of statistical analysis that looks at how predictors affect the time until an event happens, rather than the probability of the event itself. It is used to analyze data in which the time until the event is of interest. As the name indicates, this method has origins in the field of medical research for evaluating the impact of medicines or medical treatment on time until death (Sheik, Selvakumar, Parkavi, Suganya and Venkatesh, 2019).
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