In this entry, through the analysis of a data set, we examine how to make histograms, tables, transitive graphs, and scatter plots and the way to calculate medians and interquartile ranges (IQR).
In health preference research (HPR), it is naturally difficult to determine patients’ real necessities. This is because it is often the case that even patients themselves are not necessarily able to tell specifically what medical procedure they hope to receive, facing complex choices and variable expected consequences. A discrete choice experiment (DCE), which presents multiple health descriptions and infers the patients’ weighting factors from the responses, is one of the effective ways to address this problem.
In this entry, before entering the details of DCEs, we are going to
analyze the data set accessorily generated in the process of DCE; our
focus here is the time spent on choosing a choice for each question,
which is called the first response time. Respondents may change their
answer to the other before proceeding to the next question, but the
first response time only measures the time from starting the question to
selecting the first choice. In the DCE held in 2016, 4088 US
participants responded to 20 questions regarding hypothetical health
conditions. The data set that we are going to analyze contains each
individual’s first response time for 20 questions.