Level: Beginner
【Presenter】
Masayuki Hirose, National University Corporation Kyushu University Kyushu University Hospital ARO Next Generation Medical Center
Hiroko Watanabe, Kyushu University Hospital ARO Next Generation Medical Center
Takeshi Toyama, Kyushu University Hospital ARO Next Generation Medical Center
Koshiro Tagawa, Kyushu University Hospital ARO Next Generation Medical Center
Kosuke Nakazono, Kyushu University Hospital ARO Next Generation Medical Center
Takuya Nagata, Kyushu University Hospital ARO Next Generation Medical Center
Junji Kishimoto, Kyushu University Hospital ARO Next Generation Medical Center
[Announcement summary]
JMP is widely used by medical researchers at our university because it is easy to operate and supports various analysis methods. However, in recent years, there have been an increasing number of situations in which reviewers of papers are requesting relatively advanced analysis methods, or researchers themselves want to put them into practice, and JMP's existing functions alone cannot fully meet the demands. There is. For example, advanced analysis is possible using software such as SAS, but it is a high hurdle for busy medical researchers to program SAS etc. on their own.
In this presentation, we will report some analysis methods that we think will be useful to be implemented in JMP in the future, based on the consultation cases received in the statistical consulting.
I completely agree with the addition of the three requested features, as they will be used frequently in my field.
In particular, the KM curve censoring mark, number at risk, should be implemented in JMP Clinical, so why not just port it? I think.
