Level: Beginner
【Presenter】
Masayuki Hirose, National University Corporation Kyushu University Kyushu University Hospital ARO Next Generation Medical Center
Hiroko Watanabe, ARO Next Generation Medical Center, Kyushu University Hospital
Takeshi Toyama, Kyushu University Hospital ARO Next Generation Medical Center
Koshiro Tagawa, ARO Next Generation Medical Center, Kyushu University Hospital
Kosuke Nakazono, ARO Next Generation Medical Center, Kyushu University Hospital
Takuya Nagata, Kyushu University Hospital ARO Next Generation Medical Center
Junji Kishimoto, ARO Next Generation Medical Center, Kyushu University Hospital
[Presentation overview]
JMP is widely used by medical researchers at our university because it is easy to operate and supports a wide variety of analysis methods. However, in recent years, there has been an increase in requests from reviewers of papers for relatively advanced analysis methods, as well as situations in which researchers themselves want to put them into practice. There is For example, advanced analysis is possible using software such as SAS, but the hurdles are high for busy medical researchers to perform programming such as SAS on their own.
In this presentation, we will report on some of the analysis methods that we believe will be beneficial if implemented in JMP in the future, based on consultation cases received during statistical consultations.
I completely agree with you about the 3 features you requested, as I use them frequently in my field as well.
In particular, the KM curve censoring mark and number at risk should be implemented in JMP Clinical, so why not just port them? I think.
