In Sweden I seem to be the only person who uses the excellent statistical software JMP. I have used it for several years and now have version 14.2.0. The majority of the research colleagues that I work with use SPSS but I think JMP is much better. However, since I am a surgeon my statistical knowledge is somewhat limited. I know JMP fairly well but I mostly do univariate and multivariate analyses of nominal data. However, now I got a question from a journal regarding the Cox proportional hazard analysis of the data. Since I do not know how to do that in JMP I would appreciate if the community could help me. The dependent (y) variabel is continuous and is time to event (in bold, see a small sample below). To the left (in italic and book antiqua) are the x variables as nominal values and to the right of the y variabel are the x variables converted to numerical (1 or 0) values where 1 is a "positive event" and 0 is the reference.
I wonder how I do in JMP to get the results of these sample data (these are just examples and not the real data) and I would like to be able to present it like below. I would prefer an instruction of how to do it in an interactive mode. However, if possible also in a scripting answer. My knowledge of how to use JMP regarding programming is somewhat better than my statistical knowledge.
| Univariable analysis | Multivariable analysis |
| Hazard ratio (95% confidence interval) | p | Hazard ratio (95% confidence interval) | p |
| | | | |
Hilar stricture (Reference non-hilar) | 0.00 (0.00-0.00) | | 0.00 (0.00-0.00) | |
| | | | |
Male (Reference Female) | 0.00 (0.00-0.00) | | 0.00 (0.00-0.00) | |
| | | | |
Age ≥ 75 years (Reference <75 years) | 0.00 (0.00-0.00) | | 0.00 (0.00-0.00) | |
| | | | |
ASA III-IV (reference ASA I-II) | 0.00 (0.00-0.00) | | 0.00 (0.00-0.00) | |
Below is the example file:
Hilar stenosis | Gender | Age ≥ 75 years | ASA III-IV | Time to event | Hilar structure (GS) Yes=1 No=0 | Men (GS) Male=1 Female=0 | Age ≥ 75 years =1 else 0 | ASA III-IV=1 else 0 |
No | Male | No | No | 115 | 0 | 1 | 0 | 0 |
No | Female | Yes | No | 157 | 0 | 0 | 1 | 0 |
No | Female | No | Yes | 101 | 0 | 0 | 0 | 1 |
No | Female | Yes | Yes | 138 | 0 | 0 | 1 | 1 |
No | Female | Yes | No | 114 | 0 | 0 | 1 | 0 |
No | Female | No | Yes | 177 | 0 | 0 | 0 | 1 |
No | Female | No | No | 133 | 0 | 0 | 0 | 0 |
No | Female | Yes | No | 39 | 0 | 0 | 1 | 0 |
Yes | Male | Yes | Yes | 29 | 1 | 1 | 1 | 1 |
Yes | Female | Yes | Yes | 7 | 1 | 0 | 1 | 1 |
No | Female | Yes | No | 156 | 0 | 0 | 1 | 0 |
Yes | Female | Yes | Yes | 169 | 1 | 0 | 1 | 1 |
No | Female | No | No | 894 | 0 | 0 | 0 | 0 |
Yes | Female | Yes | No | 303 | 1 | 0 | 1 | 0 |
Yes | Male | No | Yes | 79 | 1 | 1 | 0 | 1 |
No | Female | Yes | Yes | 32 | 0 | 0 | 1 | 1 |
No | Female | No | No | 211 | 0 | 0 | 0 | 0 |
Yes | Male | No | Yes | 248 | 1 | 1 | 0 | 1 |
No | Female | Yes | Yes | 252 | 0 | 0 | 1 | 1 |
No | Male | No | Yes | 456 | 0 | 1 | 0 | 1 |
Of JSL code I have no knowledge.
Sincerely yours
Lars Enochsson
Professor of Surgery
Umeå University
Sweden