Thanks, it is helpful. I knew there were several modeling capacities built into this package "rms". I would just like to have a general ideal how the points for each predictor determined. I read a paper by Lasonos et al 2008. It mentioned it was by the size of the effect. -- View this message in context: http://r.789695.n4.nabble.com/package-rms-nomogram-tp4638552p4638813.html Sent from the R help mailing list archive at Nabble.com.
package "rms" nomogram
4 messages · B787s, David Winsemius
Putting context back in.
On Jul 31, 2012, at 9:01 AM, B787s wrote:
Dear R-Help, I am using 'rms' package to draw nomogram. I wonder how is the "Points" determined for each predictor in the model? Is it by the coefficient estimate (beta) relative to the highest effect in the model or?
It would be better if you asked this question about a specific example because the rms package has many sorts of regression fit- objects for which nomogram will provide results. The linear predictor in a regression method will have contributions from each of the terms, so I would have said that the variate scales were being displayed relative to the mean values rather than relative to the "highest effect" ... what ever that term means to you. The upper portion of a nomogram is used to calculate "Points", while the lower portion is used to calculate probability of event by transforming from the linear predictor scale to the response scale. A unit-increment in "Points" displayed by 'plot.nomogram' for one variate will be related to a unit increment of another variate by the ratios of their coefficients.
Thanks Lin
David Winsemius, MD
On Aug 1, 2012, at 6:22 PM, B787s wrote:
Thanks, it is helpful. I knew there were several modeling capacities built into this package "rms". I would just like to have a general ideal how the points for each predictor determined. I read a paper by Lasonos et al 2008. It mentioned it was by the size of the effect.
Let me guess.... it's the one lying behind the request for US$ at: http://jco.ascopubs.org/content/26/8/1364.long It seems possible the conceptual gaps may be in the degree to which you understand how glm() functions work. Do you have a working understanding of what a linear predictor is? Do you understand what a link function does? Do you understand that a unit change in the linear predictor will not imply a unit change in the response unless the link function is "identity"? If the article did not cover those topics then you were ill-served.
David Winsemius, MD Alameda, CA, USA
well, the article from this high impact factor journal mentioned about each step for building a nomogram including interpretation without going too much detail into statistical concept. All I want to know is what the R code does to come up with the graph, and not raising attention or get someone to review what the posting needs to be and what I need to know. My question is at the end, unanswered. -- View this message in context: http://r.789695.n4.nabble.com/package-rms-nomogram-tp4638552p4638819.html Sent from the R help mailing list archive at Nabble.com.
On Aug 1, 2012, at 8:09 PM, B787s wrote:
well, the article from this high impact factor journal mentioned about each step for building a nomogram including interpretation without going too much detail into statistical concept. All I want to know is what the R code does to come up with the graph, and not raising attention or get someone to review what the posting needs to be and what I need to know. My question is at the end, unanswered.
Well, indeed. You might want to examine your own contributions to this difficulty you are facing. You cited an article (probably) in a journal that is not available to me without several hours of work on my part. (You also cited it only by misspelling the first author's name ... which you misspelled.) Apparently it was not on a particularly high level of mathematical detail. You are posting only with the name of airplanes but otherwise without any identification. You offer no information about your efforts at searching for tutorials. (I found several readily available.) Please read the Posting Guide for better understanding of how the contributors to this mailing list view the responsibilities of questioners.
David Winsemius, MD Alameda, CA, USA