1) How does one capture the plots from the plsmo procedure? Simply
inserting a routing call to a graphical device (such as jpeg, png, etc)
and then running the plsmo procedure (and then dev.off()) does not route
the output to the file system. 1b) Related to above, has anyone thought
of revising the plsmo procedure to use ggplot? I'd like to capture
several such graphs into a faceted arrangement.
2) The 2nd issue is more about communications than software. I have
developed a model using lrm() and am using plot to display the model.
All that is fairly easy. However, my coauthors are used to traditional
methods, where baseline categories are rather broadly defined (e.g.
males, age 25-40, height 170-180cm, BP 120-140, etc) and results are
reported as odds-ratios, not as probabilities of outcomes.
Therefore, and understandably, they are finding the graphs which arise
from lrm->Predict->plot difficult to interpret. Specifically, in one
graph, the adjusted to population is defined one way, and in another
graph of the same model (displaying new predictors) there will be a new
"adjusted to" population. Sometimes the adjusted populations are
substantially distinct, giving rise to event rates that vary
dramatically across graphs. This can prove challenging when trying to
present the set of graphs as parts of a whole. It all makes sense; it
just adds complexity to introducing these new methods.
One strategy might be to manually define the baseline population across
graphs; this way I could attempt to impose some content-specific
coherence to the graphs, by selecting the baseline populations. Clearly
this is do-able, but I have yet to see it done. I'd welcome suggestions
and comments.
Thanks,
Rob
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