[R] tests for significance on conditional inference trees from party package

Adrian Johnson oriolebaltimore at gmail.com
Tue Dec 13 20:19:52 CET 2016

Dear group,
Please allow me to ask a naive question and pardon if it is qualified
as stupid question.

I am using party package to classify covariates and predict
distribution of survival times for the classified variables.
Typically I have a matrix of covariates (columns) including outcome
data (overall survival in months, censor status) and other covariates
I want to split in tree (such as treatment dose etc. ) . Rows are
patients (~1000 patients).

Now similarly I have many such matrices (4K)  with completely
different set of covariates but identical outcome data and patients
(in rows). i cannot combine all data into a giant matrix,because these
covariates are totally independent.

Currently I am running this model in a loop and storing the tree and
parsing the tree structure.

My question is, is there some testing method to choose or rank these
4K trees such that I can select each tree from top to bottom. I know
each tree is important in its own way.    If selection based on
significance is required, then is there any other way instead of
conditional inference tree , that partitions data but will also carry
some significance to choose from.


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