[R] Conditional distribution plot using Model-based Recursive Partitioning

From: Alan Fernihough <alan.fernihough_at_gmail.com>
Date: Thu, 05 May 2011 15:59:37 +0100


Hello,

I am using the party module to estimate the relationship between the probability of being a student and number of siblings (alive). However, I need to include a number of relevant covariates. My code is below:

fm3 <- mob(Student ~ age + alive + sex2 + cwa + cha + cym | Religion+Servant + Literacy, control = ctrl, data = samp2, model = glinearModel, family =binomial())
plot(fm3, tp_args = list(which = "alive"),tnex = 2, type = "simple" )

Which works fine. However, the plots generated do not show the conditional relationship between the dependent and independent variable at each node. Basically, there are spinogram leafs at nodes where the unconditional relationship is the opposite to the conditional relationship -- as given in the summary tables.

I have tried playing around with the plot function arguements, yet to no avail.

Can anybody suggest to me a way which I would be able to plot the tree and have either a conditional spinogram in the leaf or even just text with a number showing a marginal effect or coefficient please?

Thanks,

Alan

-- 
Alan Fernihough
IRCHSS Scholar
UCD School of Economics

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