On Thu, 13 Mar 2014, Tim Marcella wrote:
Hi,
I am working with hurdle models in the pscl package to model zero
inflated overdispersed count data and want to incorporate censored
observations into the equation. 33% of the observed positive count data
is right censored, i.e. subject lost to follow up during the duration of
the study. Can this be accounted for in the hurdle() function?
No, this is currently not supported. If the censoring points are fixed
(e.g., counts of "5" actually mean "5 or more") then using an ordinal
model might be an alternative to using a count model. However, if the
censoring points differ, then I wouldn't know of a package that provides
this out of the box...
Thanks, Tim
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