Okay the data sets dat1 and dat 2 are the same dat1 just has fewer
covariates.
David, I understand your concern with the number of events and number of
variables I am using however. 611 is only the unique times at which the
events occur where as there are 6987 events in my data of 77272
observatio
My sessionInfo is as follows:
R version 2.15.1 (2012-06-22)
Platform: x86_64-unknown-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_GB.UTF-8LC_COLLATE=en_GB.UTF-8
[5] LC_MONETARY=en_GB.UTF-8LC_MESSAGES=en_GB.UTF-8
[7] LC_PAPER=C
I am unsure if the package mi uses MICE because I can specify the number of
iterations for the mi functions.
Also on a side note:
I have a large data set with 300+ covariates (some are have missing values).
So I was wondering if I should use all the complete covariates for the
imputation models
Hello,
I have a couple of questions with regards to fitting a coxph model to a data
set in R:
I have a very large dataset and wanted to get the baseline hazard using the
basehaz() function in the package : 'survival'.
If I use all the covariates then the output from basehaz(fit), where fit is
a m
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