On 05/05/2010 11:29 AM, David Foreman wrote:
While
sm4.6ll<-fit.mult.impute(Surv(agesi, si)~partner+ in.love+ pubty+ FPA+
strat(gender),fitter = cph, xtrans = dated.sexrisk2.i, data =
dated.sexrisk2, x=T,y=T,surv=T, time.inc=16)
runs perfectly using Hmisc, Design and mice under R11 run via Sciviews-K,
with
library(Design)
library(mice)
ds2d<-datadist(dated.sexrisk2)
options(datadist="ds2d")
options(contrasts=c("contr.treatment","contr.treatment"))
the equivalent
sm4.6ll<-fit.mult.impute(Surv(agesi, si)~partner+ in.love+ pubty+ FPA+
strat(gender),fitter = *psm*, xtrans = dated.sexrisk2.i, data =
dated.sexrisk2, x=T,y=T,surv=T, time.inc=16)
returns the error message
Error in dimnames(X)<- list(rnam, c("(Intercept)", atr$colnames)) :
length of 'dimnames' [2] not equal to array extent
Using survreg{survival} for which psm is a wrapper, also runs perfectly on
the unimputed dataset.
Is this a bug, or am I doing something wrong? I particularly want to make
use of Design's validation and calibration utilities on multiply imputed
data.
With many thanks for everyone's help
David Foreman
The rms and Design packages do not support the user specifying a
contrast option.
validate and calibrate function do not explicitly support multiple
imputation.
Think about converting the the rms package.
Frank
Consultant and Visiting Professor in Child and Adolescent Psychiatry
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