On Fri, 23 Jul 2010, Christopher David Desjardins wrote:
Hi,
I am trying to fit the following model:
sr.reg.s4.nore <- survreg(Surv(age_sym4,sym4), as.factor(lifedxm),
data=bip.surv)
Next time include a reproducible example. i.e. something we can run.
Now, Google "Hauck Donner Effect" to understand why
anova(sr.reg.s4.nore)
is preferred.
Chuck
Where age_sym4 is the age that a subject develops clinical thought
problems; sym4 is whether they develop clinical thoughts problems (0 or
1); and lifedxm is mother's diagnosis: BIPOLAR, MAJOR DEPRESSION, or
CONTROL.
I am interested in whether or not survival differs by this covariate.
When I run my model, I am getting the following output:
summary(sr.reg.s4.nore)
Call:
survreg(formula = Surv(age_sym4, sym4) ~ as.factor(lifedxm),
data = bip.surv)
Value Std. Error z p
(Intercept) 4.037 0.455 8.86643
0.000000000000000000755
as.factor(lifedxm)CONTROL 14.844 4707.383 0.00315
0.997484052845082791450
as.factor(lifedxm)MAJOR 0.706 0.447 1.58037
0.114022774867277756905
Log(scale) -0.290 0.267 -1.08493
0.277952437474223823521
Scale= 0.748
Weibull distribution
Loglik(model)= -76.3 Loglik(intercept only)= -82.6
Chisq= 12.73 on 2 degrees of freedom, p= 0.0017
Number of Newton-Raphson Iterations: 21
n=186 (6 observations deleted due to missingness)
I am concerned about the p-value of 0.997 and the SE of 4707. I am
curious if it has to do with the fact that the CONTROL group doesn't
have a mixed response, meaning that all my subjects do not develop
clinical levels of thought problems and subsequently 'survive'.
table(bip.surv$sym4,bip.surv$lifedxm)
BIPOLAR CONTROL MAJOR
0 41 60 78
1 7 0 6
Is there some sort of way that I can overcome this? Is my model
misspecified? Is this better suited to be run as a Bayesian model using
priors to overcome the lack of a mixed response?
Also, please cc me on an email as I am a digest subscriber.
Thanks,
Chris
--
Christopher David Desjardins
PhD student, Quantitative Methods in Education
MS student, Statistics
University of Minnesota
192 Education Sciences Building
http://cddesjardins.wordpress.com
______________________________________________
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Charles C. Berry (858) 534-2098
Dept of Family/Preventive Medicine
E mailto:cbe...@tajo.ucsd.edu UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
