On Nov 12, 2008, at 8:48 AM, Tom La Bone wrote:
I figured it out. In case anyone else ever has this question --
given the
following output from cenmle:
fit.cen <- cenmle(obs, censored, groups)
fit.cen
Value Std. Error z p
(Intercept) 1.19473 0.0772 15.4695 5.58e-54
groups1 0.00208 0.0789 0.0263 9.79e-01
Log(scale) -0.40221 0.0168 -23.9034 2.82e-126
Scale= 0.669
Log Normal distribution
Loglik(model)= -3908.9 Loglik(intercept only)= -3908.9
Loglik-r: 0.0006265534
Chisq= 0 on 1 degrees of freedom, p= 0.98
Number of Newton-Raphson Iterations: 1
n = 1766
The p-value is (for example):
p.value <- summary(fit.cen)[[9]][[11]]
An approach that may yield somewhat more self-documenting code would
be to examine either the fit object or the summary object with str and
then to access results by extracting named elements. Since I don't
have the package in question, let me use the lm object on its help
page as an example:
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2,10,20, labels=c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
str(lm.D9)
str(summary(lm.D9))
summary(lm.D9)$coefficients
summary(lm.D9)$coefficients["groupTrt", "Pr(>|t|)"]
# to get the p-value
> summary(lm.D9)$coefficients["groupTrt","Pr(>|t|)"]
[1] 0.2490232
You had originally asked for a method to extract coefficients and for
that purpose you may want to look at:
?coefficients
> slope <- coefficients(lm.D9)["groupTrt"]
> slope
groupTrt
-0.371
--
David Winsemius
Heritage Labs
Tom
Tom La Bone wrote:
The cenmle function is used to fit two sets of censored data and
test if
they are significantly different. I can print out the results of the
analysis on the screen but can't seem to figure out how to access
these
results in R and assign them to new variables, e.g., assign the slope
calculated with cenmle to the variable m. Any suggestions?
Tom
--
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