This is very nice also. I am going to use this approach in the future when I
use lm. However, I can't seem to get to work the way I want with cenmle. I
will continue to experiment. Thanks folks for the suggestions.
Tom
David Winsemius wrote:
>
>
> On Nov 12, 2008, at 8:48 AM, Tom La Bone wro
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. Errorz p
(Intercept) 1.19473 0.0772 15.4
Oh, I like your answer better than mine! Thanks.
Tom
Richard Cotton 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
> 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. Errorz p
> (Intercept) 1.19473 0.0772 15.4695 5.58e-54
> groups1 0.00208
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. Errorz p
(Intercept) 1.19473 0.0772 15.4695 5.58e-54
groups1 0.00208 0.0789 0.026
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 wit
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