Hello,
@Bert: I didn't expect a full tutorial service but probably a hint of
the Masters of statistics ;)
Anyway I posted my question again on a special statistic
forum. Your hint about the censored regression: I don't think
that this is the case here. As so far as I understand it is there
the dependent variable censored. In my case is the independent
variable not a fixed value but rather a range.
/J
Am 17.07.2011 um 16:15 schrieb Bert Gunter:
Johannes:
R is not a statistical tutorial service, although kind and able
helpeRs sometimes do reply to such queries. You should try such a
service, for example:
http://stackoverflow.com/
FWIW, this is an example of censoring in regression. R has packages
for this, but you need to learn more or get help to use them properly,
as you, yourself, indicated.
-- Bert
On Sun, Jul 17, 2011 at 3:01 AM, Johannes Radinger
<jradin...@gmx.at> wrote:
Hello R-people!
I have a general statistical question about regressions. I just
want to
describe my case:
I have got a dataset of around 150 observations and 1 dependent and 2
independent variables.
The dependent variable is of metric nature (in my case meters in a
range
from around 0.5-10000 m). The first independent is also metric (in mm
ranging from 50-700 mm) and it is assumed to be in a linear
relation with
the dependend one. So that is not a problem at all to do a
typicall linear
regression on that.
No there is the second independent variable. This is also of
metric nature
and gives information on time (ranging from 1 day to 800 days) but
here
sometimes is this variable not exactly clear, I know for example a
range
(1-2 days) or less than x days etc. So my dataset could look like
this:
measured dependent variable in days:
1
15
7-9
<2
<9
24
4
4-7
So my question: Is there a general method to include such types of
variables
into a regression analysis?
Secondly I assume that there is not a linear relation given, it is
more of a
logarithmic nature so that the influence of the time on the dependent
variable decreases with increasing size.
So in short my questions:
* How can I use variable values like <5 or 4-5 in a regression
* Is it possible to combine the linear relationship with a
logarithmic one
in a multiple regression
*How can that be done in R, are there any special packages you'd
recommend?
Thank you very much
best regards
Johannes
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--
"Men by nature long to get on to the ultimate truths, and will often
be impatient with elementary studies or fight shy of them. If it were
possible to reach the ultimate truths without the elementary studies
usually prefixed to them, these would not be preparatory studies but
superfluous diversions."
-- Maimonides (1135-1204)
Bert Gunter
Genentech Nonclinical Biostatistics
467-7374
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/
pdb-biostatistics/pdb-ncb-home.htm
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