I am using the mle2 function to run a simple linear model with a normal
distribution. I have one continuous variable (X) and one factor (treatment)
with 6 levels. I have seen ANCOVA examples similar to this, but my goal is
to compare the differences in the slope parameters (the interaction term)
am
On Dec 12, 2011, at 3:38 PM, Uwe Ligges wrote:
On 12.12.2011 19:36, Brian Jensvold wrote:
I am doing a logistic regression, and by accident I included a field
which has the 2digit abbreviation for all 50 states labeled "st".
I was
surprised to see that the glm did not come up with an erro
On 12.12.2011 19:36, Brian Jensvold wrote:
I am doing a logistic regression, and by accident I included a field
which has the 2digit abbreviation for all 50 states labeled "st". I was
surprised to see that the glm did not come up with an error message but
instead appears to have automatically
I am doing a logistic regression, and by accident I included a field
which has the 2digit abbreviation for all 50 states labeled "st". I was
surprised to see that the glm did not come up with an error message but
instead appears to have automatically broken down this field into
individual fields (
binary features.
However, you may find 120 variables is not much data.
Andrew
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Lorenzo Isella
Sent: Thursday, February 17, 2011 7:14 AM
To: r-help
Subject: [R] Categorical Variables
Dear All,
Please consider a dataframe like the one below (I am showing only a few
rows).
role degree strength weight count disparity intermittency
P 10 82 18017 2 2.317073 5.550314e-05
P 7 529 434560 5.178466 6.904488e-03
I'm a new to the R world and I have been following the John Fox Appendix on
Cox regression
(http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-cox-regression.pdf)
to run some analyses. I have been able to generate models and some simple
figures e.g.:
>library(splines) #required for surv
Hello,
I am looking to generate propensity score in R using ps() command. My
question comes from how to include categorical variables in the equation to
generate propensity score. How should I include reference category in the
estimation? Should I drop the reference group manually before running t
on 01/23/2009 11:10 AM Stephen Collins wrote:
> When including categorical variables in a regression, the default in R is
> to set the first level as the base. Is there an option to specify a
> different level as the base?
See ?relevel and the See Also's listed therein.
HTH,
Marc Schwartz
_
-
Von: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Im
Auftrag von Stephen Collins
Gesendet: Friday, January 23, 2009 12:10 PM
An: r-h...@stat.math.ethz.ch
Betreff: [R] Categorical Variables and glm()
When including categorical variables in a regression, the default in R
When including categorical variables in a regression, the default in R is
to set the first level as the base. Is there an option to specify a
different level as the base?
Regards,
Stephen Collins, MPP | Analyst
Health & Benefits | Aon Consulting
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