Dear R users,
I have a couple of linear model related questions.
1) How do I produce a fixed effect linear model using lme? I saw somewhere
(this may be Splus documentation since I use Splus and R interchangeably)
that using lme(...,random= ~ -1 | groups,...) works, but it gives the same
as lme(...,random= ~ 1 | groups,...), ie. fits a random effect intercept
term.
The reason why I want to do this is test for the significance of the
random effect intercept term. anova( , ) does not work for an lm model and
lme model together.
2) Is there some nice way of handling linear models which are of the form
response_ij = a_i + b_i x_ij + \epsilon_ij
where a_i and b_i are fixed effects, x_ij is given (continuous) data,
\epsilon_ij ~ N(0, \sigma^2), and the i's range over some group? This is
basically a group of regression models, but I want them handled as one
unit for the purposes of estimation of \sigma^2 etc. I know that lmList()
does fit such a model, but does so as a group of separate models. I can
see that this would be possible to do this using lm() and indicator
variables, but this seems like a clumsy approach. Surely there is a better
way.
Sincerely, Faheem Mitha.
-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !) To: r-help-request at
stat.math.ethz.ch
_._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
FAHEEM MITHA <faheem at email.unc.edu> writes:> I have a couple of linear model related questions. > > 1) How do I produce a fixed effect linear model using lme? I saw somewhere > (this may be Splus documentation since I use Splus and R interchangeably) > that using lme(...,random= ~ -1 | groups,...) works, but it gives the same > as lme(...,random= ~ 1 | groups,...), ie. fits a random effect intercept > term.I don't think you can fit a fixed-effects model with lme.> The reason why I want to do this is test for the significance of the > random effect intercept term. anova( , ) does not work for an lm model and > lme model together.You can do this if you list the lme model first in the call to anova().> 2) Is there some nice way of handling linear models which are of the form > > response_ij = a_i + b_i x_ij + \epsilon_ij > > where a_i and b_i are fixed effects, x_ij is given (continuous) data, > \epsilon_ij ~ N(0, \sigma^2), and the i's range over some group? This is > basically a group of regression models, but I want them handled as one > unit for the purposes of estimation of \sigma^2 etc. I know that lmList() > does fit such a model, but does so as a group of separate models. I can > see that this would be possible to do this using lm() and indicator > variables, but this seems like a clumsy approach. Surely there is a better > way.If you look at the result of summary(fm) where fm is a model fit by lmList you will see that the estimate of \sigma^2 is the pooled estimate. All the standard errors, etc. are based on the pooled estimate of the variance. Alternatively, the section on linear models in Venables and Ripley (1999) shows how to use lm to fit separate models like this. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Dear R people,
If I want to use a package, say nlme, I need to say library(nlme) to
load it. The same with any others. I often forget to do this. Is there
some way of telling R which packages should be loaded at the start?
Sincerely, Faheem Mitha.
-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !) To: r-help-request at
stat.math.ethz.ch
_._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._