R help - Feb 2006 - R-newbie-question, fixed effects panel model, large number of observations

Hi,

I'm trying to fit a fixed effect (LSDV) panelmodel with R. I have a dataset
with y as dependent, x1&x2 as indeps, t as time index and i as an
id-variable for each individual. There are three observations for each
individual (t=1, t=2, t=3).

I want to try a simple regression, but with individual intercepts:

-------------------------------------------------
# reading in some data ...

mydata <- read.csv(...)
attach(mydata)

# fit modell

mymodel <- lm(y ~ -1 + factor(i) + x1 + x2)
summary(mymodel)
-------------------------------------------------

Works fine when the size of my dataset doesn't exceed about n=5000
observations, but I have some more. Can I do a partitioned regression with
R, are there any other options already implemented in R ?

Thanks,
Thomas

This is one function I wrote.
http://sociology.yculblog.com/post.794856.html



2006/2/12, Thomas Wilde <thomas.wilde at gmx.de>:
> Hi,
>
> I'm trying to fit a fixed effect (LSDV) panelmodel with R. I have a
dataset
> with y as dependent, x1&x2 as indeps, t as time index and i as an
> id-variable for each individual. There are three observations for each
> individual (t=1, t=2, t=3).
>
> I want to try a simple regression, but with individual intercepts:
>
> -------------------------------------------------
> # reading in some data ...
>
> mydata <- read.csv(...)
> attach(mydata)
>
> # fit modell
>
> mymodel <- lm(y ~ -1 + factor(i) + x1 + x2)
> summary(mymodel)
> -------------------------------------------------
>
> Works fine when the size of my dataset doesn't exceed about n=5000
> observations, but I have some more. Can I do a partitioned regression with
> R, are there any other options already implemented in R ?
>
> Thanks,
> Thomas
>
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--
伝伷伻佡伖侒
Deparment of Sociology
Fudan University