Re: [R] Dummy variables model

From: Christoph Buser <>
Date: Tue 06 Sep 2005 - 00:47:16 EST


If you'd like to fit a fixed effect model without random effects, you can use lm() or aov() (see ?lm and ?aov). If your variable is a factor (?factor) then you can specify your model in lm() without coding all dummy variables.


Christoph Buser

Christoph Buser <> Seminar fuer Statistik, LEO C13
ETH (Federal Inst. Technology)	8092 Zurich	 SWITZERLAND
phone: x-41-44-632-4673		fax: 632-1228

Tobias Muhlhofer writes:
> Hi, all!
> Anyone know an easy way to specify the following model.
> Panel dataset, with stock through time, by firm.
> I want to run a model of y on a bunch of explanatory variables, and one
> dummy for each firm, which is 1 for observations that come from firm i,
> and 0 everywhere else. I have over 200 firms (and a factor variable that
> contains a firm identifier).
> Any easy way of going about this, without having to define all these
> dummies? I checked lme() with random = ~ 1|firm, but the problem is that
> these are random effects, i.e. that there are firm-by-firm disturbance
> terms and overall disturbance terms, whereas I want just overall
> disturbance terms. This is generally called a "fixed effects" model,
> although it seems like the term "fixed effects" is being used somewhat
> differently in the context of the nlme package.
> Toby
> --
> **************************************************************************
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> !DSPAM:431c4675196241771238468! mailing list PLEASE do read the posting guide! Received on Tue Sep 06 01:07:05 2005

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