(no subject)

Perfect. Thank you. It is good to know that we can specify the
random-effects variance
equal to zero. Thanks.
Peter


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On Wed, Aug 1, 2018 at 10:57 PM, Ben Bolker <bbolker at gmail.com> wrote:

  (please keep r-sig-mixed-models in the Cc:)

  I'm pretty sure that lmer and lm models are commensurate, in case that
helps.  Here's an example rigged to make the random-effects variance
equal to zero, so we can check that the log-likelihoods etc. are
identical.

set.seed(101)
dd <- data.frame(y=rnorm(20),x=rnorm(20),f=factor(rep(1:2,10)))
library(lme4)
m1 <- lmer(y~x+(1|f),data=dd,REML=FALSE) ## estimated sigma^2_f=0
m2 <- lm(y~x,data=dd)
all.equal(c(logLik(m1)),c(logLik(m2))) ## TRUE
all.equal(fixef(m1),coef(m2))
anova(m1,m2)


On 2018-08-01 11:41 PM, Peter Paprzycki wrote:

Thank you. Oh, was just trying to compare my random-effects model to the
one where my grouping variable (schools) is treated as fixed.

Peter

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On Wed, Aug 1, 2018 at 10:32 PM, Ben Bolker <bbolker at gmail.com
<mailto:bbolker at gmail.com>> wrote:


      I'm not 100% sure I understand the question, but I think the

answer is

    "no": lmer cannot fit a model that doesn't contain any random

effects.

    Perhaps you can give more context as to why it won't work for you to
    revert to lm() or plm() in these cases?

    On 2018-08-01 11:30 PM, Peter Paprzycki wrote:

    > This is very basic, is there a way to specify in lmer function

    that I would

    > like to run my grouping variable as a fixed factor only, without

    reverting

    > to lm or plm functions. If one does not specify a random variable,

    one gets

    > the error message with lmer function; something that is equivalent

    to the

    > statement, "index = "grouping variable", model = "within"" with

    the plm

    > function.
    >
    >

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--

Peter Paprzycki, Ph.D.
Visiting Assistant Professor
Research Support Center Manager

Educational Research and Administration
College of Education and Psychology
The University of Southern Mississippi
USM Box 5093; 118 College Drive
Hattiesburg, Mississippi 39406-0001
tel. (601)-266-4708
email: Peter.Paprzycki at usm.edu <mailto:Peter.Paprzycki at usm.edu>


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--

Peter Paprzycki, Ph.D.
Visiting Assistant Professor
Research Support Center Manager

Educational Research and Administration
College of Education and Psychology
The University of Southern Mississippi
USM Box 5093; 118 College Drive
Hattiesburg, Mississippi 39406-0001
tel. (601)-266-4708
email: Peter.Paprzycki at usm.edu


Sidere mens eadum mutato