fixed or random effects?

Douglas Bates <bates at ...> writes:

On Mon, Oct 1, 2012 at 1:10 PM, joana martelo <jmmartelo at ...> wrote:

[snip]
 
# For you the year factor will have only two levels and that is too few
# to model the effect of year as a random effect.  When you incorporate
# a random-effects term in a model you end up estimating a variance
# component instead of trying to estimate coefficients in a linear model
# expression directly.  Having only two levels of year will not allow
# for a precise estimate of a variance component.  In fact, it will be a
# horribly imprecise estimate.

There are no hard and fast rules of how many levels are required to be
able to estimate a variance component but fewer than 5 is too few and
more than 10 is adequate.  I have used as few as 6 levels but that was
on nicely balanced data from a designed experiment.  Observational
data that is highly unbalanced requires more care.

jinx (snap):

http://separatedbyacommonlanguage.blogspot.ca/2006/10/jinx-and-snap.html

(making
   gmane
     happy
       with
         more
           stuff)