Hi ,
I was hoping I could get some advice on doing
regression analysis when the data comes from few
clusters. The data I am using comes from 12 clusters
and the mean cluster size is around 30. I understand
that some standard methods for regression analysis
using clusterd data (e.g. multiple linear regression,
GEE) provide consistent estimates only when the number
of clusters is large. What would be the best approach
in my case where there are few clusters of reasonably
large size ? Would RE, RE with ML or FE models be
appropriate. Would love to hear form you and many
thanks in advance.
Krishna does not give many details. However, a fixed cluster effect model
estimates a different parameter vector from a clustered model. The fixed
effect model estimates the effects that would be observed, if only we could
sample an enormous number of individuals from the population of individuals
in the clusters that we have. A clustered model (including those used in
defining GEEs and even GLLAMMs) estimates the effects that would be
observed, if only we sampled an enormous number of clusters (of similar
size to the clusters we have) from the population of clusters. (There is
also a difference between GEE parameters and GLLAM parameters, namely that
GEEs measure marginal effects in the population of clusters and GLLAMMs
measure conditional effects in the population of clusters, but that is a
separate issue.)
