This is the type of comment that raises real doubts in my mind about statistical analysis. It comes from a multilevel graduate class.

**Observations are pooled (i.e., groups are**

combined and group membership ignored) to

estimate model coefficients. For example, data

from students within schools would be analyzed

at the student level (ignoring schools) even if

school features are of interest.

Between-group variation is ignored.

Estimates are OK when variation between

groups is negligible (e.g., school means are

comparable).

When between-group variation is not negligible,

larger groups will dominate the analysis.

combined and group membership ignored) to

estimate model coefficients. For example, data

from students within schools would be analyzed

at the student level (ignoring schools) even if

school features are of interest.

Between-group variation is ignored.

Estimates are OK when variation between

groups is negligible (e.g., school means are

comparable).

When between-group variation is not negligible,

larger groups will dominate the analysis.

SE will be invalid as well I believe.

Given that almost everything is nested inside of something, and between group variation will not be negligible, this would seem to invalidate much or all of linear and logistic regression. Similar limits come up all the time for other methods.

So if these type of problems are in fact common, how much of the analysis done is actually valid?