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Finally, in addition to ambiguities in what constitutes a
``treatment'' and which treatments should be administered, there may
be substantial ambiguity about what constitues a ``unit of study'' in
an experiment or observational study.
The ``units of study'' are the rows in the Y vector and X matrix
in the matrix form of the regression equations.
Example.
In a study of a new method of teaching mathematics, school district
officials were able to get 60 students in each of nine schools to
participate. In each school, 30 children were randomly assigned to
the ``current'' method, and 30 were assigned to the ``new'' method.
Three teachers taught three classes each of the ``current'' method
classes , and three more taught three classes each of the ``new''
method classes. 
In the example,
children participated in the study,
with 270 children experiencing each teaching method. We might think
of these children as the experimental units. However,
- Because the children interact with one another in the classroom
(in both methods), their responses to the end-of-semester test will be
dependent on one another within each classroom (even if no one cheats
on the exam!). Thus perhaps we should think of the classrooms as the
experimental units; now there are only 9 units in the ``current''
method and 9 units in the ``new'' method.
- Finally, perhaps the teacher also has an influence on the
outcome of the students; then all the children who have the same
teacher will have dependent responses, so perhaps classes within
teacher should be the units of study; now there are only 3 units in
the ``current'' method, and 3 units in the ``new'' method.
This example is frustrating because each of the possible units:
children, classrooms, and teachers, contributes something to the
outcome. Mixed effects linear models, which we will discuss later,
provide one way to ``hedge our bets'' across the three possible
definitions of units in this problem.
Nevertheless, identifying and clearly stating what the units of study
are is an important point in both communication and in understanding
what the data are telling us.
Next: About this document
Up: Uses of ANOVA
Previous: Treatments
Brian Junker
Mon Jan 19 17:10:49 EST 1998