Consider the case where an experimental variable along with a "participant
variable" are used in a study. That is, levels of one variable are
manipulated by the experimenter and levels of another variable are based on
some inherent participant attribute (i.e. IQ, hair color, race, gender,
etc.). Let's consider one of three situations: 1) the number of participants
per cell varies in proportion to the respective populations 2) the
experimenter uses quota sampling to ensure equal cell sample sizes 3) when
applicable, cut scores are chosen in order to produce equal cell-sizes.

Such situations are common in the behavioral sciences. Furthermore, ANOVA is
commonly used to analyze data collected using such paradigms.

So here are three questions:

1. From an analysis point of view, what problems in data analysis are likely
to arise?
2. IF these problems are not addressed, what are the implications?
3. What is the proper way to analyze such data?

Thanks

Steve Hall- Orlando, FL


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