I. Comparing multiple treatments in the same experiment
II. Taking the risk out of choosing the "right" levels of the independent variable so that you:
A. Don't overlook relationships among variablesB. Discover the nature of the relationship
1. Types of relationships (linear, quadratic [e.g., positively accelerating, negatively accelerating], cubic, etc.)2. Value of determining the nature of relationship
a. Refining theory3. How to choose levelsb. Improving ability to generalize to unexplored values
a. Number of levelsb. How far apart (proportionately)
III. Why multiple control groups are often needed
A. Confounding factors:
1. Hypothesis guessingB. Absence of a "correct" comparison group. For example, should therapy be compared against no-treatment or against a placebo treatment?2. Nontreatment differences between treatment and control conditions