| Between-subjects design | An experimental design in which different groups of subjects are exposed to the various levels of the independent variable.
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| Within-subjects design | An experimental design in which each subject is exposed to all levels of an independent variable.
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| Single-subject design | An experimental design that focuses on the behavior of an individual subject rather than groups of subjects.
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| Error variance | Variability in the value of the dependent variable that is related to extraneous variables and not to the variability in the independent variable.
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| Randomized two-group design | A between-subjects design in which subjects are assigned to groups randomly.
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| Parametric design | An experimental design in which the amount of the independent variable is systematically varied across several levels.
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| Nonparametric design | Experimental research design in which levels of the independent variable are represented by different categories rather than differing amounts.
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| Multiple control group design | Single-factor, experimental design that includes two or more control groups.
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| Matched groups design | Between-subjects experimental design in which matched sets of subjects are distributed, at random, one per group across groups of the experiment.
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| Matched pairs design | A two-group matched groups design.
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| Carryover effects | A problem associated with within-subjects designs in which exposure to one level of the independent variable alters the behavior observed under subsequent levels.
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| Counterbalancing | A technique used to combat carryover effects in within-subjects designs. Counterbalancing involves assigning the various treatments of an experiment in a different order for different subjects.
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| Factorial design | An experimental design in which every level of one independent variable is combined with every level of every other independent variable.
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| Main effect | The independent effect of one independent variable in a factorial design on the dependent variable. There are as many main effects as there are independent variables.
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| Interaction | When the effect of one independent variable on the dependent variable in a factorial design changes over the levels of another independent variable.
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| Simple effects | In a factorial analysis of variance (ANOVA), the effect of one factor at a given level (or a combination of levels) of another (or factors).
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| Higher order factorial design | Experimental design that includes more than two independent variables (factors).
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