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BHS 204-01 Methods in Behavioral Sciences I

Explore different experimental designs - between-subjects, multi-level, and factorial designs - to understand treatment effects and interactions in behavioral sciences. Learn how ANOVA and planned comparisons help analyze data.

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BHS 204-01 Methods in Behavioral Sciences I

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  1. BHS 204-01Methods in Behavioral Sciences I May 12, 2003 Chapter 8 (Ray) Between-Subjects Designs

  2. Completely Randomized Design • Two groups: • Treatment group – randomly assigned, receives treatment, then measurement. • Control group – randomly assigned, receives no treatment (placebo), then measurement. • Each subject must be equally likely to be placed in either group. • Dependent variable is compared – treatment effect.

  3. Multi-Level Design • Instead of a treatment group and a control group, the independent variable occurs at multiple levels: • R Group A Level 1 T M • R Group B Level 2 T M • R Group C Level 3 T M • R Group D Level 4 T M • Analyzed using ANOVA (F-ratio) and planned comparisons (t-tests).

  4. Factorial Design • Multiple independent variables (factors), each with at least two levels. • Each level of each independent variable must exist for the other independent variable. • The dependent variable (measurement) is the same for all groups (conditions). • Treatment effects are called main effects. • Independent variables may combine to cause interaction effects.

  5. Figure 8.3. (p. 175)Matrix showing the four possible combinations of each of the two levels of a 2 x 2 factorial random-subject design. Notice that each cell contains one of the four possible combinations of our two independent variables (housing condition and feeding schedule.

  6. Figure 8.2. (p. 173)Schematic representation of 2 x 2, 3 x 3, and 2 x 3 x 2 factorial designs. Note that the total number of treatment conditions in each design can be obtained by multiplying the number of levels of each factor.

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