Methods Cozby Experimental Design 1

Causality Review Remember from Chapter 4 that in order to make a causal inference, you need to satisfy three requirements: 1. Covariation 2. Temporal order 3. Eliminate alternative explanations (3rd variable problem) Confounding • Third variables which are not controlled for are called confounding variables, or simply confounds. Experimental Design Basic experiments • As we already know, experiments address confounding variables through: – Experimental control – Randomization • Experiments establish temporal order by manipulating the independent variable and measuring its effects on the dependent variable. • Thus, the most basic experiment will have only two variables, one IV and one DV, each one with 2 levels. Basic Experiments Example: What is the effect of whining on the sympathy of a romantic partner? Whining (yes/no) Sympathy (1-10) To test this hypothesis in an experiment, there are three steps: 1. Assign participants to conditions 2. Conduct manipulation 3. Measure the dependent variable Step 1: Assigning Participants • Independent Groups (Between subjects) – Assign different participants to each experimental condition • Repeated Measures (Within groups) – Every participant is assigned to every condition of the independent variable Repeated Measures design Advantages – Fewer participants needed – Extremely sensitive to effects of the independent variable • Why? Repeated Measures design Disadvantages Order effects 1. Practice effect 2. Fatigue effect 3. Contrast effect Developmental Designs • Developmental designs explore how individuals change as a function of age. – Cross-sectional – Longitudinal – Sequential Chapter 9: Conducting the Experiment Step 2: Conducting the Manipulation • There are 2 types of manipulation: • Straightforward manipulation – Independent variable is manipulated through written, verbal, or visual materials • Staged manipulation – Event is artificially created by the researcher to: 1. Create a psychological state in participants 2. Increase fidelity to real world Strength of Manipulation • Within ethical and financial limits, a stronger manipulation is generally better. • Remember, if the manipulation is too weak, then it isn’t possible to detect any differences between groups. Step 3: Measuring the DV • Types of Measures: – Self-report – Behavioral – Physiological Measuring the DV Back to our example: Whining (yes/no) Sympathy (1-10) • This design is called a posttest-only design because the participants were only tested once, after the manipulation (hence, posttest). • Contrast this design with the pretest-posttest design (Cozby, p. 141)