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Ch. 7: Randomized Experiments and Causal Inference

Ch. 7: Randomized Experiments and Causal Inference. Randomized Experiments. Experiments where participants are randomly assigned to the experimental groups or conditions. Often referred to as “true experiments.”. Reasons for Using Random Assignment.

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Ch. 7: Randomized Experiments and Causal Inference

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  1. Ch. 7: Randomized Experiments and Causal Inference

  2. Randomized Experiments • Experiments where participants are randomly assigned to the experimental groups or conditions. • Often referred to as “true experiments.”

  3. Reasons for Using Random Assignment • Provides a safeguard against biased assignment of sampling units to the different treatment groups. • Distributes the characteristics of the sampling units over the different conditions to prevent biased outcomes. • Permits the use of statistical analyses that require certain data characteristics.

  4. Ways of Achieving Random Assignment • Presorting booklets or questionnaires • Blindly drawing names • Flipping a coin • Consulting a table of random numbers

  5. Between-Subjects Designs • Subjects are exposed to one condition each. • Also called nested designs.

  6. Within-Subjects Design • Subjects are exposed to each condition. • Also called: • Repeated-measures design • Crossed design • Importance of counter-balancing

  7. Latin Squares Design

  8. Factorial Designs • Design has more than one factor and two or more levels of each factor

  9. Aristotle’s Four Kinds of Causation • Material • Formal • Final • Efficient

  10. Three Criteria of Efficient Causation • Covariation • Temporal precedence • Internal validity

  11. Mill’s Methods • Method of agreement • If X, then Y. • X is a sufficient condition of Y. • Method of difference • If not-X, then not-Y. • X is a necessary condition of Y.

  12. Mill’s Methods and the Simple Randomized Design

  13. Solomon Four-Group Design

  14. Plausible Causal Events in the Solomon Design

  15. Diagramming the Solomon Design R = Randomization O = Observation X = Treatment exposure

  16. Preexperimental Designs • One-shot case study: • Symbolized as X-O • where X = treatment exposure andO = observation • One-group pre-post design • Symbolized as O-X-O

  17. Examples of Potential Threats to Internal Validity • History • Maturation • Instrumentation • Selection

  18. The Social Psychology of the Experiment • Artifact: A finding resulting from conditions other than those intended by the experimenter. • Demand characteristics & the good subject • Use of quasi-control subjects • Experimenter Expectancy Effect • Use of blind experimenters and double-blind procedures

  19. Basic Expectancy Control Design

  20. Burnham’s (1966) Use of the Expectancy Control Design

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