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Clinical Research: Part 2 Quasi-Experiments

Learn about quasi-experiments, non-equivalent control group design, and interrupted time series design in clinical research and their applications. Explore how these methods differ from true experiments and when to use them.

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Clinical Research: Part 2 Quasi-Experiments

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  1. Clinical Research: Part 2Quasi-Experiments

  2. Reminders • Food day coming soon (5 extra credit points) • Course evaluations: Solely evaluate me/lecture (you will complete a separate evaluation of Jenna/lab the day of Exam 3)

  3. Overview • How does a quasi-experiment differ from a true experiment? • What are the features of different types of quasi-experiments? • When would a quasi-experiment be useful?

  4. Quasi-Experimental Designs • Experiment • Random assignment to two or more groups • Quasi-Experiment • “Quasi” = almost, so an almost-experiment • Could use non-random assignment • Group assignment could be assigned based on some contextual factor (e.g., school, class, company) • Group assignment could be assigned based on some other participant variable (e.g., diagnostic status) • Participants could self-select their group assignment • Researchers/clinicians could assign participants non-randomly (based on personal preferences) • Might only involve one group (no control group)

  5. Non-Equivalent Control Group Design

  6. Non-Equivalent Control Group Design • Choose two groups (e.g., two schools) that are similar • Make one the experimental group and one the comparison group • Examine how scores on a DV change before and after the experimental program is implemented • Because there was no random assignment, the two groups probably differ in a number of ways (e.g. age, gender, ethnicity, personality) • Confounds reduce internal validity (ability to draw causal conclusions) • Reduce the problem of these confounds by choosing a comparison group that matches the experimental group as closely as possible

  7. Intervention to reduce no-shows at Clinic A

  8. Interrupted Time Series Design • Usually no comparison group • Gather data extensively before and after a program is implemented

  9. Lopez Bernal et al. (2013)

  10. Wagenaaret al. (2009)

  11. TrafficFatalities

  12. Frank’s dog died TrafficFatalities

  13. Controlled Interrupted Time Series Design • Strengths of the non-equivalent control group design (has a comparison group) and interrupted time series design (has longitudinal data)

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