Designs: experimental designs, quasi experiments, and


 

Validity issues of causal claims are always at the forefront of evaluation design. It is critical for the evaluator to understand issues of internal, external, measurement, and statistical validity. Though the classical experiment remains the standard for evaluating statistical and causal rigor, many evaluations continue to use quasi experiments and non-experimental designs.

For this Discussion, review this week’s Learning Resources and pick two of the following scenarios of causal claim:

  1. Field Experiment: Minimum wage legislation will lead to higher unemployment
  2. Cross Sectional Study: Capital punishment deters crime
  3. Time Series Study: Privatization of government-owned industries will increase economic growth
  4. Time Series Study: Airline deregulation will result in lower airfares

ASSIGNMENT:  an evaluation of the most important validity issues of each causal claim chosen. Explain the variety of validity issues possible in each scenario and provide a rationale for what qualifies as “most important” to you. Your evaluation should also include identifying illustrative and supportive examples related to the scenarios, as well as relevant and credible references from your Learning Resources and Walden Library. 

READINGS:  

Required Readings

Langbein, L. (2012). Public program evaluation: A statistical guide (2nd ed.). Armonk, NY: ME Sharpe.
Chapter 2, “Defensible Program Evaluations: Four Types of Validity” (pp. 26–50)
Chapter 3, “Internal Validity: The Logic of Internal Validity” (pp. 51–72)

McDavid, J. C., Huse, I., & Hawthorn, L. R. L. (2019). Program evaluation and performance measurement: An introduction to practice (3rd ed.). Thousand Oaks, CA: Sage.
Chapter 3, “Research Designs for Program Evaluations” (pp. 97-155)

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