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Designs: Experimental Designs, Quasi Experiments, and Non-Experimental Designs QUESTION: 1 to 2 pages 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. ______________________________________________________________________ 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 weeks 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 ______________________________________________________________________ Required Resources Readings Langbein, L. (2012). Public program evaluation: A statistical guide (2nd ed.). Armonk, NY: ME Sharpe. o Chapter 2, Defensible Program Evaluations: Four Types of Validity (pp. 2650) o Chapter 3, Internal Validity: The Logic of Internal Validity (pp. 5172) McDavid, J. C., Huse, I., & Hawthorn, L. R. L. (2013). Program evaluation and performance measurement: An introduction to practice (2nd ed.). Thousand Oaks, CA: Sage. o Chapter 3, Research Designs for Program Evaluations (pp. 89144) United States Government Accountability Office (USGAO). (2012). Designs for assessing program implementation and effectiveness. In Designing evaluations: 2012 revision (pp. 3149). Retrieved fromhttp://www.gao.gov/assets/590/588146.pdf

Date Posted: 18/09/2015
Category: General
Due Date: 22/09/2015
Instruction
Designs: Experimental Designs, Quasi Experiments, and Non-Experimental Designs QUESTION: 1 to 2 pages 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. ______________________________________________________________________ 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 weeks 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 ______________________________________________________________________ Required Resources Readings Langbein, L. (2012). Public program evaluation: A statistical guide (2nd ed.). Armonk, NY: ME Sharpe. o Chapter 2, Defensible Program Evaluations: Four Types of Validity (pp. 2650) o Chapter 3, Internal Validity: The Logic of Internal Validity (pp. 5172) McDavid, J. C., Huse, I., & Hawthorn, L. R. L. (2013). Program evaluation and performance measurement: An introduction to practice (2nd ed.). Thousand Oaks, CA: Sage. o Chapter 3, Research Designs for Program Evaluations (pp. 89144) United States Government Accountability Office (USGAO). (2012). Designs for assessing program implementation and effectiveness. In Designing evaluations: 2012 revision (pp. 3149). Retrieved fromhttp://www.gao.gov/assets/590/588146.pdf
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Topwrite 11 years ago
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    Topwrite | Sep 23, 2015, 00:45 AM
  • Hello, I do like the examples you have given as far as you explaining experimental Designs, Quasi Experiments and Non-Experimental Designs. However, the question is asking you to choose two of the four scenarios listed below. 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 Please, read the instructions again and revise the assignment asap. I am running late with this. Thanks
    User_7413 | Sep 23, 2015, 01:47 AM
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    Topwrite | Sep 23, 2015, 03:51 AM
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    Topwrite | Sep 23, 2015, 10:55 AM
  • Hello Profpeterjohnson, I am still having a problem with this response. Again, you have to pick two causal claims from these group: 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. ________________________________________________________________________________ The claims you have on the post are none of these four above. Please response asap. Thanks
    User_7413 | Sep 23, 2015, 11:29 AM
  • am really sorry for that, i uploaded the wrong file, i know i have delayed, kindly forgive me, am uploading the right one right away
    Topwrite | Sep 23, 2015, 11:56 AM
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    Topwrite | Sep 23, 2015, 12:00 PM
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    Topwrite | Sep 23, 2015, 12:52 PM
  • Thanks for now. All is Ok.
    User_7413 | Sep 24, 2015, 03:28 AM
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