Indicator Construction 8321

 Now that you have thought through a logical model or framework for your Final Project, it is time to develop preliminary input, output, and outcome indicators. For this Assignment, use the guidelines from the Urban Institute resource and consult relevant Optional Resources from this week. 

 3-page paper which describes your input, output, and outcome program indicators, including the following:

• Describe the variables and the data you will be using.
• Provide a realistic discussion of the availability of research data.
• Provide an analysis of intended data collection strategies.
  • If a sample or sample survey will be used, discuss the sampling frame or the sampling strategy you intend to use.

Optional Resources

Note: Consult the following resources based on your interest and relevance to your project:

Bamberger, M. (2010). Reconstructuring baseline data for impact evaluation and results measurement. Retrieved from http://siteresources.worldbank.org/INTPOVERTY/Resources/335642-1276521901256/premnoteME4.pdf

Parnaby, P. (2006). Evaluation through surveys [Blog post]. Retrieved from http://www.idea.org/blog/2006/04/01/evaluation-through-surveys/

Rutgers, New Jersey Agricultural Experiment Station. (2014). Developing a survey instrument. Retrieved from http://njaes.rutgers.edu/evaluation/resources/survey-instrument.asp

MEASURE Evaluation. (n.d.). Secondary analysis of data. Retrieved February 24, 2015, from http://www.cpc.unc.edu/measure/our-work/secondary-analysis/secondary-analysis-of-data

Zeitlin, A. (2014). Sampling and sample size [PowerPoint slides]. Retrieved from http://www.povertyactionlab.org/sites/default/files/2.%20Sampling%20and%20Sample%20Size_AFZ3.pdf

Required Readings

Langbein, L. (2012). Public program evaluation: A statistical guide (2nd ed.). Armonk, NY: ME Sharpe.
Chapter 7, “Designing Useful Surveys for Evaluation” (pp. 209–238)

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 4, “Measurement for Program Evaluation and Performance Monitoring” (pp. 161-199)

Geddes, B. (1990). How the cases you choose affect the answers you get: Selection bias in comparative politics. Political Analysis, 2(1), 131–150. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.372.5896&rep=rep1&type=pdf

Levitt, S., & List, J. (2009). Was there really a Hawthorne effect at the Hawthorne plant? An analysis of the original illumination experiments. Retrieved from http://www.nber.org/papers/w15016.pdf

Urban Institute. (2014). Outcome indicators project. Retrieved from http://www.urban.org/center/cnp/projects/outcomeindicators.cfm