Indicator Construction 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. QUESTION: Submit by a 2- to 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. o If a sample or sample survey will be used, discuss the sampling frame or the sampling strategy you intend to use. ____________________________________________________________________________________ Introduction Now that you have started developing your evaluation design, how are you going to collect the necessary information that will give you the answers to your questions? Is there preliminary or baseline data on the program participants or beneficiaries of the program? Are both the incidence and prevalence of the problems your program is designed to address well documented? What types of data are appropriate for your evaluation? What are your variables of interest and how are you going to measure these? Evaluations rely heavily on data. The good news is that you have a variety of methods that can be used to collect the data. The data can be baseline data, secondary data, surveys, censuses, case studies, and qualitative information. However, data collection issues such as data quality, coverage, costs, and ethics are major considerations in any data collection effort. The Learning Resources this week will focus on problems having to do with collecting data, given specific evaluation designs, measures, indicators of concepts of interest, and relevant units of observation. You will also concentrate on issues having to do with measurement and the selection of units of analysis. Learning Objectives Students will: Evaluate design and data collection problems Analyze the relevance of program evaluation Analyze selection of cases by dependent variable Develop input, output, and outcome program indicators Analyze data collection strategies ____________________________________________________________________________________ Required Resources Readings Langbein, L. (2012). Public program evaluation: A statistical guide (2nd ed.). Armonk, NY: ME Sharpe. o Chapter 7, Designing Useful Surveys for Evaluation (pp. 209238) 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 4, Measurement for Program Evaluation and Performance Monitoring (pp. 145185) Geddes, B. (1990). How the cases you choose affect the answers you get: Selection bias in comparative politics. Political Analysis, 2(1), 131150. Retrieved fromhttp://www.nyu.edu/classes/nbeck/q2/geddes.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 fromhttp://www.urban.org/center/cnp/projects/outcomeindicators.cfm 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 fromhttp://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, fromhttp://www.cpc.unc.edu/measure/our-work/secondary-analysis/secondary-analysis-of-data Zeitlin, A. (2014). Sampling and sample size [PowerPoint slides]. Retrieved fromhttp://www.povertyactionlab.org/sites/default/files/2.%20Sampling%20and%20Sample%20Size_AFZ3.pdf

Indicator Construction 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. QUESTION: Submit by a 2- to 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. o If a sample or sample survey will be used, discuss the sampling frame or the sampling strategy you intend to use. ____________________________________________________________________________________ Introduction Now that you have started developing your evaluation design, how are you going to collect the necessary information that will give you the answers to your questions? Is there preliminary or baseline data on the program participants or beneficiaries of the program? Are both the incidence and prevalence of the problems your program is designed to address well documented? What types of data are appropriate for your evaluation? What are your variables of interest and how are you going to measure these? Evaluations rely heavily on data. The good news is that you have a variety of methods that can be used to collect the data. The data can be baseline data, secondary data, surveys, censuses, case studies, and qualitative information. However, data collection issues such as data quality, coverage, costs, and ethics are major considerations in any data collection effort. The Learning Resources this week will focus on problems having to do with collecting data, given specific evaluation designs, measures, indicators of concepts of interest, and relevant units of observation. You will also concentrate on issues having to do with measurement and the selection of units of analysis. Learning Objectives Students will: Evaluate design and data collection problems Analyze the relevance of program evaluation Analyze selection of cases by dependent variable Develop input, output, and outcome program indicators Analyze data collection strategies ____________________________________________________________________________________ Required Resources Readings Langbein, L. (2012). Public program evaluation: A statistical guide (2nd ed.). Armonk, NY: ME Sharpe. o Chapter 7, Designing Useful Surveys for Evaluation (pp. 209238) 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 4, Measurement for Program Evaluation and Performance Monitoring (pp. 145185) Geddes, B. (1990). How the cases you choose affect the answers you get: Selection bias in comparative politics. Political Analysis, 2(1), 131150. Retrieved fromhttp://www.nyu.edu/classes/nbeck/q2/geddes.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 fromhttp://www.urban.org/center/cnp/projects/outcomeindicators.cfm 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 fromhttp://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, fromhttp://www.cpc.unc.edu/measure/our-work/secondary-analysis/secondary-analysis-of-data Zeitlin, A. (2014). Sampling and sample size [PowerPoint slides]. Retrieved fromhttp://www.povertyactionlab.org/sites/default/files/2.%20Sampling%20and%20Sample%20Size_AFZ3.pdf