PRR 475 Review - Tips

1. PRR 475 Review - Tips • Powerpoint Presentations – widgets too • Topic Handouts • Sample Questions • Other Handouts e.g. Statistics • Exercises from Lab • Trochim chapters • Other texts, websites

2. Research/Evaluation Concepts – evaluation.ppt Proposals & Research Design –propdesb.ppt Measurement –measure.ppt Sampling –sample.ppt Survey methods –survey99.ppt Basic Statistics/Data analysis - handouts Experiments –expmt.ppt Observ., qualitative, other methods –QLQN.ppt, econevaluation.ppt Communication & Ethics researchwriting.ppt, ethics.ppt

3. Outline • Definitions of Research/Evaluation • Purposes of Evaluation / Research • Science and Scientific Management • Research/Evaluation as Process • Types of Research / Evaluation

4. Definitions • Evaluation = Process of judging the merit or worth of something • Research • application of scientific methods to answer questions • controlled inquiry directed at increasing knowledge/establishing truth • Evaluation Research - combine the two

5. Body of Knowledge systematic abstract general parsimonious Method of Inquiry logical induction deduction self-corrective empirical Science

6. Scientific Management • Application of scientific principles to management and decision making • systematic information gathering • empirical, objective, self-corrective

7. Research define problem objectives/hypotheses literature review research methods gather data/analysis conclusions Evaluation describe program evaluation criteria program scoping evaluation methods gather data/analysis conclusions Process -- Steps

8. Types of Evaluationby Program Stage • formative (conceptualization/design)] • process (implementation) • summative (outcomes, impacts, efficiency)

9. Types - By Approach • Standards • norm-based • criterion-referenced • Goals and objectives • Impacts or effects

10. Evaluation Criteria • Effort - qnty and qlty of inputs • Performance - qnty and qlty of outputs • Adequacy - meet needs? • Efficiency - benefits/costs • Equity - distributional issues, fairness

11. Process Evaluation • Identifies how and why program works • attributes • recipients • conditions • effects • single or multiple • intended or side effects • timing & duration, long/short term • cognitive, affective or behavioral

12. Research ProcessDefine Problem, Research Objectives • HOW? • Overall Method • Survey • Experiment • Case Study • Secondary Data • What? • Concepts • Variables • Measures • Who? • Population • Sampling Data Gathering Analysis Application

13. Proposal Format 1. Problem Statement - define program to be evaluated/problem to be studied, users & uses of results. Justify importance of the problem/study. 2. Objectives : Concise listing . In evaluation studies, the objectives usually focus on the key elements of program to be evaluated & the evaluation criteria. These are the study objectives NOT the program objectives. 3. Background/Literature Review - place for more extensive history/structure of program. Focus on aspects most relevant to proposed evaluation. Discuss previous studies or the relevant methods. 4. Methods - details on procedures for achieving objectives - data gathering and analysis, population, sampling, measures, etc. Who will do what to whom, when, where, how and why? 5. Attachments - budget, timeline, measurement instruments, etc. NOTE: Most “programs” must be narrowed to specific components to be evaluated. Think of a “Program of studies” rather than a single evaluation study. The proposal should define this specific study & how it fits into a broader program of studies.

14. Purposes of Proposal • Communicate with Client • Demonstrate your grasp of problem • Plan the study in advance, so others can evaluate the study approach • will it work? • have you overlooked something? • will results be useful to client? • Can we afford it?

15. Sample Objectives 1. Estimate benefits and costs of program 2. Estimate economic impacts of program on local community (social, environmental, fiscal). 3. Determine effects of program on target population. 4. Describe users and non-users of program 5. Assess community recreation needs, preferences 6. Determine market/financial feasibility of program 7. Evaluate adequacy or performance of program

16. Methods Choices • Overall Approach/Design • Qualitative or Quantitative • Primary or secondary data • Survey, experiment, case study, etc. • Who to study - population, sample • individuals, market segments, populations • What to study - concepts, measures • behavior, knowledge, attitudes • Cost vs Benefit of Study

17. Definition & Measurement “measurement is the beginning of science, … until you can measure something, your knowledge is meager and unsatisfactory” Lord Kelvin Nominal/Conceptual Definition - define concept in terms of other concepts, links concepts without tying them to real world Operational definition - equates definition with measurement, specify procedures/operations to generate the concept.

18. Levels of Measurement

19. Validity vs Reliability

20. Questionnaire Design 1. Preliminary Info Information needed Who are subjects Method of communication 2. Question Content 3. Question Wording 4. Response Format 5. Question Sequencing/Layout

21. What Info? Demographic, Socioeconomic, Physical Cognitive - Knowledge & beliefs Affective - attitudes, feelings, preferences Behavioral - actions

22. Sampling • Always define study population first • Use element/unit/extent/time for complete definition • element - who is interviewed • sampling unit - basic unit containing elements • extent - limit population (often spatially) • time - fix population in time

23. Types of Sampling Approaches • Probability vs non-Probability • Judgment, Simple Random, Systematic • Stratify or Cluster (Area Sample) • Time Sampling

24. Sample size • Based on four factors • Cost/budget • Accuracy desired • variance in popln on variable of interest • subgroup analysis planned • Formula: n= Z2 2 / e 2 • n= sample size • Z indicates confidence level (95% = 1.96) •  = standard deviation of variable in population • e = sampling error

25. Sampling errors for binomial(95% confidence interval)percent distribution in population

26. Computing 95% confidence interval • N= 100 , sample mean = 46%, use p= 50/50, • sampling error from table = 10% • 95% CI is 46% + or - 10% = (36, 56) • N=1,000 sample mean =22% • sampling error from table = 2.5% • 95% CI is 22% + or - 2.5% = (19.5, 24.5)

27. Research Designs/Data Collection Approaches

28. Major Design Types • Surveys • Experiments • Observation • Secondary Data • Qualitative Approaches • Focus Group • Case Study

29. General Guidelines on when to use different approaches 1. Describing a population - surveys 2. Describing users/visitors - on-site survey 3. Describing non-users, potential users or general population - household survey 4. Describing observable characteristics of visitors - on-site observation 5. Measuring impacts, cause-effect relationships - experiments

30. Guidelines (cont) 6. Anytime suitable secondary data exists - secondary data 7. Short, simple household studies - phone 8. Captive audience or very interested population - self-administered survey 9. Testing new ideas - experimentation or focus groups 10. In-depth study - in-depth personal interviews, focus groups, case studies

31. Primary or Secondary Data • Secondary data are data that were collected for some purpose other than your study,e.g. government records, internal documents, previous surveys • Choice between Primary /Secondary Data • Costs (time, money, personnel) • Relevance, accuracy, adequacy of data

32. Qualitative vs Quantitative Quantitative Gen’l Laws Test Hypotheses Predict behavior Outsider-Objective Structured formal measures probability samples statistical analysis Qualitative Unique/Individual case Understanding Meanings/Intentions Insider-Subjective Unstructured open ended measures judgement samples interpretation of data Purpose Perspective Procedures

33. Qualitative vs Quantitative Approaches Qualitative Focus Group In-Depth Interview Case Study Participant observation Secondary data analysis Quantitative Surveys Experiments Structured observation Secondary data analysis

34. Survey vs Experiment Survey - measure things as they are, snapshot of population at one point in time, generally refers to questionnaires (telephone, self-administered, personal interview) Experiment - manipulate at least one variable (treatment) to evaluate response, to study cause-effect relationships (field and lab experiments)

35. STEPS IN A SURVEY • 1. Define problem and study objectives • 2. Identify information needs & study population(s) • 3. Determine basic design/approach • - cross sectional vs longitudinal • - on-site vs household vs other • - self-admin. vs personal interview vs phone • - structured or unstructured questions • 4. Questionnaire design • 5. Choose sample (frame, size, sampling design) • 6. Estimate time, costs, manpower needs, etc.

36. Survey Implementation • 7. Proposal & “Human subjects” review • 8. Line up necessary resources • 9. Pre-test instruments and field procedures • 10. Data gathering and follow-up procedures • 11. Coding, cleaning and data processing • 12. Analysis: preliminary, then final. • 13. Communication and presentation of results.

37. Characteristics of a true Experiment 1. Sample equivalent experimental and control groups 2. Isolate and control the treatment 3. Measure the effect

38. R MB1 X MA1 Experimental group R MB2 MA2 Control group Pre-test/Post-test with Control R denotes random assignment to groups X denotes the treatment Measure of effect =  Expmt gp -  Control gp = (MA1-MB1) - (MA2-MB2) = with vs without

39. Threats to Internal validity • * Pre-measurement (Testing) : effect of pre-measurement on dependent variable (post-test) • * Selection: nonequivalent experimental & control groups, (statistical regression a special case) • * History: impact of any other events between pre- and post measures on dependent variable • * Interaction: alteration of the “effect” due to interaction between treatment & pre-test. • Maturation:aging of subjects or measurement procedures • Instrumentation:changes in instruments between pre and post. • Mortality: loss of some subjects

40. Economic Evaluation Tools • Benefit-Cost Analysis • Cost Effectiveness Analysis • Financial Analysis/Feasibility • Fiscal Impact Analysis • Economic Impact Analysis • Social/Environmental Impact Analysis

41. Ethical Issues • Human Subjects • Honest and Open Reporting • Client confidentiality • No selling

42. Human Subjects • Voluntary Participation • Informed Consent • Risk-benefit ratio • Anonymity vs Confidentiality

43. Research Writing • Like any writing, • Know audience • Know Story/Message/Subject • Follow Formats for Outlet • Research Style • Objective, Factual • Impersonal • Dense, concise, logical

44. Sections • Abstract – Executive Summary • Introd/Problem statement • Objectives • Lit Review/Background • Methods • Results • Discussion, Implications • References

45. Three Audiences/styles • Researchers – research journal style • Technical, methods, statistical tests • Managers – business style • Results and implications • Public – newspaper style • Interesting, no jargon, highlights

46. Written/Research Problem Objectives Methods Results Discussion Oral/Business Objectives Key Results & Recommendations Justify from study Brief methods Discussion Research vs Business Reports

47. Reminders • Final Exam is Friday Dec 15, 7:45-9:45 am, this room • Final Papers due by Wednesday Dec 13 • See YaYen Sun to finish lab work by end of week.