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A. Simplifying the Evaluation Design
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- Truncated longitudinal design (Design 3): study starts at midterm
- Pretest-posttest project group with posttest analysis of project and comparison groups (Design 4.1b): eliminates baseline comparison group
- Posttest comparison of project and control group (Design 5): eliminates baseline
- Evaluation based on posttest data from project group (Design 7): eliminates comparison group and baseline project group
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- Prioritize and focus on critical issues
- Reduce the number of site visits or the time period over which observations are made
- Reduce the amount and cost of data collection
- Reduce the number of persons or groups studied
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B. Clarifying Client Information Needs
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Prioritize data needs with the client to try to eliminate the collection of nonessential data.
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C. Using Existing Data
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- Census or surveys covering project areas
- Data from project records
- Records from schools, health centers, and other public-service agencies
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- Newspapers and other mass media
- Records from community organizations
- Dissertations and other university studies [for both QUAL and QUANT]
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D. Reducing Sample Size
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- Lower the level of required precision (lower precision = small sample)
- Reduce types of disaggregation required (less disaggregation = smaller sample
- Use stratified sample designs (to reduce total interviews)
- Use cluster sampling (lower travel costs)
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- Consider critical or quota sampling rather than comprehensive or representative sampling
- Reduce the number of persons or groups studied.
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E. Reducing Costs of Data Collection, Input, and Analysis
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- Self-administered questionnaires (with literate populations)
- Direct observation-instead of surveys (sometimes saves money but not always)
- Automatic counters and other nonobtrusive methods
- Direct inputting of survey data through handheld devices
- Optical scanning of survey forms and electronic surveys
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- Decrease the number or period of observations
- Prioritize informants
- Employ and train university students, student nurses, and community residents to collect data (for both QUAL and QUANT)
- Data input through handheld devices
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Mixed Method Designs
- Triangulation to compensate for reduced sample size
- Focus groups and community forums instead of household surveys
- PRA and other participatory methods
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