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  • Official statistics

    Statistics published by government agencies or other public bodies such as international organizations are often useful in evaluations.
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  • Previous evaluations and research

    Using the findings from evaluation and research studies conducted on the same or closely related areas is an important first step for evaluation planning. 
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  • Content analysis

    Content analysis is a research method in the social sciences used to reduce large amounts of unstructured textual content into manageable data relevant to the (evaluation) research questions.
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  • Participant observation

    Participant observation is used to identify the attitudes and operation of a community by a researcher living within its environs.
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  • Transect

    Transect walks are a method for gathering spatial data on an area by observing people, surroundings and resources while walking around an area or community.
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  • Field trips

    Field trips are organised trips where participants visit physical sites.
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  • Biophysical measurement

    Biophysical measurement measures physical changes that take place over a period of time related to a specific indicator and using an accepted measurement procedure.
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  • Geographical

    Capturing geographic information about persons or objects of interest such as the locations of high prevalence of a disease or the location of service delivery points.
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  • Control group

    A control group is an untreated research sample against which all other groups or samples in the research is compared.
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  • Realist analysis of testable hypotheses

    Realist analysis of testable hypotheses tests the program theory by developing a nuanced understanding of ‘what works for whom in what circumstances and in what respects, and how?’.
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  • Check dose-response patterns

    Evaluators can examine the link between dose and response as part of determining whether the program caused the outcome.
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  • Check results match a statistical model

    Program staff may develop a statistical model as part of the project theory design. Statistical models can be useful tools to predict elements of the program:
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  • Check results match expert predictions

    Expert predictions can be a useful part of developing the program theory. Program staff can draw expert predictions from the literature or by engaging a group of experts.
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  • Check timing of outcomes

    The program theory may predict the timing of outcomes for the evaluator to check against these dates with the dates of actual changes and outcomes.
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  • Key informant

    Asking experts of programmes or in the community to predict what would have happened in the absence of the intervention.
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  • Searching for disconfirming evidence/following up exceptions

    Treating data that doesn’t fit the expected pattern not as outliers but as potential clues to other causal factors and then seeking to explain them.
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  • General Elimination Methodology

    General Elimination Methodology has two stages:
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  • Force field analysis

    A force field analysis is used to support the decision making process by providing a detailed overview of the variety of forces that may be acting on an organisational change issue. 
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  • Statistically controlling for extraneous variables

    Statistically controlling for extraneous variables is an option for removing the influence of a variable on the study of program results.
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  • Ruling out technical explanations

    Ruling out technical explanations involves identifying and investigating possible ways that the results might reflect technical limitations rather than actual causal relationships.
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  • Judgemental matching

    Judgemental matching involves creating a comparison group by finding a match for each person or site in the treatment group based on researcher judgements about what variables are important.
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  • Difference-in-difference

    Difference-in-difference involves comparing the before-and-after difference for the group receiving the intervention (where they have not been randomly assigned) to the before-after difference for those who did not.
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  • Sequential allocation

    Sequential allocation involves creating a treatment group and a comparison group by using a sequence to choose participants (e.g. every 3rd person on the list).
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  • Statistically created counterfactual

    A statistical model, such as regression analysis, is used to develop an estimate of what would have happened in the absence of an intervention.
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  • Numeric weighting

    Numeric weighting involves developing numeric scales in order to rate performance against each evaluation criterion and then adding them up for a total score.
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  • Multi-criteria analysis

    A multi-criteria analysis (MCA) is a form of appraisal that measures variables such as material costs, time savings and project sustainability as well as the social and environmental impacts in addition to monetary impacts.
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  • Qualitative weight and sum

    Using qualitative ratings (such as symbols) to identify performance in terms of essential, important and unimportant criteria. "In QWS:
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  • Textual narrative synthesis

    Dividing the studies into relatively homogenous groups, reporting study characteristics within each group, and articulating broader similarities and differences among the groups
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  • Meta-analysis

    Meta-analysis is a statistical method for combining numeric evidence from experimental (and sometimes quasi-experimental studies) to produce a weighted average effect size.  
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  • Rapid evidence assessment

    Rapid Evidence Assessment is a process that uses a combination of key informant interviews and targeted literature searches to produce a report in a few days or a few weeks.
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  • Modus operandi

    Interventions create distinctive/characteristic patterns of effects. Scriven describes the modus operandi as a set of footprints:
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  • Expert panel

    Expert panels are used when specialized input and opinion is required for an evaluation.
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