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Internal Staff
Evaluation OptionConducting an evaluation using staff from the implementing agency rather than hiring external consultants.
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Peer review for meta-evaluation
Evaluation OptionReviewing the evaluation by using peers from within the organisation or outside of the organisation
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Community
Evaluation OptionThe community, particularly intended beneficiaries of an intervention, can undertake an evaluation or contribute to a combined team.
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Public Consultations
Evaluation Option
Public consultations are usually conducted through public meetings to provide an opportunity for the community to raise issues of concern and respond to options.
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Simple Random Sampling
Evaluation Option
A simple random sample (SRS) is the most basic probabilistic option used for creating a sample from a population. Each SRS is made of individuals drawn from a larger population (represented by the variable N), completely at random. As a result, said individuals have an equal chance of being selected throughout the sampling process. The benefit of SRS is that as a result, the investigator is guaranteed to choose a sample which is representative of the population, which ensures statistically valid conclusions.
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Stratified Random Sampling
Evaluation Option
Stratified random sampling is a probabilistic sampling option. The first step in stratified random sampling is to split the population into strata, i.e. sections or segments. The strata are chosen to divide a population into important categories relevant to the research interest.
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Sequential Sampling
Evaluation Option
Sequential sampling is a non-probabilistic sampling technique, initially developed as a tool for product quality control. The sample size, n, is not fixed in advanced, nor is the timeframe of data collection. The process begins, first, with the sampling of a single observation or a group of observations. These are then tested to see whether or not the null hypothesis can be rejected. If the null is not rejected, then another observation or group of observations is sampled and the test is run again. In this way the test continues until the researcher is confident in his or her results.
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Outlier Sampling
Evaluation Option
This type of sampling focuses on the extremes – the end-points of the normal distribution bell-curve. Outlier sampling studies cases that are unusual or special in some way, such as outstanding successes or notable failures. Many programs can have ‘best’ sites of implementation. Studying why these sites are different can provide insight into both what is unique to that case and also what is typical and shared with other sites.
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Maximum Variation Sampling
Evaluation Option
A maximum variation sample contains cases that are purposefully as different from each other as possible. This type of sampling is useful for examining range in large national or global programs.
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Homogenous Sampling
Evaluation Option
Homogenous sampling involves selecting similar cases to further investigate a particular phenomenon or subgroup of interest. The logic of homogenous sampling is in contrast to the logic of maximum variation sampling.
