Mixed, Stratified, and Nested Sampling Methods

Mixed, stratified, and nested sampling methods, as the name implies, combine the use of two or more of the basic sampling methods. Several methods are mutually exclusive and difficult to combine, such as homogenous sampling and maximum variation sampling. Other sampling methods pair well together. Some examples include:

• Mixed matched and continuum sampling: Selecting two samples that differ significantly along a dimension of interest, but within each sample, a full continuum of other dimensions is represented
• Mixed homogenous and intensity sampling: Limiting the sample to a very narrow range of variation, and within that range, selecting only cases that demonstrate a phenomenon of interest with sufficient intensity
• Mixed criterion-based and purposeful random sampling: Beginning with the identification of all cases that meet the defined criterion of interest, then selecting cases from this group using a random selection method; this limits the bias introduced to the sample to only the intended bias

• PreviousGroup Characteristics Sampling
• NextOther Purposeful Sampling Methods