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Selecting a Sampling Design

If you are... consider using ...
in an emergency situation. . . judgmental sampling
a screening situation. . . judgmental sampling for small-scale problems with small budgets and limited schedule
systematic/grid sampling
simple random sampling
searching for rare characteristics (including hot spots). . . adaptive cluster sampling
systematic/grid sampling
identifying areas of contamination. . . adaptive cluster sampling
stratified sampling A, B
systematic/grid sampling or simple random sampling when no professional knowledge or prior information exists A, B
estimating the prevalence of a rare trait. . . simple random sampling A, B
stratified sampling A, B
estimating/testing an area/process mean or proportion. . .

simple random sampling or systematic/grid sampling when no professional knowledge or prior information exists A, B
ranked set sampling (for means only)
stratified sampling A, B
comparing parameters of two areas/processes. . .

simple random sampling or systematic/grid sampling A, B
ranked set sampling
stratified sampling A, B
AConsider using compositing in conjunction with this design if analytical costs are much higher than sampling costs and samples can be homogenized.

BUse compositing only when interested in means.


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Simple Random Sampling - A random number generator (or equivalent process) is used to select all sampling locations.

Can be used for any objective - estimating/testing means, proportions, etc., comparing means, proportions, etc., of two or more areas/processes, delineating boundaries, etc., but is one of the least efficient (though easiest) designs since it doesn't use any prior information or professional knowledge. It is primarily used in conjunction with other sampling designs, as the last stage of sampling in multi-stage projects (i.e., a sample of units is selected at the first stage and then subunits are selected from each unit), and for assigning units in experimental (e.g., intra-laboratory studies). Use when:

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Stratified Random Sampling - Prior information about the area/process is used to create groups that are sampled independently using a random process. These groups can be based on spatial or temporal proximity, or on preexisting information or professional judgment.

Can be used for any objective - estimating means, proportions, etc., delineating boundaries, etc. Use when:

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Systematic and Grid Sampling - A random number generator (or equivalent process) is used to select an initial sampling point (either spatial or temporal) and the remaining points are based on a specific pattern (weekly, rectangular, square, triangular, etc.)

Can be used for any objective - estimating means/testing, proportions, etc.; delineating boundaries; finding hot spots; and estimating spatial or temporal patterns or correlations. It is primarily used for pilot studies, scoping studies, and exploratory studies. Use when:

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Ranked Set Sampling - Screening (inexpensive) measurements are used on an initial random sample. The results are ranked into groups based on relative magnitude (high, medium, low), then one location from each group is sampled.

Used primarily for estimating/testing means or comparing two means. Use when:

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Adaptive Cluster Sampling - Take random samples. If result shows characteristic of interest (i.e., "hit"), take additional samples adjacent to the original.

Can be used for estimating or searching for rare characteristics, delineating hot spots, estimating means, and determining extent of contamination. Use when:

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Composite Sampling - First, another sampling design is used to select sample locations. Then composite samples are created by physically combining and homogenizing these samples based on a fixed compositing scheme.

Can be used to estimate/test means, compare two or more means, estimate the prevalence of a trait (or the proportion of an area/process that has a particular trait), or to identify samples with a specific trait. Use

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