Among probability sampling methods, what kinds of research conditions are more appropriate for each sampling method?

What will be an ideal response?

Commonly used probability sampling methods include simple random sampling, systematic sampling, cluster sampling, and stratified sampling. Simple random and systematic sampling methods are more likely to be used if the population is homogeneous, while cluster sampling is the preferred method if the population is scattered. Resource constraints in terms of time and money favor cluster over simple random or systematic sampling when face-to-face interviews are planned. The availability of a sampling frame also affects the choice of a particular method.

The feasibility of simple random sampling depends largely on whether or not there exist accurate and complete lists of the population elements from which the sample is to be drawn. It would be prohibitively expensive and time-consuming to compose such a sampling frame.

Systematic sampling is easier to draw than simple random sampling, so it is often used in lieu of simple random sampling, particularly if the sampling list is long or the desired sample size is large. Systematic sampling is commonly used when choosing a sample from city or telephone directories or other preexisting but unnumbered lists.

Cluster sampling is commonly used in survey practice, and clusters are usually natural groupings, such as organizations or associations, or geographic units. Deciding whether to study all the elements within the cluster or to randomly select the elements for study usually depends on the heterogeneity of the elements within the clusters. The more heterogeneous the elements, the greater the proportion of those should be studied. This method is more expensive in terms of sample frame preparation and data collection, but considerable amounts of money and time can be saved overall because cluster sampling does not require the complete lists of each and every population unit to be constructed. Travel-related time and costs for the purpose of conducting interviews are also greatly reduced.

Stratified sampling may be proportional or disproportional, depending on the probability of each sampling element to be selected. In proportional stratified sampling, all population strata are sampled proportional to their composition in the population. Disproportional sampling is used when one or more strata within the population are underrepresented and would not otherwise appear in sufficient numbers in simple random sampling. In general, disproportional sampling is used whenever a simple random sample would not produce enough cases of a certain type to support the intended analysis.