Stratified sampling
Stratified sampling is a method of sampling from a population. In statistical surveys, when subpopulations within an overall population vary, it is advantageous to sample each subpopulation (stratum) independently. Stratification is the process of dividing members of the population into homogeneous subgroups before sampling. The strata should be mutually exclusive: every element in the population must be assigned to only one stratum. The strata should also be collectively exhaustive: no population element can be excluded.
Overview[edit | edit source]
Stratified sampling strategies can be divided into two groups: proportionate and disproportionate. Whether to use proportionate or disproportionate stratification depends on the researcher's knowledge about the population of interest and the goals of the research.
Proportionate stratification[edit | edit source]
In proportionate stratification, the size of the sample from each stratum is proportional to the size of the stratum. For example, if the population consists of X total individuals, m of which are male and f female (and where m + f = X), then the relative size of the two samples (x1 = m/X males, x2 = f/X females) should reflect this ratio.
Disproportionate stratification[edit | edit source]
In disproportionate stratification, the size of the sample from each stratum is not proportional to the size of the stratum. This type of stratification is used when the researcher wants to highlight a subgroup within the population. This may be the best strategy when a subgroup is small and the research requires a larger sample from that group than would be needed if the sample were drawn proportionately.
Advantages and disadvantages[edit | edit source]
Stratified sampling has several advantages over simple random sampling. For example, using stratified sampling, it may be possible to reduce the sample size required to achieve a given precision. Or it may be possible to increase the precision with the same sample size.
However, stratified sampling also has disadvantages. It can be complex to decide how to stratify a population and what stratification to use. It can also be difficult to manage the process of drawing a stratified sample.
See also[edit | edit source]
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