Sampling (statistics) | Sampling techniques

Stratified randomization

In statistics, stratified randomization is a method of sampling which first stratifies the whole study population into subgroups with same attributes or characteristics, known as strata, then followed by simple random sampling from the stratified groups, where each element within the same subgroup are selected unbiasedly during any stage of the sampling process, randomly and entirely by chance. Stratified randomization is considered a subdivision of stratified sampling, and should be adopted when shared attributes exist partially and vary widely between subgroups of the investigated population, so that they require special considerations or clear distinctions during sampling. This sampling method should be distinguished from cluster sampling, where a simple random sample of several entire clusters is selected to represent the whole population, or stratified systematic sampling, where a systematic sampling is carried out after the stratification process. Stratified random sampling is sometimes also known as "quota random sampling". (Wikipedia).

Stratified randomization
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Related pages

Weighting | Stratified sampling | P-value | Statistics | Simple random sample | Uniqueness quantification | Statistical population | Subgroup analysis | Sampling frame | Variable and attribute (research) | Observational study | Covariance | Margin of error | Quota sampling | Coverage probability | Confounding | Blocking (statistics) | Sample size determination | Sampling error | Minimisation (clinical trials) | Probability distribution | Standard deviation | Cluster sampling | Systematic sampling | Type I and type II errors | Sampling (statistics) | Clinical trial | Mutual exclusivity