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  2. Stratified sampling - Wikipedia

    en.wikipedia.org/wiki/Stratified_sampling

    Proportionate allocation uses a sampling fraction in each of the strata that are proportional to that of the total population. For instance, if the population consists of n total individuals, m of which are male and f female (and where m + f = n), then the relative size of the two samples (x 1 = m/n males, x 2 = f/n females) should reflect this proportion.

  3. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    Sample size determination or estimation is the act of choosing the number of observations or replicates to include in a statistical sample. The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined ...

  4. Stratified randomization - Wikipedia

    en.wikipedia.org/wiki/Stratified_randomization

    Graphic breakdown of stratified random sampling. 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 ...

  5. Stratification (clinical trials) - Wikipedia

    en.wikipedia.org/wiki/Stratification_(clinical...

    Stratification (clinical trials) Stratification of clinical trials is the partitioning of subjects and results by a factor other than the treatment given. Stratification can be used to ensure equal allocation of subgroups of participants to each experimental condition. This may be done by gender, age, or other demographic factors.

  6. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    In survey methodology, the design effect (generally denoted as , , or ) is a measure of the expected impact of a sampling design on the variance of an estimator for some parameter of a population. It is calculated as the ratio of the variance of an estimator based on a sample from an (often) complex sampling design, to the variance of an ...

  7. Horvitz–Thompson estimator - Wikipedia

    en.wikipedia.org/wiki/Horvitz–Thompson_estimator

    In statistics, the Horvitz–Thompson estimator, named after Daniel G. Horvitz and Donovan J. Thompson, [1] is a method for estimating the total [2] and mean of a pseudo-population in a stratified sample by applying inverse probability weighting to account for the difference in the sampling distribution between the collected data and the a target population.

  8. Cochran–Mantel–Haenszel statistics - Wikipedia

    en.wikipedia.org/wiki/Cochran–Mantel–Haenszel...

    Cochran–Mantel–Haenszel statistics. In statistics, the Cochran–Mantel–Haenszel test (CMH) is a test used in the analysis of stratified or matched categorical data. It allows an investigator to test the association between a binary predictor or treatment and a binary outcome such as case or control status while taking into account the ...

  9. Probability-proportional-to-size sampling - Wikipedia

    en.wikipedia.org/wiki/Probability-proportional...

    Probability-proportional-to-size sampling. In survey methodology, probability-proportional-to-size (pps) sampling is a sampling process where each element of the population (of size N) has some (independent) chance to be selected to the sample when performing one draw. This is proportional to some known quantity so that . [1]: 97 [2]