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  2. Stratified randomization - Wikipedia

    en.wikipedia.org/wiki/Stratified_randomization

    Stratified randomization may also refer to the random assignment of treatments to subjects, in addition to referring to random sampling of subjects from a population, as described above. Simple random sampling after stratification step. In this context, stratified randomization uses one or multiple prognostic factors to make subgroups, on ...

  3. 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.

  4. 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 ...

  5. Minimisation (clinical trials) - Wikipedia

    en.wikipedia.org/wiki/Minimisation_(clinical_trials)

    Minimisation is a method of adaptive stratified sampling that is used in clinical trials, as described by Pocock and Simon. [1] [2] The aim of minimisation is to minimise the imbalance between the number of patients in each treatment group over a number of factors. Normally patients would be allocated to a treatment group randomly and while ...

  6. Oversampling and undersampling in data analysis - Wikipedia

    en.wikipedia.org/wiki/Oversampling_and_under...

    Within statistics, oversampling and undersampling in data analysis are techniques used to adjust the class distribution of a data set (i.e. the ratio between the different classes/categories represented). These terms are used both in statistical sampling, survey design methodology and in machine learning . Oversampling and undersampling are ...

  7. Permutation test - Wikipedia

    en.wikipedia.org/wiki/Permutation_test

    A permutation test (also called re-randomization test or shuffle test) is an exact statistical hypothesis test making use of the proof by contradiction . A permutation test involves two or more samples. The null hypothesis is that all samples come from the same distribution . Under the null hypothesis, the distribution of the test statistic is ...

  8. Randomization - Wikipedia

    en.wikipedia.org/wiki/Randomization

    Randomization is a statistical process in which a random mechanism is employed to select a sample from a population or assign subjects to different groups. [ 1 ] [ 2 ] [ 3 ] The process is crucial in ensuring the random allocation of experimental units or treatment protocols, thereby minimizing selection bias and enhancing the statistical ...

  9. Resampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Resampling_(statistics)

    The best example of the plug-in principle, the bootstrapping method. Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio ...