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  2. Study heterogeneity - Wikipedia

    en.wikipedia.org/wiki/Study_heterogeneity

    Statistical testing for a non-zero heterogeneity variance is often done based on Cochran's Q [13] or related test procedures. This common procedure however is questionable for several reasons, namely, the low power of such tests [14] especially in the very common case of only few estimates being combined in the analysis, [15] [7] as well as the specification of homogeneity as the null ...

  3. Homogeneity and heterogeneity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Homogeneity_and...

    They relate to the validity of the often convenient assumption that the statistical properties of any one part of an overall dataset are the same as any other part. In meta-analysis, which combines the data from several studies, homogeneity measures the differences or similarities between the several studies (see also Study heterogeneity).

  4. Homogeneity and heterogeneity - Wikipedia

    en.wikipedia.org/wiki/Homogeneity_and_heterogeneity

    Homogeneity and heterogeneity; only ' b ' is homogeneous Homogeneity and heterogeneity are concepts relating to the uniformity of a substance, process or image.A homogeneous feature is uniform in composition or character (i.e., color, shape, size, weight, height, distribution, texture, language, income, disease, temperature, radioactivity, architectural design, etc.); one that is heterogeneous ...

  5. Homoscedasticity and heteroscedasticity - Wikipedia

    en.wikipedia.org/wiki/Homoscedasticity_and...

    One version of this is to use covariance matrices as the multivariate measure of dispersion. Several authors have considered tests in this context, for both regression and grouped-data situations. [ 28 ] [ 29 ] Bartlett's test for heteroscedasticity between grouped data, used most commonly in the univariate case, has also been extended for the ...

  6. Pearson's chi-squared test - Wikipedia

    en.wikipedia.org/wiki/Pearson's_chi-squared_test

    Pearson's chi-squared test is used to assess three types of comparison: goodness of fit, homogeneity, and independence. A test of goodness of fit establishes whether an observed frequency distribution differs from a theoretical distribution.

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  8. Forest plot - Wikipedia

    en.wikipedia.org/wiki/Forest_plot

    Results that fail to overlap well are termed heterogeneous and is referred to as the heterogeneity of the data—such data is less conclusive. If the results are similar between various studies, the data is said to be homogeneous, and the tendency is for these data to be more conclusive. The heterogeneity is indicated by the I 2.

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