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  2. Risk difference - Wikipedia

    en.wikipedia.org/wiki/Risk_difference

    Download as PDF; Printable version; In other projects ... Risk difference can be estimated from a 2x2 contingency table: Group ... Formula Value Absolute risk ...

  3. Barnard's test - Wikipedia

    en.wikipedia.org/wiki/Barnard's_test

    Under specious pressure from Fisher, Barnard retracted his test in a published paper, [8] however many researchers prefer Barnard’s exact test over Fisher's exact test for analyzing 2 × 2 contingency tables, [9] since its statistics are more powerful for the vast majority of experimental designs, whereas Fisher’s exact test statistics are conservative, meaning the significance shown by ...

  4. Boschloo's test - Wikipedia

    en.wikipedia.org/wiki/Boschloo's_test

    Boschloo's test is a statistical hypothesis test for analysing 2x2 contingency tables. It examines the association of two Bernoulli distributed random variables and is a uniformly more powerful alternative to Fisher's exact test .

  5. Contingency table - Wikipedia

    en.wikipedia.org/wiki/Contingency_table

    C suffers from the disadvantage that it does not reach a maximum of 1.0, notably the highest it can reach in a 2 × 2 table is 0.707 . It can reach values closer to 1.0 in contingency tables with more categories; for example, it can reach a maximum of 0.870 in a 4 × 4 table.

  6. McNemar's test - Wikipedia

    en.wikipedia.org/wiki/McNemar's_test

    The McNemar's test is a special case of the Cochran–Mantel–Haenszel test; it is equivalent to a CMH test with one stratum for each of the N pairs and, in each stratum, a 2x2 table showing the paired binary responses. [18] Multinomial confidence intervals are used for matched pairs binary data.

  7. Yates's correction for continuity - Wikipedia

    en.wikipedia.org/wiki/Yates's_correction_for...

    This reduces the chi-squared value obtained and thus increases its p-value. The effect of Yates's correction is to prevent overestimation of statistical significance for small data. This formula is chiefly used when at least one cell of the table has an expected count smaller than 5. = =

  8. Prevalence - Wikipedia

    en.wikipedia.org/wiki/Prevalence

    In science, prevalence describes a proportion (typically expressed as a percentage). For example, the prevalence of obesity among American adults in 2001 was estimated by the U. S. Centers for Disease Control (CDC) at approximately 20.9%. [5] Prevalence is a term that means being widespread and it is distinct from incidence.

  9. Attack rate - Wikipedia

    en.wikipedia.org/wiki/Attack_rate

    In epidemiology, the attack rate is the proportion of an at-risk population that contracts the disease during a specified time interval. [1] It is used in hypothetical predictions and during actual outbreaks of disease.