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  2. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    Depending on the type of study design in place, there are various ways to modify that design to actively exclude or control confounding variables: [26] Case-control studies assign confounders to both groups, cases and controls, equally. For example, if somebody wanted to study the cause of myocardial infarct and thinks that the age is a ...

  3. Spurious relationship - Wikipedia

    en.wikipedia.org/wiki/Spurious_relationship

    Graphical model: Whereas a mediator is a factor in the causal chain (top), a confounder is a spurious factor incorrectly implying causation (bottom). In statistics, a spurious relationship or spurious correlation [1] [2] is a mathematical relationship in which two or more events or variables are associated but not causally related, due to either coincidence or the presence of a certain third ...

  4. Correlation does not imply causation - Wikipedia

    en.wikipedia.org/wiki/Correlation_does_not_imply...

    All of those examples deal with a lurking variable, which is simply a hidden third variable that affects both of the variables observed to be correlated. That third variable is also known as a confounding variable, with the slight difference that confounding variables need not be hidden and may thus be corrected for in an analysis. Note that ...

  5. Propensity score matching - Wikipedia

    en.wikipedia.org/wiki/Propensity_score_matching

    Propensity scores are used to reduce confounding by equating groups based on these covariates. Suppose that we have a binary treatment indicator Z, a response variable r, and background observed covariates X. The propensity score is defined as the conditional probability of treatment given background variables:

  6. Simpson's paradox - Wikipedia

    en.wikipedia.org/wiki/Simpson's_paradox

    The phenomenon may disappear or even reverse if the data is stratified differently or if different confounding variables are considered. Simpson's example actually highlighted a phenomenon called noncollapsibility, [32] which occurs when subgroups with high proportions do not make simple averages when combined. This suggests that the paradox ...

  7. Stratification (clinical trials) - Wikipedia

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

    Stratification can be used to control for confounding variables (variables other than those the researcher is studying), thereby making it easier for the research to detect and interpret relationships between variables. [1] For example, if doing a study of fitness where age or gender was expected to influence the outcomes, participants could be ...

  8. FDA wants new testing to detect asbestos in products with talc

    www.aol.com/fda-wants-testing-detect-asbestos...

    Manufacturers of baby powder and cosmetic products made with talc will have to test them for asbestos under a proposal announced by the U.S. Food and Drug Administration.

  9. Control variable - Wikipedia

    en.wikipedia.org/wiki/Control_variable

    A variable in an experiment which is held constant in order to assess the relationship between multiple variables [a], is a control variable. [2] [3] A control variable is an element that is not changed throughout an experiment because its unchanging state allows better understanding of the relationship between the other variables being tested.