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  2. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    Confounding variables may also be categorised according to their source. The choice of measurement instrument (operational confound), situational characteristics (procedural confound), or inter-individual differences (person confound). An operational confounding can occur in both experimental and non-experimental research designs. This type of ...

  3. Endogeneity (econometrics) - Wikipedia

    en.wikipedia.org/wiki/Endogeneity_(econometrics)

    The endogeneity problem is particularly relevant in the context of time series analysis of causal processes. It is common for some factors within a causal system to be dependent for their value in period t on the values of other factors in the causal system in period t − 1.

  4. 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 ...

  5. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables ⁡ (+) = ⁡ + ⁡ + ⁡ (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...

  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. Generalized estimating equation - Wikipedia

    en.wikipedia.org/.../Generalized_estimating_equation

    Examples of variance structure specifications include independence, exchangeable, autoregressive, stationary m-dependent, and unstructured. The most popular form of inference on GEE regression parameters is the Wald test using naive or robust standard errors, though the Score test is also valid and preferable when it is difficult to obtain ...

  8. Instrumental variables estimation - Wikipedia

    en.wikipedia.org/wiki/Instrumental_variables...

    This equation is similar to the equation involving ⁡ (,) in the introduction (this is the matrix version of that equation). When X and e are uncorrelated , under certain regularity conditions the second term has an expected value conditional on X of zero and converges to zero in the limit, so the estimator is unbiased and consistent.

  9. Propensity score matching - Wikipedia

    en.wikipedia.org/wiki/Propensity_score_matching

    SPSS: A dialog box for Propensity Score Matching is available from the IBM SPSS Statistics menu (Data/Propensity Score Matching), and allows the user to set the match tolerance, randomize case order when drawing samples, prioritize exact matches, sample with or without replacement, set a random seed, and maximize performance by increasing ...