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  2. Inverse probability weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse_probability_weighting

    An alternative estimator is the augmented inverse probability weighted estimator (AIPWE) combines both the properties of the regression based estimator and the inverse probability weighted estimator. It is therefore a 'doubly robust' method in that it only requires either the propensity or outcome model to be correctly specified but not both.

  3. Horvitz–Thompson estimator - Wikipedia

    en.wikipedia.org/wiki/Horvitz–Thompson_estimator

    In statistics, the Horvitz–Thompson estimator, named after Daniel G. Horvitz and Donovan J. Thompson, [1] is a method for estimating the total [2] and mean of a pseudo-population in a stratified sample by applying inverse probability weighting to account for the difference in the sampling distribution between the collected data and the target population.

  4. 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:

  5. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    inverse-variance weighting, also known as analytic weights, [24] is when each element is assigned a weight that is the inverse of its (known) variance. [ 25 ] [ 9 ] : 187 When all elements have the same expectancy, using such weights for calculating weighted averages has the least variance among all weighted averages.

  6. Inverse-variance weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse-variance_weighting

    For normally distributed random variables inverse-variance weighted averages can also be derived as the maximum likelihood estimate for the true value. Furthermore, from a Bayesian perspective the posterior distribution for the true value given normally distributed observations and a flat prior is a normal distribution with the inverse-variance weighted average as a mean and variance ().

  7. Propensity score - Wikipedia

    en.wikipedia.org/?title=Propensity_score&redirect=no

    Download as PDF; Printable version; In other projects Appearance. move to sidebar hide. From Wikipedia, the free encyclopedia. Redirect page. Redirect to: Propensity ...

  8. Heckman correction - Wikipedia

    en.wikipedia.org/wiki/Heckman_correction

    The Heckman correction is a statistical technique to correct bias from non-randomly selected samples or otherwise incidentally truncated dependent variables, a pervasive issue in quantitative social sciences when using observational data. [1]

  9. Inverse probability - Wikipedia

    en.wikipedia.org/wiki/Inverse_probability

    The inverse probability problem (in the 18th and 19th centuries) was the problem of estimating a parameter from experimental data in the experimental sciences, especially astronomy and biology. A simple example would be the problem of estimating the position of a star in the sky (at a certain time on a certain date) for purposes of navigation ...