Survey Weighting and Regression
In the words of Andrew Gelman, “survey weighting is a mess.” F ull weighting (that is, creating weights based on cell counts in the population contingency table) on all covariat es is straightforward enough for estimating simple quantit ies like means. However, weights can be hard to calculate and eve n with known weights it gets tricky to estimate and calculate standard errors for more complicated quantities such as regression coefficients using weighting. Moreover, as more and more covariates are used to calculate weights, the w eights can become unstable and it may make more sense to use raking weights based on the covariates’ marginal dist ributions rather than the full contingency table. Finally, the population covariate contingency table may not be avail ble, so we may be forced to use raking weights based on the covariates’ marginal distributions.