Eitodennäköisyysnäytteistys

Eitodennäköisyysnäytteistys, or inverse probability weighting (IPW), is a statistical technique used to estimate the average causal effect of a treatment or intervention in observational studies. It addresses confounding by selecting individuals for the analysis in a way that mimics a randomized controlled trial. The core idea is to assign weights to each participant based on their probability of receiving the treatment they actually received, given their observed characteristics.

Specifically, IPW estimates the probability of receiving the treatment (the propensity score) for each individual using a logistic regression model. Then, weights are calculated as the inverse of these estimated propensity scores. Participants who received the treatment but had a low probability of receiving it are given higher weights, and vice versa. Similarly, participants who did not receive the treatment but had a high probability of receiving it are given higher weights.

By applying these inverse probability weights, the analysis creates a pseudo-population where the distribution of confounding variables is balanced between the treated and control groups, as if randomization had occurred. This allows for a more unbiased estimation of the treatment effect, as the influence of measured confounders is accounted for. IPW is particularly useful when the treatment assignment mechanism is complex or when there are many confounding variables. It is a non-parametric method that does not require strong assumptions about the functional form of the treatment effect.