Categories → Causal Inference , Method
The matching method is a technique used in causal inference to estimate the causal effect of an intervention or treatment on an outcome of interest.
In this method, a treatment group and a control group are compared, and the individuals in these groups are matched based on their observed characteristics. The goal of matching is to create groups that are similar in terms of their observed characteristics, so that any difference in outcomes between the treatment and control groups can be attributed to the treatment itself.
There are different types of matching methods, but one common approach is propensity score matching. In this method, a propensity score is calculated for each individual in the sample, which represents the probability of being assigned to the treatment group based on their observed characteristics. The treatment group and control group are then matched based on their propensity scores, so that individuals with similar scores are compared.
Once the groups are matched, the average difference in outcomes between the treatment and control groups is calculated, and this difference can be interpreted as the causal effect of the treatment. The matching method can be used in observational studies where individuals are not randomly assigned to treatment or control groups, but it relies on the assumption that all relevant variables that could affect the outcome have been measured and included in the matching process. If there are unobserved variables that are related to both the treatment assignment and the outcome, the matching method may not produce accurate estimates of the causal effect.