Since version 10
The Effects Analysis tool calculates the Causal Effect on one outcome Y, based on the values of one or more treatments X.
This is equivalent to setting an intervention on each treatment value, but this tool provides a way to automatically record the outcome Y for each treatment intervention, and also allows for comparison of different treatments in a chart.
For example, in the image below, we are calculating the causal effect of Education on Salary and also the causal effect of Experience on Salary.
Values on the X-axis are normalized, so when multiple treatments are present, they can be compared.
When a treatment X is discrete, the causal effect on the outcome Y, is calculated for each state in X, given the current evidence.
When a treatment X is continuous, the treatment X is discretized given the current evidence, then the causal effect on the outcome Y is calculated for each discretized interval of X.
When the outcome Y is discrete, and the outcome state y is specified, P(Y=y | Do (X=x)) is calculated for each treatment value.
When the outcome Y is discretized, and the outcome state is not specified, , the mean and the variance of Y is calculated for each treatment value.
If the outcome state is specified, the probability of the outcome is calculated instead.
When the outcome Y is continuous, the mean and the variance of Y is calculated for each treatment value.