Scientists have developed a method called the possible worlds framework to determine if a proposed causal relationship is supported by observed data, even when some information is missing. They created diagrams to show all possible scenarios and used them to prove when causal relationships are not compatible. This framework can also be used to solve the problem of possibilistic causal compatibility. By considering graphical symmetries and consistency constraints, they were able to create a series of tests that can determine if a causal hypothesis is valid.