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Assemble mediate countersignature

all right so previously we talked about the baron and kenny approach uh there were two approaches as you can remember one was the subtraction approach or approach one and another was the multiplication approach or the approach two um and when we have done the labs we especially in the first part of the lab we have seen that when our outcome was continuous then the subtraction approach as well as the multiplication approach that means approach one and two they both gave you the same result right but when we are dealing with a non-collapsible measure such as earth's ratio or hazard ratio then we have seen in our lab scenario that when our outcome was binary then the approach 1 and approach 2 gave very different result for the indirect effect right so that gives us a hint that when we are working with the subtraction approach at least then the change in estimate approach does not really work that means that um this subtraction approach is not going to be useful anymore when we're working with the uh non-collapsible measures such as hazard ratio or odds ratio and product coefficient method still gave us the [Music] expected result that means the approach to still gave us the expected result but product coefficient methods can be hard to interpret and that means that we are only stuck with the continuous outcome type of model so if we are using um a linear model to deal with binary outcomes then it is not really clear what we are really trying to estimate here and even in a scenario where we have continuous outcomes um when confounding at exist then the situation can be quite complicated then the simplistic methods such as baron and kenny approach might not work anymore so what about confronting like if you have a confounder variable in the baron kenny approach example that we have seen in our lab um can it accommodate the confounding it is not really clear and to deal with this confounding type of scenarios we need to work with modern methods instead of this baron kenny approach to get a good understanding and understanding about the mediation all right so what is this modern approach we are talking about uh basically we are talking about the counter factual definition and in this counterfactual definition if you remember from our previous lab we are basically talking about comparison of the exposure group versus the control group that was the situation under which we were estimating that total effect right but when we are under this mediation then we have basically another form of exposure so in in this scenario um there are at least two variables that are impacting our outcome right and this mediator variable it can also take the value of 1 and it can take the value of 0. so if this was the scenario that our exposure was 1 and our mediator was 1 and our...