```mermaid graph LR treatment --> |indirect\npath a\n0.034| t1 t1 --> |indirect\npath b\n0.27\npersistence| t2 treatment --> |direct\npath d\n0.01| t2 ``` ```r # simulate model_sim <- glue(' t1 ~ 0.034*treatment + 0.5*t0 t2 ~ 0.01*treatment + 0.27*t1 + 0.5*t0 ') # recover model <- " # mediator model (a path) t1 ~ a*treatment + c1*t0 # full model (b and d paths) t2 ~ d*treatment + b*t1 + c2*t0 indirect := a*b total := d + (a*b) direct := total - indirect prop_med := (a*b)/(d + (a*b)) " ``` Conclusions - To estimate persistence, fit `t2 ~ t0 + t1` (i.e., coefficient for `t1`). - Ratios of treatment coefficients from `t1 ~ treatment + t0` and `t2 ~ treatment + t0` do not reflect persistence is there is a non-zero direct effect. If direct effect is exactly 0, then results will be identical. - To get indirect (i.e., mediation effect), fit the full mediation model.