Misidentification 3: Y1 regressed on X1, EX1, & LEN7

For the third misidentification, we regressed Y₁ on X1, EX1, and LEN7 using the base LM command in R (illustrated in the Figure below). This was replicated 10,000 times – using R-loops – while randomly varying the effects for each causal pathway between the constructs in the network excluding the direct effect of X₁ on Y₁ (true direct causal effect = 1.00; N = 10,000; R-Code).

As illustrated in the figure below, the misidentification of the structural association where Y₁ was regressed on X₁, as well as all EX1 and LEN7, produced an average slope coefficient of b = 27.74. This suggests that a 1 point increase in X₁ directly causes a 27.74 increase in Y₁, on average. As a reminder, the true slope coefficient is 1.00. We will begin exploring structural specifications in Misidentification 4!