med_serial3: Serial Mediation Model with Three Mediators
In jeksterslabds/jeksterslabRds: Jekster's Lab Data Science and Statistics

Estimates the indirect effect in a serial mediation model, that is the product of α1, xi1 , xi3, and β2 from M1_i = δ_{M1} + α1 X_i + ε_{M1_i}, M2_i = δ_{M2} + α2 X_i + ξ1 M1_i + ε_{M2_i}, M3_i = δ_{M3} + α3 X_i + ξ2 M1_i + ξ3 M2_i + ε_{M3_i}, and Y_i = δ_Y + τ^{\prime} X_i + β1 M1_i + β2 M2_i + β3 M3_i + ε_{Y_i}.

1	med_serial3(data, scale = FALSE, minimal = TRUE, s2 = FALSE, s2_est = "both")

`data`	A matrix with variables X, M1, M2, M3, and Y.
`scale`	Logical. If `TRUE`, scales the data before fitting the model.
`minimal`	Logical. If `TRUE`, returns the indirect effect of X on Y through M1, M2, amd M3. If `FALSE`, returns all the regression coefficients estimated.
`s2`	Logical. If `TRUE`, estimates residual variance.
`s2_est`	String. Residual variance estimator. If `"both"`, returns both OLS and ML estimates as a vector. If `"ols"`, returns OLS estimate. If `"ml"`, returns ML estimate. Ignored if `s2 = FALSE`.