Generate a User-Defined Within-Subject Mediation Model

Generates lavaan model syntax for a user-defined within-subject mediation model. Users specify directed paths among mediators and from mediators to the outcome. The function automatically adds the corresponding difference and level components and identifies all indirect effects.

Usage

GenerateModelCustom(prepared_data, paths, MP = character(0))

Arguments

prepared_data: A data frame returned by [PrepareData()]. It must contain `M1diff`, `M1avg`, ..., and `Ydiff`.
paths: A character vector defining directed paths among mediators and from mediators to the outcome. For example: `c("M1 -> M2", "M2 -> Y")`.
MP: A character vector identifying moderated paths. Supported labels follow the existing wsMed convention: `a1`, `b1`, `d1`, `b_1_2`, `d_1_2`, and `cp`.

Value

A character string containing lavaan model syntax.

Examples

prepared_data <- data.frame(
  M1diff = rnorm(100),
  M1avg  = rnorm(100),
  M2diff = rnorm(100),
  M2avg  = rnorm(100),
  M3diff = rnorm(100),
  M3avg  = rnorm(100),
  Ydiff  = rnorm(100)
)

model <- GenerateModelCustom(
 prepared_data = prepared_data,
 paths = c(
   "M1 -> M3",
   "M1 -> Y",
   "M3 -> Y",
   "M2 -> Y"
 )
)

cat(model)
#> Ydiff ~ cp*1 + b1*M1diff + d1*M1avg + b2*M2diff + d2*M2avg + b3*M3diff + d3*M3avg
#> M1diff ~ a1*1
#> M2diff ~ a2*1
#> M3diff ~ a3*1 + b_1_3*M1diff + d_1_3*M1avg
#> indirect_1_3 := a1 * b_1_3 * b3
#> indirect_1 := a1 * b1
#> indirect_2 := a2 * b2
#> indirect_3 := a3 * b3
#> total_indirect := indirect_1_3 + indirect_1 + indirect_2 + indirect_3
#> total_effect := cp + total_indirect