A serial mediation model.
Format
A data frame with 100 rows and 6 variables:
- x
Predictor. Numeric.
- m1
Mediator 1. Numeric.
- m2
Mediator 2. Numeric.
- y
Outcome variable. Numeric.
- c1
Control variable. Numeric.
- c2
Control variable. Numeric.
Examples
library(lavaan)
data(data_serial)
mod <-
"
m1 ~ a * x + c1 + c2
m2 ~ b1 * m1 + x + c1 + c2
y ~ b2 * m2 + m1 + x + c1 + c2
indirect := a * b1 * b2
"
fit <- sem(mod, data_serial,
meanstructure = TRUE, fixed.x = FALSE)
parameterEstimates(fit)[c(1, 4, 8, 28), ]
#> lhs op rhs label est se z pvalue ci.lower ci.upper
#> 1 m1 ~ x a 0.822 0.092 8.907 0.000 0.641 1.003
#> 4 m2 ~ m1 b1 0.421 0.099 4.237 0.000 0.226 0.615
#> 8 y ~ m2 b2 0.521 0.221 2.361 0.018 0.088 0.953
#> 28 indirect := a*b1*b2 indirect 0.180 0.090 2.009 0.045 0.004 0.356