Sample Dataset: Simple Mediation with Both Paths Moderated By a Moderator
Source:R/dat_2_and_3.R
data_med_mod_ab1.RdA simple mediation model with a-path and b-path moderated by one moderator.
Format
A data frame with 100 rows and 6 variables:
- x
Predictor. Numeric.
- w
Moderator. Numeric.
- m
Mediator. Numeric.
- y
Outcome variable. Numeric.
- c1
Control variable. Numeric.
- c2
Control variable. Numeric.
Examples
library(lavaan)
data(data_med_mod_ab1)
data_med_mod_ab1$xw <-
data_med_mod_ab1$x *
data_med_mod_ab1$w
data_med_mod_ab1$mw <-
data_med_mod_ab1$m *
data_med_mod_ab1$w
mod <-
"
m ~ a * x + w + da * xw + c1 + c2
y ~ b * m + x + w + db * mw + c1 + c2
w ~~ v_w * w
w ~ m_w * 1
ab := a * b
ab_lo := (a + da * (m_w - sqrt(v_w))) * (b + db * (m_w - sqrt(v_w)))
ab_hi := (a + da * (m_w + sqrt(v_w))) * (b + db * (m_w + sqrt(v_w)))
"
fit <- sem(mod, data_med_mod_ab1,
meanstructure = TRUE, fixed.x = FALSE)
parameterEstimates(fit)[c(1, 3, 6, 9, 38:40), ]
#> lhs op rhs label est se
#> 1 m ~ x a -1.255 0.164
#> 3 m ~ xw da 0.264 0.011
#> 6 y ~ m b -1.276 0.036
#> 9 y ~ mw db 0.331 0.014
#> 38 ab := a*b ab 1.602 0.214
#> 39 ab_lo := (a+da*(m_w-sqrt(v_w)))*(b+db*(m_w-sqrt(v_w))) ab_lo -0.006 0.014
#> 40 ab_hi := (a+da*(m_w+sqrt(v_w)))*(b+db*(m_w+sqrt(v_w))) ab_hi 0.246 0.096
#> z pvalue ci.lower ci.upper
#> 1 -7.659 0.000 -1.576 -0.934
#> 3 23.531 0.000 0.242 0.286
#> 6 -35.731 0.000 -1.346 -1.206
#> 9 23.119 0.000 0.303 0.359
#> 38 7.489 0.000 1.182 2.021
#> 39 -0.437 0.662 -0.033 0.021
#> 40 2.555 0.011 0.057 0.435