A one-moderator model.
Format
A data frame with 100 rows and 5 variables:
- x
Predictor. Numeric.
- w
Moderator. Numeric.
- y
Outcome variable. Numeric.
- c1
Control variable. Numeric.
- c2
Control variable. Numeric.
Examples
library(lavaan)
data(data_mod)
data_mod$xw <- data_mod$x * data_mod$w
mod <-
"
y ~ a * x + w + d * xw + c1 + c2
w ~~ v_w * w
w ~ m_w * 1
a_lo := a + d * (m_w - sqrt(v_w))
a_hi := a + d * (m_w + sqrt(v_w))
"
fit <- sem(mod, data_mod, fixed.x = FALSE)
parameterEstimates(fit)[c(1, 3, 6, 7, 24, 25), ]
#> lhs op rhs label est se z pvalue ci.lower
#> 1 y ~ x a 0.453 0.235 1.924 0.054 -0.008
#> 3 y ~ xw d 0.596 0.020 29.951 0.000 0.557
#> 6 w ~~ w v_w 1.137 0.161 7.071 0.000 0.822
#> 7 w ~1 m_w 3.213 0.107 30.142 0.000 3.005
#> 24 a_lo := a+d*(m_w-sqrt(v_w)) a_lo 1.733 0.244 7.113 0.000 1.256
#> 25 a_hi := a+d*(m_w+sqrt(v_w)) a_hi 3.004 0.247 12.178 0.000 2.521
#> ci.upper
#> 1 0.915
#> 3 0.635
#> 6 1.452
#> 7 3.422
#> 24 2.211
#> 25 3.487