| plotProbe {semTools} | R Documentation |
This function will plot the line graphs representing the simple effect of the independent variable given the values of the moderator.
plotProbe(object, xlim, xlab="Indepedent Variable", ylab="Dependent Variable", ...)
object |
The result of probing latent interaction obtained from |
xlim |
The vector of two numbers: the minimum and maximum values of the independent variable |
xlab |
The label of the x-axis |
ylab |
The label of the y-axis |
... |
Any addition argument for the |
None. This function will plot the simple main effect only.
Sunthud Pornprasertmanit (psunthud@gmail.com)
indProd For creating the indicator products with no centering, mean centering, double-mean centering, or residual centering.
probe2WayMC For probing the two-way latent interaction when the results are obtained from mean-centering, or double-mean centering.
probe3WayMC For probing the three-way latent interaction when the results are obtained from mean-centering, or double-mean centering.
probe2WayRC For probing the two-way latent interaction when the results are obtained from residual-centering approach.
probe3WayRC For probing the two-way latent interaction when the results are obtained from residual-centering approach.
library(lavaan)
dat2wayMC <- indProd(dat2way, 1:3, 4:6)
model1 <- "
f1 =~ x1 + x2 + x3
f2 =~ x4 + x5 + x6
f12 =~ x1.x4 + x2.x5 + x3.x6
f3 =~ x7 + x8 + x9
f3 ~ f1 + f2 + f12
f12 ~~0*f1
f12 ~~ 0*f2
x1 ~ 0*1
x4 ~ 0*1
x1.x4 ~ 0*1
x7 ~ 0*1
f1 ~ NA*1
f2 ~ NA*1
f12 ~ NA*1
f3 ~ NA*1
"
fitMC2way <- sem(model1, data=dat2wayMC, meanstructure=TRUE, std.lv=FALSE)
result2wayMC <- probe2WayMC(fitMC2way, c("f1", "f2", "f12"), "f3", "f2", c(-1, 0, 1))
plotProbe(result2wayMC, xlim=c(-2, 2))
dat3wayMC <- indProd(dat3way, 1:3, 4:6, 7:9)
model3 <- "
f1 =~ x1 + x2 + x3
f2 =~ x4 + x5 + x6
f3 =~ x7 + x8 + x9
f12 =~ x1.x4 + x2.x5 + x3.x6
f13 =~ x1.x7 + x2.x8 + x3.x9
f23 =~ x4.x7 + x5.x8 + x6.x9
f123 =~ x1.x4.x7 + x2.x5.x8 + x3.x6.x9
f4 =~ x10 + x11 + x12
f4 ~ f1 + f2 + f3 + f12 + f13 + f23 + f123
f1 ~~ 0*f12
f1 ~~ 0*f13
f1 ~~ 0*f123
f2 ~~ 0*f12
f2 ~~ 0*f23
f2 ~~ 0*f123
f3 ~~ 0*f13
f3 ~~ 0*f23
f3 ~~ 0*f123
f12 ~~ 0*f123
f13 ~~ 0*f123
f23 ~~ 0*f123
x1 ~ 0*1
x4 ~ 0*1
x7 ~ 0*1
x10 ~ 0*1
x1.x4 ~ 0*1
x1.x7 ~ 0*1
x4.x7 ~ 0*1
x1.x4.x7 ~ 0*1
f1 ~ NA*1
f2 ~ NA*1
f3 ~ NA*1
f12 ~ NA*1
f13 ~ NA*1
f23 ~ NA*1
f123 ~ NA*1
f4 ~ NA*1
"
fitMC3way <- sem(model3, data=dat3wayMC, meanstructure=TRUE, std.lv=FALSE)
result3wayMC <- probe3WayMC(fitMC3way, c("f1", "f2", "f3", "f12", "f13", "f23", "f123"),
"f4", c("f1", "f2"), c(-1, 0, 1), c(-1, 0, 1))
plotProbe(result3wayMC, xlim=c(-2, 2))