Description Usage Arguments Value Examples
Simple mediation analysis
1 2 3 |
data |
the data as a data frame |
dep |
a string naming the dependent variable |
med |
a string naming the mediator variable |
pred |
a string naming the predictor variable |
estMethod |
|
bootstrap |
a number between 1 and 100000 (default: 1000) specifying the number of samples that need to been drawn in the bootstrap method |
test |
|
ci |
|
ciWidth |
a number between 50 and 99.9 (default: 95) specifying the
confidence interval width that is used as |
pm |
|
paths |
|
label |
|
estPlot |
|
A results object containing:
results$med | a table containing mediation estimates | ||||
results$paths | a table containing the individual path estimates | ||||
results$estPlot | an image | ||||
results$modelSyntax | the lavaan syntax used to fit the mediation model | ||||
Tables can be converted to data frames with asDF
or as.data.frame
. For example:
results$med$asDF
as.data.frame(results$med)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | set.seed(1234)
X <- rnorm(10)
M <- 0.5*X + rnorm(10)
Y <- 0.7*M + rnorm(10)
dat <- data.frame(X=X, M=M, Y=Y)
med(dat, dep = "Y", pred = "X", med = "M")
#
# Mediation Estimates
# -----------------------------------------------------
# Effect Estimate SE Z p
# -----------------------------------------------------
# Indirect 0.3736 0.0920 4.059 < .001
# Direct 0.0364 0.1044 0.348 0.728
# Total 0.4100 0.1247 3.287 0.001
# -----------------------------------------------------
#
#
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