Nothing
devtools::load_all()
m1 <- '
X =~ x1 + x2
Z =~ z1 + z2
Y =~ y1 + y2
Y ~ X + Z + X:Z
'
fit_pi <- modsem(m1, oneInt)
bootstrap_modsem(fit_pi, FUN = coef, R = 10)
rsqr_diff <- function(est_h1) {
est_h0 <- estimate_h0(est_h1, reduced = FALSE)
r2.h1 <- modsem_inspect(est_h1, what = "r2")
r2.h0 <- modsem_inspect(est_h0, what = "r2")
r2.h1[names(r2.h0)] - r2.h0
}
bootstrap_modsem(fit_pi, FUN = rsqr_diff, R = 10)
fit_da <- modsem(m1, oneInt, method = "lms")
summary(fit_da)
bootstrap_modsem(fit_da, FUN = coef, R = 10L)
tpb <- "
# Outer Model (Based on Hagger et al., 2007)
ATT =~ att1 + att2 + att3 + att4 + att5
SN =~ sn1 + sn2
PBC =~ pbc1 + pbc2 + pbc3
INT =~ int1 + int2 + int3
BEH =~ b1 + b2
# Inner Model (Based on Steinmetz et al., 2011)
INT ~ ATT + SN + PBC
BEH ~ INT + PBC + INT:PBC
"
boot <- bootstrap_modsem(model = modsem,
model.syntax = tpb, data = TPB,
method = "dblcent", rcs = TRUE,
rcs.scale.corrected = TRUE,
rcs.mc.reps = 10000,
R = 10L,
FUN = "coef")
coef <- apply(boot, MARGIN = 2, FUN = mean, na.rm = TRUE)
se <- apply(boot, MARGIN = 2, FUN = sd, na.rm = TRUE)
cat("Parameter Estimates:\n")
print(coef)
cat("Standard Errors: \n")
print(se)
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