bruceR (version 2023.9)

lavaan_summary: Tidy report of lavaan model.

Description

Tidy report of lavaan model.

Usage

lavaan_summary(
  lavaan,
  ci = c("raw", "boot", "bc.boot", "bca.boot"),
  nsim = 100,
  seed = NULL,
  digits = 3,
  print = TRUE,
  covariance = FALSE,
  file = NULL
)

Value

Invisibly return a list of results:

fit

Model fit indices.

measure

Latent variable measures.

regression

Regression paths.

covariance

Variances and/or covariances.

effect

Defined effect estimates.

Arguments

lavaan

Model object fitted by lavaan.

ci

Method for estimating standard error (SE) and 95% confidence interval (CI).

Defaults to "raw" (the standard approach of lavaan). Other options:

"boot"

Percentile Bootstrap

"bc.boot"

Bias-Corrected Percentile Bootstrap

"bca.boot"

Bias-Corrected and Accelerated (BCa) Percentile Bootstrap

nsim

Number of simulation samples (bootstrap resampling) for estimating SE and 95% CI. In formal analyses, nsim=1000 (or larger) is strongly suggested.

seed

Random seed for obtaining reproducible results. Defaults to NULL.

digits

Number of decimal places of output. Defaults to 3.

print

Print results. Defaults to TRUE.

covariance

Print (co)variances. Defaults to FALSE.

file

File name of MS Word (.doc).

See Also

PROCESS, CFA

Examples

## Simple Mediation:
## Solar.R (X) => Ozone (M) => Temp (Y)

# PROCESS(airquality, y="Temp", x="Solar.R",
#         meds="Ozone", ci="boot", nsim=1000, seed=1)

model = "
Ozone ~ a*Solar.R
Temp ~ c.*Solar.R + b*Ozone
Indirect := a*b
Direct := c.
Total := c. + a*b
"
lv = lavaan::sem(model=model, data=airquality)
lavaan::summary(lv, fit.measure=TRUE, ci=TRUE, nd=3)  # raw output
lavaan_summary(lv)
# lavaan_summary(lv, ci="boot", nsim=1000, seed=1)


## Serial Multiple Mediation:
## Solar.R (X) => Ozone (M1) => Wind(M2) => Temp (Y)

# PROCESS(airquality, y="Temp", x="Solar.R",
#         meds=c("Ozone", "Wind"),
#         med.type="serial", ci="boot", nsim=1000, seed=1)

model0 = "
Ozone ~ a1*Solar.R
Wind ~ a2*Solar.R + d12*Ozone
Temp ~ c.*Solar.R + b1*Ozone + b2*Wind
Indirect_All := a1*b1 + a2*b2 + a1*d12*b2
Ind_X_M1_Y := a1*b1
Ind_X_M2_Y := a2*b2
Ind_X_M1_M2_Y := a1*d12*b2
Direct := c.
Total := c. + a1*b1 + a2*b2 + a1*d12*b2
"
lv0 = lavaan::sem(model=model0, data=airquality)
lavaan::summary(lv0, fit.measure=TRUE, ci=TRUE, nd=3)  # raw output
lavaan_summary(lv0)
# lavaan_summary(lv0, ci="boot", nsim=1000, seed=1)

model1 = "
Ozone ~ a1*Solar.R
Wind ~ d12*Ozone
Temp ~ c.*Solar.R + b1*Ozone + b2*Wind
Indirect_All := a1*b1 + a1*d12*b2
Ind_X_M1_Y := a1*b1
Ind_X_M1_M2_Y := a1*d12*b2
Direct := c.
Total := c. + a1*b1 + a1*d12*b2
"
lv1 = lavaan::sem(model=model1, data=airquality)
lavaan::summary(lv1, fit.measure=TRUE, ci=TRUE, nd=3)  # raw output
lavaan_summary(lv1)
# lavaan_summary(lv1, ci="boot", nsim=1000, seed=1)