summary.modsem_lms {modsem}

summary for modsem objects

Description

summary for modsem objects

summary for modsem objects

summary for modsem objects

summary for modsem objects

Usage

## S3 method for class 'modsem_lms'
summary(
  object,
  H0 = TRUE,
  verbose = TRUE,
  r.squared = TRUE,
  adjusted.stat = FALSE,
  digits = 3,
  scientific = FALSE,
  ci = FALSE,
  standardized = FALSE,
  loadings = TRUE,
  regressions = TRUE,
  covariances = TRUE,
  intercepts = TRUE,
  variances = TRUE,
  ...
)

## S3 method for class 'modsem_qml'
summary(
  object,
  H0 = TRUE,
  verbose = TRUE,
  r.squared = TRUE,
  adjusted.stat = FALSE,
  digits = 3,
  scientific = FALSE,
  ci = FALSE,
  standardized = FALSE,
  loadings = TRUE,
  regressions = TRUE,
  covariances = TRUE,
  intercepts = TRUE,
  variances = TRUE,
  ...
)

## S3 method for class 'modsem_mplus'
summary(
  object,
  scientific = FALSE,
  standardize = FALSE,
  ci = FALSE,
  digits = 3,
  loadings = TRUE,
  regressions = TRUE,
  covariances = TRUE,
  intercepts = TRUE,
  variances = TRUE,
  ...
)

## S3 method for class 'modsem_pi'
summary(object, ...)

Arguments

object

modsem object to summarized

H0

should a null model be estimated (used for comparison)

verbose

print progress for the estimation of null model

r.squared

calculate R-squared

adjusted.stat

should sample size corrected/adjustes AIC and BIC be reported?

digits

number of digits to print

scientific

print p-values in scientific notation

ci

print confidence intervals

standardized

print standardized estimates

loadings

print loadings

regressions

print regressions

covariances

print covariances

intercepts

print intercepts

variances

print variances

...

arguments passed to lavaan::summary()

standardize

standardize estimates

Examples

## Not run: 
m1 <- "
 # Outer Model
 X =~ x1 + x2 + x3
 Y =~ y1 + y2 + y3
 Z =~ z1 + z2 + z3

 # Inner model
 Y ~ X + Z + X:Z
"

est1 <- modsem(m1, oneInt, "lms")
summary(est1, ci = TRUE, scientific = TRUE)

## End(Not run)
## Not run: 
m1 <- "
 # Outer Model
 X =~ x1 + x2 + x3
 Y =~ y1 + y2 + y3
 Z =~ z1 + z2 + z3

 # Inner model
 Y ~ X + Z + X:Z
"

est1 <- modsem(m1, oneInt, "qml")
summary(est1, ci = TRUE, scientific = TRUE)

## End(Not run)