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Group Estimates By Dependent or Independent Variables

Source: R/group_by_dvs.R
group_estimates.Rd

Groups parameter estimates or other information such as p-values into a table with dependent variables as columns and independent variables as rows, or a transpose of this table.

Usage

group_by_dvs(
  object,
  ...,
  col_name = "est",
  add_prefix = TRUE,
  group_first = FALSE,
  use_standardizedSolution = FALSE
)

group_by_ivs(
  object,
  ...,
  col_name = "est",
  add_prefix = TRUE,
  group_first = FALSE,
  use_standardizedSolution = FALSE
)

Arguments

object

A lavaan object or the output of lavaan::parameterEstimates() or lavaan::standardizedSolution().

...

Optional arguments to be passed to lavaan::parameterEstimates(). Ignored if object is an output of lavaan::parameterEstimates() or lavaan::standardizedSolution().

col_name

The column name of information to be grouped. Default is "est". It accepts only one name.

add_prefix

If TRUE, the default, col_name will be added as prefix to the column names of the output.

group_first

If TRUE, the rows will be grouped by groups first and then by independent variables Ignored if the model has only one group. Default is FALSE.

use_standardizedSolution

If TRUE and object is not an estimates table, then lavaan::standardizedSolution() will be used to generate the table. If FALSE, the default, then lavaan::parameterEstimates() will be used if necessary.

Value

A data-frame-like object of the class est_table.

Details

It gets a lavaan object or the output of lavaan::parameterEstimates() or lavaan::standardizedSolution() and group selected columns by "dependent" variables group_by_dvs() or by "independent" variables group_by_ivs().

"Dependent" variables are defined as variables on the left hand side of the operator ~.

"Independent" variables are defined as variables on the right hand side of the operator ~.

Note that a variable can both be a "dependent" variable and an "independent" variable in a model.

Author

Shu Fai Cheung https://orcid.org/0000-0002-9871-9448

Examples


library(lavaan)
set.seed(5478374)
n <- 50
x <- runif(n) - .5
m <- .40 * x + rnorm(n, 0, sqrt(1 - .40))
y <- .30 * m + rnorm(n, 0, sqrt(1 - .30))
dat <- data.frame(x = x, y = y, m = m)
model <-
'
m ~ a*x
y ~ b*m
ab := a*b
'

fit <- sem(model, data = dat, fixed.x = FALSE)
parameterEstimates(fit)
#>   lhs op rhs label   est    se     z pvalue ci.lower ci.upper
#> 1   m  ~   x     a 0.569 0.343 1.660  0.097   -0.103    1.240
#> 2   y  ~   m     b 0.219 0.153 1.430  0.153   -0.081    0.519
#> 3   m ~~   m       0.460 0.092 5.000  0.000    0.280    0.641
#> 4   y ~~   y       0.570 0.114 5.000  0.000    0.347    0.794
#> 5   x ~~   x       0.078 0.016 5.000  0.000    0.048    0.109
#> 6  ab := a*b    ab 0.125 0.115 1.083  0.279   -0.101    0.350

# Group by DVs
group_by_dvs(fit)
#>   iv est_m est_y
#> m  m    -- 0.219
#> x  x 0.569    --

# Group by IVs
group_by_ivs(fit)
#>   dv est_m est_x
#> m  m    -- 0.569
#> y  y 0.219    --