modelbpp (version 0.1.6)

get_add: Models That Are Less Restricted

Description

Generate a list of models with one or more fixed parameter freed.

Usage

get_add(
  sem_out,
  must_add = NULL,
  must_not_add = NULL,
  remove_constraints = TRUE,
  exclude_error_cov = TRUE,
  exclude_feedback = FALSE,
  exclude_xy_cov = FALSE,
  df_change = 1,
  model_id = NA,
  keep_correct_df_change = TRUE,
  remove_duplicated = TRUE,
  progress = FALSE
)

Value

An object of the class partables, a named list of parameter tables, each of them to be used by lavaan::lavaan() or update()

for fitting a model with the added parameters.

Arguments

sem_out

The original model, which is the output from an structural equation modeling function. Currently support lavaan::lavaan objects only.

must_add

A character vector of parameters, named in lavaan::lavaan() style (e.g., "y ~ x"), that must be added. Default is NULL.

must_not_add

A character vector of parameters, named in lavaan::lavaan() style (e.g., "x1 ~~ x1"), that must not be added. Default is NULL.

remove_constraints

Whether equality constraints will be removed. Default is TRUE.

exclude_error_cov

Exclude error covariances of indicators. Default is TRUE.

exclude_feedback

Exclude paths that will result in a feedback loop. For example, if there is path from x through m to y, then the path x ~ y will create a feedback loop. Default is FALSE for now, to maintain backward compatibility. Do not rely on the default value because it will be changed to TRUE in a future major version.

exclude_xy_cov

Exclude covariance between two variables, in which one has a path to another. For example, if there is path from x through m to y, then the covariance x ~~ y, which denotes the covariance between x and the error term of y, will be excluded if this argument is TRUE. Default is FALSE for now, to maintain backward compatibility. Do not rely on the default value because it will be changed to TRUE in a future major version.

df_change

How many degrees of freedom (df) away in the list. All models with df change less than or equal to this number will be included, taking into account requirements set by other arguments. Default is 1.

model_id

The identification number of the starting model. Default is NA, no identification number.

keep_correct_df_change

Keep only models with actual df change equal to expected df change.

remove_duplicated

If TRUE, the default, duplicated models are removed.

progress

Whether a progress bar will be displayed, implemented by the pbapply package. Default is FALSE.

Author

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

Details

It generates a list of models with one or more fixed parameter freed (and the degrees of freedom, df, increases by one or more). If a model has equality constraints, models with one or more of the constraints between two free parameters released will also be included.

Graphically, paths or covariances are "added" to form the list of models.

The models to be included are identified by lavaan::modificationIndices().

The models will be checked by lavaan to make sure that the decrease in model degrees of freedom is of the expected value.

This function is called by model_set() and usually users do not need to call it. It is exported for advanced users.

See Also

print.partables()

Examples

library(lavaan)
dat <- dat_path_model
mod <-
"
x3 ~ a*x1 + b*x2
x4 ~ a*x1
ab := a*b
"
fit <- sem(mod, dat_path_model, fixed.x = TRUE)
mod_to_add <- get_add(fit)
mod_to_add