Generate a list of models with one or more free parameter dropped (fixed to zero).
Usage
get_drop(
sem_out,
must_drop = NULL,
must_not_drop = NULL,
df_change = 1,
model_id = NA,
keep_correct_df_change = TRUE,
remove_duplicated = TRUE,
progress = FALSE
)Arguments
- sem_out
The original model, which is the output from an structural equation modeling function. Currently support lavaan::lavaan objects only.
- must_drop
A character vector of parameters, named in
lavaan::lavaan()style (e.g.,"y ~ x"), that must be included. Default isNULL.- must_not_drop
A character vector of parameters, named in
lavaan::lavaan()style (e.g.,"x1 ~~ x1"), that must not be included. Default isNULL.- df_change
How many degrees of freedom 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
pbapplypackage. Default isFALSE.
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.
Details
It generates a list of models with one or more free parameters dropped, that is, fixed to zero (with degrees of freedom, df, increases by one or more).
All free parameters are included in the pool of candidates, except for those explicitly requested to be kept.
The models will be checked by lavaan
to make sure that the increase 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.
Author
Shu Fai Cheung https://orcid.org/0000-0002-9871-9448
Examples
library(lavaan)
dat <- dat_path_model
mod <-
"
x3 ~ a*x1 + b*x2
x4 ~ a*x1 + x2
ab := a*b
"
fit <- sem(mod, dat_path_model, fixed.x = TRUE)
mod_to_drop <- get_drop(fit)
mod_to_drop
#> $`drop: x3~x2`
#> id lhs op rhs user block group free ustart exo label plabel start est
#> 1 1 x3 ~ x1 1 1 1 1 NA 0 a .p1. 0.282 0.279
#> 2 2 x3 ~ x2 1 1 1 0 0 0 b .p2. 0.000 0.000
#> 3 3 x4 ~ x1 1 1 1 2 NA 0 a .p3. 0.282 0.279
#> 4 4 x4 ~ x2 1 1 1 3 NA 0 .p4. 0.402 0.204
#> 5 5 x3 ~~ x3 0 1 1 4 NA 0 .p5. 0.382 0.683
#> 6 6 x4 ~~ x4 0 1 1 5 NA 0 .p6. 0.430 0.475
#> 7 7 x3 ~~ x4 0 1 1 6 NA 0 .p7. 0.148 0.264
#> 8 8 x1 ~~ x1 0 1 1 0 NA 1 .p8. 1.109 1.109
#> 9 9 x1 ~~ x2 0 1 1 0 NA 1 .p9. 0.040 0.040
#> 10 10 x2 ~~ x2 0 1 1 0 NA 1 .p10. 1.148 1.148
#> 11 11 .p1. == .p3. 2 0 0 0 NA 0 0.000 0.000
#> se
#> 1 0.050
#> 2 0.058
#> 3 0.050
#> 4 0.061
#> 5 0.054
#> 6 0.061
#> 7 0.043
#> 8 0.000
#> 9 0.000
#> 10 0.000
#> 11 0.000
#>
#> $`drop: x4~x2`
#> id lhs op rhs user block group free ustart exo label plabel start est
#> 1 1 x3 ~ x1 1 1 1 1 NA 0 a .p1. 0.282 0.299
#> 2 2 x3 ~ x2 1 1 1 2 NA 0 b .p2. 0.511 0.372
#> 3 3 x4 ~ x1 1 1 1 3 NA 0 a .p3. 0.282 0.299
#> 4 4 x4 ~ x2 1 1 1 0 0 0 .p4. 0.000 0.000
#> 5 5 x3 ~~ x3 0 1 1 4 NA 0 .p5. 0.382 0.403
#> 6 6 x4 ~~ x4 0 1 1 5 NA 0 .p6. 0.430 0.617
#> 7 7 x3 ~~ x4 0 1 1 6 NA 0 .p7. 0.148 0.212
#> 8 8 x1 ~~ x1 0 1 1 0 NA 1 .p8. 1.109 1.109
#> 9 9 x1 ~~ x2 0 1 1 0 NA 1 .p9. 0.040 0.040
#> 10 10 x2 ~~ x2 0 1 1 0 NA 1 .p10. 1.148 1.148
#> 11 11 .p1. == .p3. 2 0 0 0 NA 0 0.000 0.000
#> se
#> 1 0.050
#> 2 0.058
#> 3 0.050
#> 4 0.061
#> 5 0.054
#> 6 0.061
#> 7 0.043
#> 8 0.000
#> 9 0.000
#> 10 0.000
#> 11 0.000
#>
#> $`drop: x3~~x4`
#> id lhs op rhs user block group free ustart exo label plabel start est
#> 1 1 x3 ~ x1 1 1 1 1 NA 0 a .p1. 0.282 0.281
#> 2 2 x3 ~ x2 1 1 1 2 NA 0 b .p2. 0.511 0.511
#> 3 3 x4 ~ x1 1 1 1 3 NA 0 a .p3. 0.282 0.281
#> 4 4 x4 ~ x2 1 1 1 4 NA 0 .p4. 0.402 0.402
#> 5 5 x3 ~~ x3 0 1 1 5 NA 0 .p5. 0.382 0.382
#> 6 6 x4 ~~ x4 0 1 1 6 NA 0 .p6. 0.430 0.430
#> 7 7 x3 ~~ x4 0 1 1 0 0 0 .p7. 0.000 0.000
#> 8 8 x1 ~~ x1 0 1 1 0 NA 1 .p8. 1.109 1.109
#> 9 9 x1 ~~ x2 0 1 1 0 NA 1 .p9. 0.040 0.040
#> 10 10 x2 ~~ x2 0 1 1 0 NA 1 .p10. 1.148 1.148
#> 11 11 .p1. == .p3. 2 0 0 0 NA 0 0.000 0.000
#> se
#> 1 0.050
#> 2 0.058
#> 3 0.050
#> 4 0.061
#> 5 0.054
#> 6 0.061
#> 7 0.043
#> 8 0.000
#> 9 0.000
#> 10 0.000
#> 11 0.000
#>