For tasks such as comparing two parameter
tables inside a partables-class object.
Usage
identical_partables(object1, object2)
is_partable(x)
same_variables(x)
get_partables(x)
to_partables(...)Value
The function identical_partables()
returns either TRUE or FALSE.
The function is_partable()
returns either TRUE or FALSE.
The function same_variables()
returns either TRUE or FALSE.
The function get_partables()
returns a partables-class
object.
The function to_partables()
returns a partables-class
object, created from the objects
supplied.
Details
The function identical_partables() compare two
lavaan parameter tables and see whether they
are identical. (Adapted from a similar function
in the package semhelpinghands).
The function is_partable() tries
to
check whether an object is "likely"
to be a parameter table that can be
used by lavaan::lavaan() and its
wrappers, such as lavaan::sem().
Note that there is no guarantee the the parameter table makes sense or will not lead to error when fitted. It can only check whether it has the required columns.
The function same_variables()
check whether all parameter labels
in a partables-class object use
the same observed variables.
The function get_partables()
extract the partable object from
a model_set-class object.
The function to_partables()
combine objects to create a
partables-class object.
The objects to be combined can be
a lavaan-class object (e.g.,
the output of lavaan::sem())
or a parameter table of lavaan.
Examples
library(lavaan)
mod1 <-
"
x3 ~ x1
x2 ~ x4
"
mod2 <-
"
x2 ~ x4
x3 ~ x1
"
fit1 <- sem(mod1, dat_path_model)
fit2 <- sem(mod2, dat_path_model)
pt1 <- parameterTable(fit1)
pt2 <- parameterTable(fit2)
identical_partables(pt1, pt2)
#> [1] TRUE
is_partable(pt1)
#> [1] TRUE
out <- model_set(fit1,
fit_models = FALSE)
#>
#> Generate 2 less restrictive model(s):
#>
| | 0 % ~calculating
|+++++++++++++++++++++++++ | 50% ~00s
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s
#>
#> Generate 3 more restrictive model(s):
#>
| | 0 % ~calculating
|+++++++++++++++++ | 33% ~00s
|++++++++++++++++++++++++++++++++++ | 67% ~00s
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s
#>
#> Check for duplicated models (6 model[s] to check):
#>
|
| | 0%
|
|+++ | 7%
|
|+++++++ | 13%
|
|++++++++++ | 20%
|
|+++++++++++++ | 27%
|
|+++++++++++++++++ | 33%
|
|++++++++++++++++++++ | 40%
|
|+++++++++++++++++++++++ | 47%
|
|+++++++++++++++++++++++++++ | 53%
|
|++++++++++++++++++++++++++++++ | 60%
|
|+++++++++++++++++++++++++++++++++ | 67%
|
|+++++++++++++++++++++++++++++++++++++ | 73%
|
|++++++++++++++++++++++++++++++++++++++++ | 80%
|
|+++++++++++++++++++++++++++++++++++++++++++ | 87%
|
|+++++++++++++++++++++++++++++++++++++++++++++++ | 93%
|
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100%
same_variables(get_partables(out))
#> [1] TRUE
out <- model_set(fit1,
fit_models = FALSE)
#>
#> Generate 2 less restrictive model(s):
#>
| | 0 % ~calculating
|+++++++++++++++++++++++++ | 50% ~00s
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s
#>
#> Generate 3 more restrictive model(s):
#>
| | 0 % ~calculating
|+++++++++++++++++ | 33% ~00s
|++++++++++++++++++++++++++++++++++ | 67% ~00s
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s
#>
#> Check for duplicated models (6 model[s] to check):
#>
|
| | 0%
|
|+++ | 7%
|
|+++++++ | 13%
|
|++++++++++ | 20%
|
|+++++++++++++ | 27%
|
|+++++++++++++++++ | 33%
|
|++++++++++++++++++++ | 40%
|
|+++++++++++++++++++++++ | 47%
|
|+++++++++++++++++++++++++++ | 53%
|
|++++++++++++++++++++++++++++++ | 60%
|
|+++++++++++++++++++++++++++++++++ | 67%
|
|+++++++++++++++++++++++++++++++++++++ | 73%
|
|++++++++++++++++++++++++++++++++++++++++ | 80%
|
|+++++++++++++++++++++++++++++++++++++++++++ | 87%
|
|+++++++++++++++++++++++++++++++++++++++++++++++ | 93%
|
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100%
get_partables(out)
#>
#> Call:
#> NULL
#>
#> Number of parameter tables: 6
#>
#> The modifications/models:
#> add: x3~x4
#> add: x2~x1
#> drop: x3~x1
#> drop: x2~x4
#> drop: x3~~x2
#> original
fit1 <- sem(mod1, dat_path_model)
fit2 <- sem(mod2, dat_path_model)
pt1 <- parameterTable(fit1)
pt2 <- parameterTable(fit2)
to_partables(fit1, fit2)
#>
#> Call:
#> NULL
#>
#> Number of parameter tables: 2
#>
#> The modifications/models:
#> fit1
#> fit2
to_partables(pt1, pt2)
#>
#> Call:
#> NULL
#>
#> Number of parameter tables: 2
#>
#> The modifications/models:
#> pt1
#> pt2