semcoa is an R package to conduct the Composite Overfit Analysis (COA)
framework for Structural Equation Models (SEM), and to then report and
plot results.
# install.packages("devtools")
devtools::install_github("sem-in-r/semcoa")Please install following packages:
- seminr (composite model estimation)
- rpart (decision tree)
- maptools (plotting labels)
Run all tests using ‘Test Package’ of RStudio, or run specific test
files using devtools:
test_active_file("tests/testthat/test-integration-coa.R")
test_active_file("tests/testthat/test-unit-dtree.R")Look at demos folder for full examples. The following is a brief look at the code and output.
First, let’s setup our composite construct-based model using the seminr package for specifying structural equation models.
#> Generating the seminr model
#> All 216 observations are valid.
Now, we can conduct our Composite Overfit Analysis (COA). We start by
loading the semcoa library:
library(semcoa)
library(rpart)
library(maptools)
#> Loading required package: sp
#> Checking rgeos availability: FALSE
#> Note: when rgeos is not available, polygon geometry computations in maptools depend on gpclib,
#> which has a restricted licence. It is disabled by default;
#> to enable gpclib, type gpclibPermit()Now we can analyze our estimated composite SEM model using COA:
utaut_overfit <- coa(pls_model = utaut_model,
focal_construct = "BI",
params = c("path_coef", "rSquared"))
#> Computing predictive deviance
#> Generating Deviance Tree
#> Identifying Unstable PathsWe can visualize our predictive deviant cases and groups as follows:
plot_pd(utaut_overfit)
# Inspect all the names of the groups
names(utaut_overfit$dtree$deviant_groups)
#> [1] "a" "b" "c" "d" "e"And we can inspect more details about the groups by seeing the defining descriptive characteristics of each group.
# Get descriptive characteristics of one of the groups
group_rules("b", utaut_overfit$dtree)
#> BI < -0.53
#> -2.45 <= FC < -0.93
#> HAB < 1.00
#> -1.06 <= PEAnd finally, we can examine unstable paths of any of our groups.
unstable <- unstable_params(analysis = utaut_overfit)
#> Identifying Unstable Paths
unstable$group_diffs$b
#> $group
#> [1] 12 71 99
#>
#> $param_diffs
#> $param_diffs$path_coef
#> PE EE SI FC HM PV HAB Exp Age Gender BI
#> PE 0 0 0 0 0 0 0 0 0 0 -0.018426546
#> EE 0 0 0 0 0 0 0 0 0 0 -0.005368748
#> SI 0 0 0 0 0 0 0 0 0 0 0.004796548
#> FC 0 0 0 0 0 0 0 0 0 0 0.032766535
#> HM 0 0 0 0 0 0 0 0 0 0 -0.022661261
#> PV 0 0 0 0 0 0 0 0 0 0 0.033025676
#> HAB 0 0 0 0 0 0 0 0 0 0 0.004836042
#> Exp 0 0 0 0 0 0 0 0 0 0 -0.001911413
#> Age 0 0 0 0 0 0 0 0 0 0 0.010783469
#> Gender 0 0 0 0 0 0 0 0 0 0 -0.009425882
#> BI 0 0 0 0 0 0 0 0 0 0 0.000000000- Create
all_groups_*version ofgroup_rulesand other related posthoc methods that operate on individual groups - Create
summaryandprintfunctions for COA object (can useall_groups_*functions) - Reposition labels on
plot_pd() - Create
group_competesfunction that reports competes for all rules, not just rule at group root
group_rulessubroutines can reuse data structures
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