Paper

.Rbuildignore

@@ -16,3 +16,4 @@
 ^references.csv
 ^references.yml
 ^R/library-references\.R$
+^\.github$

.github/workflows/rcmdcheck.yml

@@ -0,0 +1,99 @@
+on:
+  push:
+    branches:
+      - '**'
+      - '!*_noci'
+  pull_request:
+    branches:
+      - '**'
+      - '!*_noci'
+
+name: R-CMD-check
+
+jobs:
+  R-CMD-check:
+    runs-on: ${{ matrix.config.os }}
+
+    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          #- {os: windows-latest, r: 'release'}
+          - {os: macOS-latest, r: 'release'}
+          - {os: ubuntu-20.04, r: 'release', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
+          - {os: ubuntu-20.04, r: 'devel', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
+
+    env:
+      R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
+      RSPM: ${{ matrix.config.rspm }}
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+
+    steps:
+      - uses: actions/checkout@v2
+
+      - uses: r-lib/actions/setup-r@v1
+        with:
+          r-version: ${{ matrix.config.r }}
+
+      # pandoc to check markdown files
+      - uses: r-lib/actions/setup-pandoc@v1
+
+      - name: Query dependencies
+        run: |
+          install.packages('remotes')
+          saveRDS(remotes::dev_package_deps(dependencies = TRUE), ".github/depends.Rds", version = 2)
+          writeLines(sprintf("R-%i.%i", getRversion()$major, getRversion()$minor), ".github/R-version")
+        shell: Rscript {0}
+
+      - name: Cache R packages
+        if: runner.os != 'Windows'
+        uses: actions/cache@v2
+        with:
+          path: ${{ env.R_LIBS_USER }}
+          key: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-${{ hashFiles('.github/depends.Rds') }}
+          restore-keys: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-
+
+      - name: Install system dependencies
+        if: runner.os == 'Linux'
+        run: |
+          while read -r cmd
+          do
+            eval sudo $cmd
+          done < <(Rscript -e 'writeLines(remotes::system_requirements("ubuntu", "20.04"))')
+
+      - name: Install dependencies
+        run: |
+          remotes::install_deps(dependencies = TRUE)
+          remotes::install_cran("rcmdcheck")
+        shell: Rscript {0}
+
+      - name: Check
+        if: runner.os != 'Windows'
+        env:
+          _R_CHECK_CRAN_INCOMING_REMOTE_: false
+        run: rcmdcheck::rcmdcheck(args = c("--no-manual", "--as-cran"), error_on = "warning", check_dir = "check")
+        shell: Rscript {0}
+
+      - name: BuildWin
+        if: runner.os == 'Windows'
+        env:
+          _R_CHECK_CRAN_INCOMING_REMOTE_: false
+        run: R CMD INSTALL --preclean --no-multiarch --with-keep.source seminr
+        shell: bash
+
+      - name: TestWin
+        if: runner.os == 'Windows'
+        env:
+          _R_CHECK_CRAN_INCOMING_REMOTE_: false
+        run: devtools::test()
+        shell: Rscript {0}
+
+
+      - name: Upload check results
+        if: failure()
+        uses: actions/upload-artifact@main
+        with:
+          name: ${{ runner.os }}-r${{ matrix.config.r }}-results
+          path: check

CHANGELOG.md

@@ -5,6 +5,43 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project largely adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [2.0.1] - 2021-03-21
+
+### [2.0.1] Changed
+
+- Updated the namespace to exclude MASS
+- Removed the simulation of a fixture in the test-plsc-fsquared file
+
+## [2.0.0] - 2021-02-21
+
+### [2.0.0] Added
+
+- S3 plot() method for visualizing all SEMinR models - CFA, CBSEM, PLS, PLSc
+
+
+## [1.2.0] - 2020-12-31
+
+### [1.2.0] Added
+
+- A new feature to plot interaction plots
+- Demo files for PLS Primer in R Workbook
+- PLSpredict feature
+- total paths and indirect effects
+- New visualization for reliability
+- Cronbachs alpha to reliability
+- new datasets = corp_rep_data2 and corp_rep_data
+- new method for calculating AIC and BIC
+- new demonstration files for an accompanying textbook
+
+### [1.2.0] Changed
+
+- Changed output of summary() to generate standardized matrices and lists with an S3 print method
+- Changed HOC to combine first and second stage results for outer loadings and outer weights
+- Changed estimate_bootstrap() to process bootstrap matrix in a way that is naive to differences in matrix layouts
+
+###[1.2.0] Removed
+- old test fixtures for V 3.5.X (deprecated by R)
+
 ## [1.1.0] - 2020-07-01
 
 ### [1.1.0] Added

DESCRIPTION

@@ -1,23 +1,40 @@
 Package: seminr
 Type: Package
 Title: Domain-Specific Language for Building and Estimating Structural Equation Models
-Version: 1.1.0
-Date: 2020-07-23
+Version: 2.0.1
+Date: 2021-03-21
 Authors@R: c(person("Soumya", "Ray", email = "[email protected]", role = c("aut", "ths")),
              person("Nicholas Patrick", "Danks", email = "[email protected]", role = c("aut","cre")),
-             person("Juan Manuel Velasquez", "Estrada", role = "aut"),
-             person("James", "Uanhoro", role = "ctr", email = "[email protected]"),
-             person("Arturo Heynar Cano", "Bejar", role = "ctr", email = "[email protected]"))
+             person("André", "Calero Valdez", role = "aut", email = "[email protected]"),
+             person("Juan Manuel Velasquez", "Estrada", role = "ctb"),
+             person("James", "Uanhoro", role = "ctb", email = "[email protected]"),
+             person("Johannes", "Nakayama", role = "ctb", email = "[email protected]"),
+             person("Lilian", "Koyan", role = "ctb", email = "[email protected]"),
+             person("Laura", "Burbach", role = "ctb", email = "[email protected]"),
+             person("Arturo Heynar", "Cano Bejar", role = "ctb", email = "[email protected]"),
+             person("Susanne", "Adler", role = "ctb", email = "[email protected]")
+            )
 Description: A powerful, easy to syntax for specifying and estimating complex 
     Structural Equation Models. Models can be estimated using Partial 
     Least Squares Path Modeling or Covariance-Based Structural Equation 
     Modeling or covariance based Confirmatory Factor Analysis. 
 Imports:
-    parallel, lavaan, MASS
+    parallel,
+    lavaan,
+    glue
 License: GPL-3
-Depends: R (>= 3.1.0)
+Depends: R (>= 3.5.0)
 LazyData: TRUE
-RoxygenNote: 7.1.0
-Suggests: knitr, testthat, rmarkdown
+RoxygenNote: 7.1.1
+Suggests: 
+    knitr,
+    testthat,
+    rmarkdown,
+    DiagrammeR (>= 1.0.6),
+    DiagrammeRsvg (>= 0.1),
+    rsvg (>= 2.1),
+    webp,
+    semPlot,
+    vdiffr
 VignetteBuilder: knitr
 Encoding: UTF-8

NAMESPACE

@@ -3,46 +3,91 @@
 S3method(as.reflective,construct)
 S3method(as.reflective,interaction)
 S3method(as.reflective,measurement_model)
+S3method(dot_graph,boot_seminr_model)
+S3method(dot_graph,cbsem_model)
+S3method(dot_graph,cfa_model)
+S3method(dot_graph,default)
+S3method(dot_graph,measurement_model)
+S3method(dot_graph,pls_model)
+S3method(dot_graph,specified_model)
+S3method(dot_graph,structural_model)
+S3method(plot,reliability_table)
+S3method(plot,seminr_model)
+S3method(plot,summary.predict_pls_model)
+S3method(predict,seminr_model)
+S3method(print,list_output)
 S3method(print,measurement_model_evaluation.seminr_model)
+S3method(print,seminr_theme)
 S3method(print,summary.boot_seminr_model)
 S3method(print,summary.cbsem_model)
 S3method(print,summary.cfa_model)
+S3method(print,summary.predict_pls_model)
 S3method(print,summary.seminr_model)
 S3method(print,table_output)
 S3method(summary,boot_seminr_model)
 S3method(summary,cbsem_model)
 S3method(summary,cfa_model)
+S3method(summary,predict_pls_model)
 S3method(summary,seminr_model)
 export(PLSc)
 export(as.reflective)
 export(associations)
 export(bootstrap_model)
+export(browse_plot)
+export(check_test_plot)
 export(composite)
+export(compute_itcriteria_weights)
 export(confidence_interval)
 export(constructs)
 export(correlation_weights)
+export(csem2seminr)
+export(dot_graph)
+export(dot_graph_htmt)
+export(edge_template_default)
+export(edge_template_minimal)
 export(estimate_cbsem)
 export(estimate_cfa)
 export(estimate_lavaan_ten_berge)
 export(estimate_pls)
 export(fSquared)
+export(get_theme_doc)
 export(higher_composite)
 export(interaction_term)
 export(item_errors)
+export(last_seminr_plot)
+export(mean_replacement)
 export(mode_A)
 export(mode_B)
 export(multi_items)
+export(node_endo_template_default)
+export(node_exo_template_default)
 export(orthogonal)
 export(path_factorial)
 export(path_weighting)
 export(paths)
+export(plot_htmt)
 export(plot_scores)
+export(predict_DA)
+export(predict_EA)
+export(predict_pls)
 export(product_indicator)
 export(reflective)
 export(regression_weights)
 export(relationships)
 export(report_paths)
 export(rho_A)
+export(save_plot)
+export(seminr_theme_create)
+export(seminr_theme_dark)
+export(seminr_theme_default)
+export(seminr_theme_get)
+export(seminr_theme_old)
+export(seminr_theme_set)
+export(seminr_theme_smart)
+export(set_last_seminr_plot)
 export(simplePLS)
 export(single_item)
+export(slope_analysis)
+export(specify_model)
+export(total_indirect_ci)
 export(two_stage)

R/clean_data.R

@@ -0,0 +1,24 @@
+#' Function to clean data of ommitted values by mean replacement
+#'
+#' The \code{seminr} package provides a natural syntax for researchers to describe PLS
+#' structural equation models.
+#'
+#' \code{mean_replacement} provides the verb for replacing all ommitted values (NA only) in the dataset with
+#' the mean of the variable.
+#'
+#' @param data A dataset to be used for estimating a SEMinR model
+#'
+#' @usage
+#' mean_replacement(data)
+#'
+#' @references Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2017). A Primer on Partial Least Squares
+#'  Structural Equation Modeling (PLS-SEM), 2nd Ed., Sage: Thousand Oaks.
+#'
+#' @export
+mean_replacement <- function(data) {
+  for (i in 1:ncol(data)) {
+    colmean <- mean(data[,i][!(is.na(data[,i]))])
+    data[,i][is.na(data[,i])] <- colmean
+  }
+  return(data)
+}

R/compute_metrics.R

@@ -31,7 +31,8 @@ cor_rsq <- function(cor_matrix, dv_name, iv_names) {
 cor_vifs <- function(cor_matrix, iv_names) {
   sapply(iv_names, function(iv) {
     rsq_j <- cor_rsq(cor_matrix, dv_name = iv, iv_names = iv_names[iv_names != iv])
-    1/(1 - rsq_j)
+    ret <- as.matrix(1/(1 - rsq_j))
+    convert_to_table_output(ret)
   }, USE.NAMES = TRUE)
 }
 
@@ -57,6 +58,24 @@ AIC_func <- function(rsq, pk, N, construct_score){
   2*(pk+1)+N*log(SSerrk/N)
 }
 
+return_AIC_BIC <- function(i, seminr_model) {
+  antecedents <- antecedents_of(outcome = i, smMatrix = seminr_model$smMatrix)
+  pk <- length(antecedents)
+  rsq <- cor_rsq(stats::cor(seminr_model$construct_scores), dv_name = i, iv_names = antecedents)
+  N <- nrow(seminr_model$construct_scores)
+  construct_score <- seminr_model$construct_scores[,i]
+  construct_AIC <- AIC_func(rsq,pk,N,construct_score)
+  construct_BIC <- BIC_func(rsq,pk,N,construct_score)
+  return(c(construct_AIC, construct_BIC))
+}
+
+calculate_itcriteria <- function(seminr_model) {
+  endogenous <- all_endogenous(seminr_model$smMatrix)
+  ret <- sapply(endogenous, return_AIC_BIC, seminr_model = seminr_model)
+  rownames(ret) <- c("AIC", "BIC")
+  convert_to_table_output(ret)
+}
+
 # Computes Henseler's rhoA
 compute_construct_rhoA <- function(weights, mmMatrix, construct, obsData) {
   # get the weights for the construct
@@ -75,3 +94,15 @@ compute_construct_rhoA <- function(weights, mmMatrix, construct, obsData) {
   return((t(w) %*% w)^2 * ((t(w) %*% (S) %*% w)/(t(w) %*% AAnondiag %*% w)))
 }
 
+#' Function to calculate Akaike weights for IT Criteria
+#'
+#' @param vector_of_itcriteria This argument is a vector consisting of the IT criterion estimated
+#'   value for each model.
+#'
+#' @export
+compute_itcriteria_weights <- function(vector_of_itcriteria) {
+  delta_itcriteria <- vector_of_itcriteria - min(vector_of_itcriteria)
+  rel_likelihoods <- exp(-0.5 * delta_itcriteria)
+  sum_likelihoods <- sum(rel_likelihoods, na.rm = TRUE)
+  return(rel_likelihoods / sum_likelihoods)
+}