| Get all composite constructs in a model | all_composites |
| Get all common-factor (reflective) constructs in a model | all_factors |
| Select non-interaction constructs from a measurement model | all_non_interactions |
| Converts all contructs of a measurement model, or just a single construct into reflective factors. | as.reflective |
| Converts a contruct of a measurement model into a reflective factor. | as.reflective.construct |
| Converts interaction of a measurement model into a reflective factors. | as.reflective.interaction |
| Converts all contructs of a measurement model, or just a single construct into reflective factors. | as.reflective.measurement_model |
| Specifies inter-item covariances that should be supplied to CBSEM estimation ('estimate_cbsem') or CFA estimation ('estimate_cfa') | associations |
| Return all path bootstraps as a long dataframe. Columns of the dataframes are specified paths and rows are the estimated coefficients for the paths at each bootstrap iteration. | boot_paths_df |
| seminr bootstrap_model Function | bootstrap_model |
| Open Edotor graphViz Website with the preloaded in the Browser | browse_plot |
| Composite construct measurement model specification | composite |
| Function to calculate Akaike weights for IT Criteria | compute_itcriteria_weights |
| Get indicator item names for a construct | construct_items |
| Get the measurement mode of a construct | construct_mode |
| Get the name of a single construct specification | construct_name |
| Get construct names from a model or model component | construct_names |
| Get the user-facing measurement type of a construct | construct_type |
| Measurement functions | constructs |
| Returns R-sq of a dv given correlation matrix of ivs, dv cors <- cbsem_summary$descriptives$correlations$constructs cor_rsq(cors, dv_name = "Value", iv_names = c("Image", "Quality")) | cor_rsq |
| Measurement Instrument for the Corporate Reputation Model | corp_rep_data |
| A Second Measurement Instrument for the Corporate Reputation Model | corp_rep_data2 |
| seminr csem2seminr() function | csem2seminr |
| Cross-tabulates columns of a dataframe into a matrix with NAs for unspecified pairs | df_xtab_matrix |
| Generates the dot code for the measurement model | dot_component_mm |
| Generate a dot graph from various SEMinR models | dot_graph dot_graph.boot_seminr_model dot_graph.cbsem_model dot_graph.cfa_model dot_graph.measurement_model dot_graph.pls_model dot_graph.specified_model dot_graph.structural_model |
| Creates a dot string with a network graph of constructs based on HTMT measures | dot_graph_htmt |
| generates the dot code for a subgraph (per construct) | dot_subcomponent_mm |
| The default template for labeling bootstrapped edges | edge_template_default |
| A minimal template for labeling bootstrapped edges that only shows the bootstrapped mean value | edge_template_minimal |
| Wrap a text in single quotes | esc_node |
| seminr estimate_cbsem() function | estimate_cbsem |
| seminr estimate_cfa() function | estimate_cfa |
| seminr estimate_lavaan_ten_berge() function | estimate_lavaan_ten_berge |
| seminr estimate_pls() function | estimate_pls |
| Performs PLS-MGA to report significance of path differences between two subgroups of data | estimate_pls_mga |
| extract bootstrapped statistics from an edge using a row_index | extract_bootstrapped_values |
| Helper function that applies formatting to each construct | extract_htmt_nodes |
| extracts the constructs and their types from the model | extract_mm_coding |
| gets the mm_edge value (loading, weight) for bootstrapped and regular models | extract_mm_edge_value |
| extract mm edges from model for a given index of all constructs | extract_mm_edges |
| gets the individual nodes and applies formatting | extract_mm_nodes |
| Helper function that applies formatting to each construct | extract_sm_nodes |
| Helps to render a node label for endogenous variables | format_endo_node_label |
| Helps to render a node label for exogenous variables | format_exo_node_label |
| seminr fSquared Function | fSquared |
| Gets the optimal size for construct elements in the plot | get_construct_element_size |
| Gets the optimal size for manifest elements in the plot | get_manifest_element_size |
| individual styles for measurement model edges | get_mm_edge_style |
| Get a string to insert into a node specification using the themed shape | get_mm_node_shape |
| get global measurement model node style | get_mm_node_style |
| Get a string to insert into a node specification using the themed shape | get_sm_node_shape |
| Formats the style of the structural model edges | get_value_dependent_mm_edge_style |
| Formats the style of the structural model edges | get_value_dependent_sm_edge_style |
| higher_composite | higher_composite |
| higher_reflective | higher_reflective |
| Measurement Instrument for the Influencer Model | influencer_data |
| Interaction function | interaction_term |
| Tests whether the i_th construct is endogenous or not | is_only_endogenous |
| Specifies pair of items, or sets of items, that should covary. Used to specify error covariances for 'associations'. | item_errors |
| Function to clean data of omitted values by mean replacement | mean_replacement |
| Measurement Instrument for the Mobile Phone Industry | mobi |
| Outer weighting scheme functions to estimate construct weighting. | correlation_weights mode_A mode_A, |
| Outer weighting scheme functions to estimate construct weighting. | mode_B mode_B, regression_weights |
| Outer weighting scheme functions to estimate construct weighting. | mode_plsc |
| Multi-items measurement model specification | multi_items |
| The default template for labeling endogenous construct nodes | node_endo_template_default |
| The default template for labeling exogenous construct nodes | node_exo_template_default |
| 'orthogonal' creates interaction measurement items by using the orthogonalized approach wherein | orthogonal |
| Inner weighting scheme functions to estimate inner paths matrix | path_factorial |
| Inner weighting scheme functions to estimate inner paths matrix | path_weighting |
| Plots a network graph of constructs based on HTMT measures | plot_htmt |
| Function for plotting interaction plot for moderated PLS or CBSEM model | plot_interaction |
| Function for plotting the measurement model reliability metrics of a PLS model | plot.reliability_table |
| Plot various SEMinR models | plot.seminr_model |
| seminr PLSc Function | PLSc |
| Predictive Scheme | predict_DA |
| Predictive Scheme | predict_EA |
| Predict_pls performs either k-fold or LOOCV on a SEMinR PLS model and generates predictions | predict_pls |
| Predict method for SEMinR PLS models | predict.seminr_model |
| Summary function for PLS-MGA | print.seminr_pls_mga |
| 'product_indicator' creates interaction measurement items by scaled product indicator approach. | product_indicator |
| Quadratic term function | quadratic_term |
| Reflective construct measurement model specification | reflective |
| Structural specification functions for seminr package | paths relationships |
| Function to report how missing data was handled and how much was missing. | report_missing |
| Functions for reporting the Path Coefficients and R2 of endogenous constructs and for generating a scatterplot matrix of construct scores. | plot_scores report_paths |
| Reruns a previously specified seminr model/analysis | rerun |
| Reruns a previously specified seminr PLS model | rerun.pls_model |
| seminr rho_A Function | rho_A |
| seminr rhoC_AVE() function | rhoC_AVE |
| Saves a SEMinR model plot to file | save_plot |
| A theme function for a basic b/w theme | seminr_theme_academic |
| Create a theme for a seminr graph visualization | seminr_theme_create |
| The theme function for an inverted theme on black background. | seminr_theme_dark |
| Get and set the active theme | seminr_theme_get seminr_theme_set |
| A colored theme | seminr_theme_default seminr_theme_smart |
| seminr simplePLS Function | simplePLS |
| Single-item measurement model specification | single_item |
| Function for plotting a slope analysis for an interaction in a PLS model | slope_analysis |
| seminr specific effect significance function | specific_effect_significance |
| seminr specify_model() function | specify_model |
| Standardize (scale) a matrix/df and report interpretable errors | standardize_safely |
| seminr total indirect confidence intervals function | total_indirect_ci |
| Creates an interaction measurement item using a two-stage approach. The two-stage procedure for both PLS and CBSEM models estimates construct scores in the first stage, and uses them to produce a single-item product item for the interaction term in the second stage. For a PLS model, the first stage uses PLS to compute construct scores. For a CBSEM model, the first stage uses a CFA to produce ten Berge construct scores. | two_stage |
| Outer weighting scheme functions to estimate construct weighting. | unit_weights |
