Man pages for gastonstat/plspm2
Tools for Partial Least Squares Path Modeling
| alpha | Cronbach's alpha |
| arizona | Arizona vegetation dataset |
| cereals | Cereals datset |
| check_args | Check arguments for 'plspm' and 'plspm.fit' |
| check_blocks | Check well defined blocks |
| check_boot | Check bootstrap options |
| check_data | Check Data |
| check_maxiter | Check maximum number of iterations |
| check_model | Check congruence between inner and outer models |
| check_modes | Check modes |
| check_path | Check path matrix |
| check_plscomp | Check vector of PLS components (for non-metric plspm) |
| check_scaling | Check types of measurement scales and metric |
| check_scheme | Check scheme |
| check_specs | Check specifications of PLS-PM algorithm |
| check_tol | Check tolerance threshold |
| college | College datasets |
| dummy.G | Dummy by Giorgio |
| futbol | Futbol dataset from Spain-England-Italy |
| get_alpha | Calculate Cronbach's alpha |
| get_ave | Calculate AVE (Average Variance Extracted) |
| get_boots | Performs bootstrap validation in 'plspm' |
| get_boot_stats | Get data frame with bootstrap statistics |
| get_data_scaled | Scaling data outside 'plspm' |
| get_dummies | Dummy matrices for categorical manifest variables |
| get_dummy | Non-Metric Dummy |
| get_effects | Path coefficient effects for 'plspm' |
| get_generals | Get general parameters |
| get_gof | Goodness-of-fit for 'plspm' |
| get_GQI | Group Quality Index |
| get_inner_summary | Inner summary assessment |
| get_locals_test | Local groups comparison test |
| get_manifests | Building data matrix with manifest variables |
| get_metric | Type of metric based on scaling measurement |
| get_nom_scale | Non-Metric Nominal Scale |
| get_numerics | Transform factors in MV into numeric |
| get_num_scale | Non-Metric Numerical Scale |
| get_ord_scale | Non-Metric Ordinal Scale |
| get_paths | Calculate path coefficients for 'plspm' |
| get_path_scheme | Calculate inner weighting path scheme |
| get_PLSR | Internal PLS regression (full data) |
| get_plsr1 | PLS regression for 'plspm' |
| get_PLSRdoubleQ | get_PLSRdoubleQ |
| get_PLSR_NA | Internal PLS regression with missing values |
| get_rank | Rank of a non-metric variable |
| get_rho | Calculate Dillon-Goldstein's rho |
| get_scores | Calculate Latent Variable Scores |
| get_treated_data | Apply corresponding treatment to MV |
| get_unidim | Unidimensionality of reflective blocks |
| get_weights | Outer Weights |
| get_weights_nonmetric | Outer Weights Non-Metric Data |
| innerplot | Plot inner model |
| is_missing | Presence of missing values |
| it.reb | Iterative steps of Response-Based Unit Segmentation (REBUS) |
| local.models | PLS-PM for global and local models |
| mobile | ECSI Mobile Phone Provider dataset |
| normalize | Normalize a vector |
| offense | Offense dataset |
| orange | Orange Juice dataset |
| outerplot | Plot outer model |
| plot.plspm | Plots for PLS Path Models |
| plspm | PLS-PM: Partial Least Squares Path Modeling |
| plspm.fit | Basic results for Partial Least Squares Path Modeling |
| plspm.groups | Two Groups Comparison in PLS-PM |
| quantiplot | Quantification Plot |
| rebus.pls | Response Based Unit Segmentation (REBUS) |
| rebus.test | Permutation Test for REBUS Multi-Group Comparison |
| rescale | Rescale Latent Variable Scores |
| res.clus | Clustering on communality and structural residuals |
| rho | Dillon-Goldstein's rho |
| russa | Russett A |
| russb | Russett B |
| russett | Russett dataset |
| satisfaction | Satisfaction dataset |
| simdata | Simulated data for REBUS with two groups |
| spainfoot | Spanish football dataset |
| technology | Technology data set |
| test_dataset | Test Data Set Availibility |
| test_factors | Test presence of factors |
| test_manifest_scaling | Test scaling of selected manifest variables |
| test_null_weights | Test outer weights convergence within specified maxiter |
| unidim | Unidimensionality of blocks |
| wines | Wines dataset |
