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| radiant-package | radiant |
| ca_the_table | Function to calculate the PW and IW table for conjoint |
| changedata | Change data |
| city | City distances |
| compare_means | Compare means for two or more variables |
| compare_props | Compare proportions across groups |
| computer | Perceptions of computer (re)sellers |
| conjoint | Conjoint analysis |
| conjoint_profiles | Create fractional factorial design for conjoint analysis |
| correlation | Calculate correlations for two or more variables |
| cross_tabs | Evaluate associations between categorical variables |
| diamonds | Diamond prices |
| ff_design | Function to generate a fractional factorial design |
| full_factor | Factor analysis (PCA) |
| getdata | Get data for analysis functions |
| glm_reg | Generalized linear models (GLM) |
| hier_clus | Hierarchical cluster analysis |
| kmeans_clus | K-means cluster analysis |
| kurtosi | Exporting the kurtosi function from the psych package |
| mac_launcher | Create a launcher for Mac (.command) |
| mds | (Dis)similarity based brand maps (MDS) |
| mergedata | Merge datasets using dplyr's join functions |
| mp3 | Conjoint data for MP3 players |
| newspaper | Newspaper readership |
| plot.compare_means | Plot method for the compare_means function |
| plot.compare_props | Plot method for the compare_props function |
| plot.conjoint | Plot method for the conjoint function |
| plot.correlation | Plot method for the correlation function |
| plot.cross_tabs | Plot method for the cross_tabs function |
| plot.full_factor | Plot method for the full_factor function |
| plot.glm_predict | Plot method for the predict.glm_reg function |
| plot.glm_reg | Plot method for the glm_reg function |
| plot.hier_clus | Plot method for the hier_clus function |
| plot.kmeans_clus | Plot method for kmeans_clus |
| plot.mds | Plot method for the mds function |
| plot.pmap | Plot method for the pmap function |
| plot.pre_factor | Plot method for the pre_factor function |
| plot.regression | Plot method for the regression function |
| plot.reg_predict | Plot method for the predict.regression function |
| plot.single_mean | Plot method for the single_mean function |
| plot.single_prop | Plot method for the single_prop function |
| pmap | Attribute based brand maps |
| predict.glm_reg | Predict method for the glm_reg function |
| predict.regression | Predict method for the regression function |
| pre_factor | Evaluate if data are appropriate for PCA / Factor analysis |
| radiant | radiant |
| regression | Linear regression using OLS |
| rndnames | 100 random names |
| sample_size | Sample size calculation |
| sampling | Simple random sampling |
| save_factors | Save factor scores to active dataset |
| save_glm_resid | Save residuals generated in the glm_reg function |
| save_membership | Add a cluster membership variable to the active dataset |
| save_reg_resid | Save regression residuals |
| set_class | Alias used to set the class for analysis function return |
| shopping | Shopping attitudes |
| sig_stars | Add stars '***' to a data.frame (from broom's 'tidy' function) based on p.values |
| single_mean | Compare a sample mean to a population mean |
| single_prop | Compare a sample proportion to a population proportion |
| skew | Exporting the skew function from the psych package |
| sshh | Hide warnings and messages and return invisible |
| sshhr | Hide warnings and messages and return result |
| summary.compare_means | Summary method for the compare_means function |
| summary.compare_props | Summary method for the compare_props function |
| summary.conjoint | Summary method for the conjoint function |
| summary.conjoint_profiles | Summary method for the conjoint_profiles function |
| summary.correlation | Summary method for the correlation function |
| summary.cross_tabs | Summary method for the cross_tabs function |
| summary.full_factor | Summary method for the full_factor function |
| summary.glm_reg | Summary method for the glm_reg function |
| summary.hier_clus | Summary method for the hier_clus function |
| summary.kmeans_clus | Summary method for kmeans_clus |
| summary.mds | Summary method for the mds function |
| summary.pmap | Summary method for the pmap function |
| summary.pre_factor | Summary method for the pre_factor function |
| summary.regression | Summary method for the regression function |
| summary.sample_size | Summary method for the sample_size function |
| summary.sampling | Summary method for the sampling function |
| summary.single_mean | Summary method for the single_mean function |
| summary.single_prop | Summary method for the single_prop function |
| test_check | Add interaction terms to list of test variables if needed |
| titanic | Survival data for the Titanic |
| titanic_pred | Predict survival |
| toothpaste | Toothpaste attitudes |
| var_check | Check if main effects for all interaction effects are included in the model If ':' is used to select a range _indep_var_ is updated |
| visualize | Visualize data using ggplot2 <URL: http://docs.ggplot2.org/current/> |
| win_launcher | Create a launcher for Windows (.bat) |