| AIC.beezdemand_hurdle | AIC for Hurdle Demand Model |
| annotation_logticks2 | annotation_logticks2 |
| anova.beezdemand_hurdle | ANOVA Method for Hurdle Demand Models |
| anova.beezdemand_nlme | ANOVA Method for NLME Demand Models |
| apt | Example alcohol purchase task data |
| apt_full | Full alcohol purchase task dataset |
| augment.beezdemand_fixed | Augment a beezdemand_fixed Model with Fitted Values and Residuals |
| augment.beezdemand_hurdle | Augment a beezdemand_hurdle Model with Fitted Values and Residuals |
| augment.beezdemand_nlme | Augment a beezdemand_nlme Model with Fitted Values and Residuals |
| beezdemand_descriptive_methods | S3 Methods for beezdemand_descriptive Objects |
| beezdemand_empirical_methods | S3 Methods for beezdemand_empirical Objects |
| BIC.beezdemand_hurdle | BIC for Hurdle Demand Model |
| calculate_amplitude_persistence | Calculate Amplitude and Persistence |
| calc_group_metrics | Calculate Group-Level Demand Metrics |
| calc_observed_pmax_omax | Calculate Observed Pmax/Omax Grouped by ID |
| calc_omax_pmax | Calculate Omax and Pmax for Demand Curves |
| cannabisCigarettes | Cannabis/cigarette cross-price responses |
| ChangeData | ChangeData |
| CheckCols | Check Column Names |
| CheckUnsystematic | Systematic Purchase Task Data Checker |
| check_demand_model | Check Demand Model Diagnostics |
| check_demand_model.beezdemand_fixed | Check Demand Model Diagnostics |
| check_demand_model.beezdemand_hurdle | Check Demand Model Diagnostics |
| check_demand_model.beezdemand_nlme | Check Demand Model Diagnostics |
| check_systematic_cp | Check Cross-Price Data for Unsystematic Responding |
| check_systematic_demand | Check Demand Data for Unsystematic Responding |
| check_unsystematic_cp | Check for Unsystematic Patterns in Cross-Price Data |
| coef-methods | Extract Coefficients from Cross-Price Demand Models |
| coef.beezdemand_fixed | Extract Coefficients from Fixed-Effect Demand Fit |
| coef.beezdemand_hurdle | Extract Coefficients from Hurdle Demand Model |
| coef.beezdemand_nlme | Extract Coefficients from a beezdemand_nlme Model |
| coef.cp_model_lm | Extract Coefficients from Cross-Price Demand Models |
| coef.cp_model_lmer | Extract Coefficients from Cross-Price Demand Models |
| coef.cp_model_nls | Extract Coefficients from Cross-Price Demand Models |
| compare_hurdle_models | Compare Nested Hurdle Demand Models |
| compare_models | Compare Demand Models |
| confint.beezdemand_fixed | Confidence Intervals for Fixed-Effect Demand Model Parameters |
| confint.beezdemand_hurdle | Confidence Intervals for Hurdle Demand Model Parameters |
| confint.beezdemand_nlme | Confidence Intervals for Mixed-Effects Demand Model Parameters |
| confint.cp_model_nls | Confidence Intervals for Cross-Price NLS Model Parameters |
| cp | Example crossâprice dataset |
| cp_posthoc_intercepts | Run pairwise intercept comparisons for cross-price demand model |
| cp_posthoc_slopes | Run pairwise slope comparisons for cross-price demand model |
| etm | Example Experimental Tobacco Marketplace data |
| extract_coefficients | Extract All Coefficient Types from Cross-Price Demand Models |
| ExtraF | ExtraF |
| FitCurves | FitCurves |
| FitMeanCurves | Fit Pooled/Mean Curves |
| fit_cp_linear | Fit a Linear Cross-Price Demand Model |
| fit_cp_linear.default | Fit a Linear Cross-Price Demand Model |
| fit_cp_linear.mixed | Fit a Linear Cross-Price Demand Model |
| fit_cp_nls | Fit cross-price demand with NLS (+ robust fallbacks) |
| fit_demand_fixed | Fit Fixed-Effect Demand Curves |
| fit_demand_hurdle | Fit Two-Part Mixed Effects Hurdle Demand Model |
| fit_demand_mixed | Fit Nonlinear Mixed-Effects Demand Model |
| fixed-demand | Fixed-Effect Demand Curve Fitting |
| fixef.beezdemand_nlme | Extract Fixed Effects from a beezdemand_nlme Model |
| fixef.cp_model_lmer | Extract Fixed Effects from Mixed-Effects Cross-Price Model |
| GetAnalyticPmax | Get pmax |
| GetAnalyticPmaxFallback | Analytic Pmax Fallback |
| GetDescriptives | Get Purchase Task Descriptive Summary |
| GetEmpirical | GetEmpirical |
| GetK | Get K |
| GetSharedK | Get Shared K |
| GetValsForSim | Get Values for SimulateDemand |
| get_demand_comparisons | Get Pairwise Comparisons for Demand Parameters |
| get_demand_param_emms | Get Estimated Marginal Means for Demand Parameters |
| get_demand_param_trends | Get Trends (Slopes) of Demand Parameters with respect to Continuous Covariates |
| get_descriptive_summary | Calculate Descriptive Statistics by Price |
| get_empirical_measures | Calculate Empirical Demand Measures |
| get_hurdle_param_summary | Get Hurdle Model Parameter Summary |
| get_individual_coefficients | Calculate Individual-Level Predicted Coefficients from beezdemand_nlme Model |
| get_k | Calculate K Scaling Parameter for Demand Curve Fitting |
| get_observed_demand_param_emms | Get Estimated Marginal Means for Observed Factor Combinations |
| get_subject_pars | Get Subject-Specific Parameters |
| glance.beezdemand_fixed | Glance Method for beezdemand_fixed |
| glance.beezdemand_hurdle | Glance at a beezdemand_hurdle Model |
| glance.beezdemand_nlme | Glance method for beezdemand_nlme |
| glance.beezdemand_systematicity | Glance Method for beezdemand_systematicity |
| glance.cp_model_lm | Get model summaries from a linear cross-price model |
| glance.cp_model_lmer | Get model summaries from a mixed-effects cross-price model |
| glance.cp_model_nls | Get model summaries from a cross-price model |
| ko | Example nonhuman demand data with drug and dose |
| lambertW | Lambert W |
| ll4 | Log-Logistic Transformation (LL4-like) |
| ll4_inv | Inverse Log-Logistic Transformation (Inverse LL4-like) |
| logLik.beezdemand_hurdle | Extract Log-Likelihood from Hurdle Demand Model |
| lowNicClean | Low-nicotine cigarette purchase task |
| ongoingETM | Experimental Tobacco Marketplace (ETM) data |
| palette_beezdemand | beezdemand Color Palette |
| pivot_demand_data | Reshape Demand Data Between Wide and Long Formats |
| plot-theme | beezdemand Plot Theme and Color Palette |
| plot.beezdemand_descriptive | S3 Methods for beezdemand_descriptive Objects |
| plot.beezdemand_empirical | S3 Methods for beezdemand_empirical Objects |
| plot.beezdemand_fixed | Plot Method for beezdemand_fixed |
| plot.beezdemand_hurdle | Plot Demand Curves from Hurdle Demand Model |
| plot.beezdemand_nlme | Plot Method for beezdemand_nlme Objects |
| plot.cp_model_lm | Plot Method for Linear Cross-Price Demand Models |
| plot.cp_model_lmer | Plot Method for Mixed-Effects Cross-Price Demand Models |
| plot.cp_model_nls | Plot a Cross-Price Demand Model (Nonlinear) |
| PlotCurve | Plot Curve |
| PlotCurves | Plot Curves |
| plot_qq | Plot Random Effects Q-Q |
| plot_qq.beezdemand_hurdle | Plot Random Effects Q-Q |
| plot_qq.beezdemand_nlme | Plot Random Effects Q-Q |
| plot_residuals | Plot Residual Diagnostics |
| plot_subject | Plot Demand Curve for a Single Subject |
| predict.beezdemand_fixed | Predict Method for beezdemand_fixed |
| predict.beezdemand_hurdle | Predict Method for Hurdle Demand Models |
| predict.beezdemand_nlme | Predict Method for beezdemand_nlme Objects |
| predict.cp_model_lm | Predict method for cp_model_lm objects. |
| predict.cp_model_lmer | Predict from a Mixed-Effects Cross-Price Demand Model |
| predict.cp_model_nls | Predict from a Cross-Price Demand Model (Nonlinear) |
| print.anova.beezdemand_hurdle | Print Method for ANOVA Comparisons |
| print.beezdemand_comparison | Print method for beezdemand_comparison objects |
| print.beezdemand_descriptive | S3 Methods for beezdemand_descriptive Objects |
| print.beezdemand_diagnostics | Print Method for Model Diagnostics |
| print.beezdemand_empirical | S3 Methods for beezdemand_empirical Objects |
| print.beezdemand_fixed | Print Method for beezdemand_fixed |
| print.beezdemand_hurdle | Print Method for Hurdle Demand Model |
| print.beezdemand_model_comparison | Print Method for Model Comparison |
| print.beezdemand_nlme | Print Method for beezdemand_nlme Objects |
| print.beezdemand_summary | Print Method for beezdemand Summary Objects |
| print.beezdemand_systematicity | Print Method for beezdemand_systematicity |
| print.cp_posthoc | Print method for cp_posthoc objects |
| print.summary.beezdemand_fixed | Print Method for summary.beezdemand_fixed |
| print.summary.beezdemand_hurdle | Print Summary of Hurdle Demand Model |
| print.summary.beezdemand_nlme | Print method for summary.beezdemand_nlme |
| print.summary.beezdemand_systematicity | Print Method for summary.beezdemand_systematicity |
| print.summary.cp_model_lm | Print method for summary.cp_model_lm objects. |
| print.summary.cp_model_lmer | Print method for summary.cp_model_lmer objects. |
| print.summary.cp_model_nls | Print method for summary.cp_model_nls objects |
| print.summary.cp_unsystematic | Print Method for Cross-Price Unsystematic Summary |
| print_mc_summary | Print Monte Carlo Simulation Results |
| pseudo_ll4_trans | Create a Pseudo-Log LL4 Transformation Object for ggplot2 |
| ranef.beezdemand_nlme | Extract Random Effects from a beezdemand_nlme Model |
| ranef.cp_model_lmer | Extract Random Effects from Mixed-Effects Cross-Price Model |
| RecodeOutliers | Recode Outliers |
| ReplaceZeros | Replace Zeros |
| run_hurdle_monte_carlo | Run Monte Carlo Simulation Study for Hurdle Demand Model |
| scale_color_beezdemand | beezdemand Color Scale (Discrete) |
| scale_fill_beezdemand | beezdemand Fill Scale (Discrete) |
| scale_ll4 | Create an LL4-like Scale for ggplot2 Axes |
| SimulateDemand | Simulate Demand Data |
| simulate_hurdle_data | Simulate Data from Two-Part Mixed Effects Hurdle Demand Model |
| summary.beezdemand_descriptive | S3 Methods for beezdemand_descriptive Objects |
| summary.beezdemand_empirical | S3 Methods for beezdemand_empirical Objects |
| summary.beezdemand_fixed | Summary Method for beezdemand_fixed |
| summary.beezdemand_hurdle | Summarize a Hurdle Demand Model Fit |
| summary.beezdemand_nlme | Summary method for beezdemand_nlme |
| summary.beezdemand_systematicity | Summary Method for beezdemand_systematicity |
| summary.cp_model_lm | Summary method for cp_model_lm objects. |
| summary.cp_model_lmer | Summary method for cp_model_lmer objects. |
| summary.cp_model_nls | Summarize a Cross-Price Demand Model (Nonlinear) |
| summary.cp_unsystematic | Summarize Cross-Price Unsystematic Data Check Results |
| systematic-wrappers | Systematicity Check Wrappers |
| theme_apa | APA Theme |
| theme_beezdemand | beezdemand Plot Theme |
| tidy.beezdemand_fixed | Tidy Method for beezdemand_fixed |
| tidy.beezdemand_hurdle | Tidy a beezdemand_hurdle Model |
| tidy.beezdemand_nlme | Tidy method for beezdemand_nlme |
| tidy.beezdemand_systematicity | Tidy Method for beezdemand_systematicity |
| tidy.cp_model_lm | Extract coefficients from a linear cross-price model in tidy format |
| tidy.cp_model_lmer | Extract coefficients from a mixed-effects cross-price model in tidy format |
| tidy.cp_model_nls | Convert a cross-price model to a tidy data frame of coefficients |