Graphically Based Data Analysis Using 'flexplot'
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Documentation for package ‘flexplot’ version 0.25.5
Help Pages
| added.plot | Create an added variable plot |
| added_plot | Create an added variable plot |
| alcuse | Alcohol use among youth |
| anchor.predictions | Generate Predictions for a Model |
| authors | Sales of books on Amazon |
| avengers | Simulated Statistics on the Final Avengers Battle |
| avp | Create an added variable plot |
| bf.bic | Compute Bayes Factor from BICs |
| birthweight | Dataset seeks to examine what can affect birthweight. |
| blood_pressure | Dataset examines what affects blood pressure. |
| build_group_id | Build group ID from binned variables |
| cholesterol | Dataset examines what affects cholesterol. |
| compare.fits | Compare the fits of two models |
| criminal_data | Criminal dataset |
| diet | Diet dataset |
| drug_use | Drug use and SES |
| estimates | Report Estimates (effect sizes and parameters) |
| estimates.default | Output APA style statistical significance from an object |
| estimates.glm | Report glm object Estimates (effect sizes and parameters) |
| estimates.glmerMod | Report glmerMod object Estimates (effect sizes and parameters) |
| estimates.lm | Report lm object Estimates (effect sizes and parameters) |
| estimates.lmerMod | Report lmerMod object Estimates (effect sizes and parameters) |
| estimates.RandomForest | Report RandomForest object Estimates (effect sizes and parameters) |
| estimates.zeroinfl | Report zeroinfl object Estimates (effect sizes and parameters) |
| exercise_data | Exercise dataset |
| flexplot | Create a "flexible plot" or flexplot |
| flexplota | Flexplot |
| flexplot_jasp2 | Flexplot in JASP |
| floor_ceiling | Replace minimum value with a specified floor |
| generate_predictions | Generate Predictions from Model Objects |
| generate_predictions.default | Generate Predictions for General Model Objects |
| generate_predictions.glmerMod | Generate Predictions for Generalized Linear Mixed-Effects Models |
| generate_predictions.lmerMod | Generate Predictions for Mixed-Effects Models |
| generate_predictions.polr | Generate Predictions for Ordinal Regression Models |
| generate_predictions.RandomForest | Generate Predictions for Random Forest Models |
| generate_predictions.rpart | Generate Predictions for Regression Tree Models |
| geom_jitterd | Jittered density points |
| get_model_n | Get Number of Observations from Model Objects |
| get_terms | Extract Variable Names from Model Objects |
| get_terms.default | Extract Variable Names from General Model Objects |
| get_terms.RandomForest | Extract Variable Names from RandomForest Models |
| glinmod | Perform a general linear model |
| glinmod_jasp | General Linear Model in JASP |
| glmbasic | General Linear Model |
| graduate_income | Graduate income |
| icc | Compute the ICC from a lmer (package lme4) model |
| ideation | Simulated Dataset About Suicide Ideation |
| income | Simulated Dataset About People's Income |
| job_data | Job performance dataset |
| linmod_jasp | General Linear Model in JASP |
| logistic_added_plot | Create an added variable plot with binned residuals for logistic regression |
| logistic_aligned | Align Logistic Regression Curves at the Threshold |
| logistic_coefficients | Output calculus-based logistic regression coefficients |
| logistic_overlay | Add Logistic Overlay to Plot |
| logistic_residual_plots | Create residual plots for logistic regression models |
| magnet_plot | Magnet Plot: Stacked Dot Plot for Binary Outcome with Logistic Fit |
| make.formula | Convert strings to a formula |
| marginal_plot | Create "margin plots" |
| math | Math Achievement Dataset |
| mediate_plot | Create a plot for mediation analysis |
| mixed.mod.visual | Display a graphic of a mixed model |
| mixedmod_jasp | General Linear Model in JASP |
| model.comparison | Perform a model comparison |
| modify_points | Modify the points in a flexplot (or ggplot) graphic |
| nsduh | NSDUH Dataset |
| paranormal | Simulated Dataset About Experiences with the Paranormal |
| partial_residual_plot | Partial Residual Plot |
| photo_lessons | An actual dataset of photography students |
| plant_growth | Plant Growth |
| position_jitterd | Jitter points based on density to avoid overplotting |
| position_jitterdodged | Simultaneously dodge and jitter |
| print.estimates | Print estimates Summary |
| print.glmer_estimates | Print glmer_estimates Summary |
| print.glm_estimates | Print glm_estimates Summary |
| print.lmer_estimates | Print lmer_estimates Summary |
| print.rf_estimates | Print rf_estimates Summary |
| relationship_satisfaction | Relationship satisfaction dataset |
| rescale | Transform a variable to have a particular mean and standard deivation |
| rsq_change | Compare the improvement in R squared from a baseline model |
| secret_agent | Secret agent dataset |
| sensitivity.table | Compute sensitivity/specificity/etc. |
| small | Small test dataset |
| standardized.beta | Compute standardized betas on a linear model object |
| subsetString | Extract only part of a string |
| tablesaw.injury | Tablesaw injuries |
| third.eye | Visualize flexplot with the "third eye" |
| univariate_list | Produce a bunch of univariate plots |
| visualize | Visualize a fitted model |
| visualize.default | Visualize a fitted model |
| visualize.glm | Visualize a fitted GLM model |
| visualize.glmerMod | Visualize a fitted glmerMod model |
| visualize.lm | Visualize a fitted model |
| visualize.lmerMod | Visualize a fitted lmerMod model |
| visualize.RandomForest | Visualize a fitted RandomForest model |
| youtube_plot | Create a 1080p plot for YouTube |