In this version, the structure of the primary function is rewritten. The function treats factor and numeric base terms with separate side functions leaving room for more distinguished actions on the models with the two types of terms.
New features
-
stats_cp = "ci" works for factor base-term models.
- Allow to output confidence intervals of the difference between the minimum and maximum values of the conditioning variable when
plot = FALSE.
-
prePro can be used on multilevel models
Bug fix
- Update
interplot.plot for the latest version of ggplot
New features
- Adding new statistics for testing the statistical significance of the conditional effect (by
stats_cp).
- Adding an argument to modify the plot caption (by
txt_caption).
Bug fix
- Adding example of models based on multiple imputations.
- Modifying the vignette to include new functions.
- interplot no longer sets the random seed; to ensure complete reproducibility, users must now set their own seeds using
set.seed() before calling interplot functions.
- Adds facet_labs argument, an optional character vector of facet labels to be used when plotting an interaction with a factor variable.
Function Updates
- Showing the confidence intervals between the conditional effects at the minimum and maximum values of the conditioning variable.
Error Fixed
- Avoiding the warning caused by the
class(m) == "polr".
Adding Argument
- Adding an argument to adjust CIs to control the false discovery rate.
- Adding an argument to produce conditional predicted probabilities at given values.
Vignette Updates
- Adding a brief review of the methodology of interaction.
- Adding an example to show how to control for the false discovery rate.
- Adding an example to illustrate plotting conditional predicted propbabilities.
Adding Argument
- Adding an argument to adjust the CIs.
Error Fixed
- Fixing the error in plotting
lmer projects.
Function Updates
- Take the
steps argument back in case of special design requirement of the plot.
- Fixed an error in presenting the histogram on categorical conditioning variables.
- Improving the histogram presentation: all the bars for categorical variables are centered.
Vignette Updates
Updated the vignette including instructions of how to change the aesthetics of the plot and how to use histogram function.
Vignette Updates
Updated the vignette including instructions of how to change the aesthetics of the plot and how to use histogram function.
Additional Function
- The aesthetics can be modified through built-in arguments or the ggplot
geom_ functions.
- A histogram can be superimposed into the plot.
Additional Function
Adding the function to plot interactions based on factor variables. ## Bug fix Fit ggplot2 2.0.0 Fixed the quadratic error (#16)
Additional Function
Adding the function to plot interactions based on factor variables. ## Bug fix Fit ggplot2 2.0.0
Bug fix
Fix the bug for nonlinear multilevel models with multiply imputed data (gmlmmi).
Bug fix
Fix the error to run mlm and mlmmi.