Plots the conditional coefficients ("marginal effects") of variables included in multiplicative interaction terms.

`interplot`

is a tool for plotting the conditional coefficients ("marginal effects") of variables included in multiplicative interaction terms. The function plots the changes in the coefficient of one variable in a two-way interaction term conditional on the value of the other included variable. The plot also includes simulated 95% confidential intervals of these coefficients.

To install:

- the latest released version:
`install.packages("interplot")`

. - the latest developing version:
`devtools::install_github("sammo3182/interplot")`

.

More details are available at:

http://cran.r-project.org/web/packages/interplot/vignettes/interplot-vignette.html

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

- Showing the confidence intervals between the conditional effects at the minimum and maximum values of the conditioning variable.

- Avoiding the warning caused by the
`class(m) == "polr"`

.

- Adding an argument to adjust CIs to control the false discovery rate.
- Adding an argument to produce conditional predicted probabilities at given values.

- 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 an argument to adjust the CIs.

- Fixing the error in plotting
`lmer`

projects.

- 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.

Updated the vignette including instructions of how to change the aesthetics of the plot and how to use histogram function.

Updated the vignette including instructions of how to change the aesthetics of the plot and how to use histogram function.

- The aesthetics can be modified through built-in arguments or the ggplot
`geom_`

functions. - A histogram can be superimposed into the plot.

Adding the function to plot interactions based on factor variables.

Fit `ggplot2`

2.0.0
Fixed the quadratic error (#16)

Adding the function to plot interactions based on factor variables.

Fit `ggplot2`

2.0.0

Fix the bug for nonlinear multilevel models with multiply imputed data (gmlmmi).

Fix the error to run mlm and mlmmi.