interplot (version 0.2.1)

interplot.lmmi: Plot Conditional Coefficients in (Generalized) Linear Models with Imputed Data and Interaction Terms

Description

interplot.mi is a method to calculate conditional coefficient estimates from the results of (generalized) linear regression models with interaction terms and multiply imputed data.

Usage

# S3 method for lmmi
interplot(m, var1, var2, plot = TRUE, steps = NULL,
  ci = 0.95, adjCI = FALSE, hist = FALSE, var2_dt = NA,
  predPro = FALSE, var2_vals = NULL, point = FALSE, sims = 5000,
  xmin = NA, xmax = NA, ercolor = NA, esize = 0.5, ralpha = 0.5,
  rfill = "grey70", ...)

Arguments

m

A model object including an interaction term, or, alternately, a data frame recording conditional coefficients.

var1

The name (as a string) of the variable of interest in the interaction term; its conditional coefficient estimates will be plotted.

var2

The name (as a string) of the other variable in the interaction term.

plot

A logical value indicating whether the output is a plot or a dataframe including the conditional coefficient estimates of var1, their upper and lower bounds, and the corresponding values of var2.

steps

Desired length of the sequence. A non-negative number, which for seq and seq.int will be rounded up if fractional. The default is 100 or the unique categories in the var2 (when it is less than 100. Also see unique).

ci

A numeric value defining the confidence intervals. The default value is 95% (0.95).

adjCI

A logical value indication if applying the adjustment of confidence intervals to control the false discovery rate following the Esarey and Sumner (2017) procedure. (See also Benjamini and Hochberg 1995.) The default is FALSE; the plot presents the confidence intervals suggested by Brambor, Clark, and Golder (2006).

hist

A logical value indicating if there is a histogram of `var2` added at the bottom of the conditional effect plot.

var2_dt

A numerical value indicating the frequency distribution of `var2`. It is only used when `hist == TRUE`. When the object is a model, the default is the distribution of `var2` of the model.

predPro

A logical value with default of `FALSE`. When the `m` is an object of class `glm` and the argument is set to `TRUE`, the function will plot predicted probabilities at the values given by `var2_vals`.

var2_vals

A numerical value indicating the values the predicted probabilities are estimated, when `predPro` is `TRUE`.

point

A logical value determining the format of plot. By default, the function produces a line plot when var2 takes on ten or more distinct values and a point (dot-and-whisker) plot otherwise; option TRUE forces a point plot.

sims

Number of independent simulation draws used to calculate upper and lower bounds of coefficient estimates: lower values run faster; higher values produce smoother curves.

xmin

A numerical value indicating the minimum value shown of x shown in the graph. Rarely used.

xmax

A numerical value indicating the maximum value shown of x shown in the graph. Rarely used.

ercolor

A character value indicating the outline color of the whisker or ribbon.

esize

A numerical value indicating the size of the whisker or ribbon.

ralpha

A numerical value indicating the transparency of the ribbon.

rfill

A character value indicating the filling color of the ribbon.

...

Other ggplot aesthetics arguments for points in the dot-whisker plot or lines in the line-ribbon plots. Not currently used.

Value

The function returns a ggplot object.

Details

interplot is a S3 method from the interplot. It can visualize the changes in the coefficient of one term in a two-way interaction conditioned by the other term. This function can work on interactions from results in the class of list.

Because the output function is based on ggplot, any additional arguments and layers supported by ggplot2 can be added with the +.