coefficient_forestplot: Create forest plot of model coefficients with confidence...

In tloux/paramhetero: Numeric and Visual Comparisons of Heterogeneity in Parametric Models

Create forest plot of model coefficients with confidence intervals

Description

Create a ggplot forest plot of model coefficients with confidence intervals.

Usage

coefficient_forestplot(
  model_list,
  model_names = NULL,
  varlabs = NULL,
  conflevel = 0.95,
  horiz = TRUE
)

Arguments

model_list	A list of regression models.
model_names	A list of names for the regression models.
varlabs	A vector of labels for model variables.
conflevel	Confidence level for intervals.
horiz	Toggle whether confidence intervals are displayed horizontally or vertically. Default is set to TRUE.

Details

The forest plot groups variables along the axis determined by the horiz parameter and colors the data by model. If model_names = NULL, the default, models are numbered sequentially in the order they appear in model_list (Model 1, Model 2, Model 3, etc.).

Value

A ggplot object to compare model coefficient estimates with their corresponding confidence interval(s), grouped by coefficient.

Examples

 states = as.data.frame(state.x77)

 m1 = lm(`Life Exp` ~ Income + Illiteracy, data=states,
         subset=state.region=='Northeast')
 m2 = lm(`Life Exp` ~ Income + Illiteracy, data=states,
         subset=state.region=='South')
 m3 = lm(`Life Exp` ~ Income + Illiteracy, data=states,
         subset=state.region=='North Central')
 m4 = lm(`Life Exp` ~ Income + Illiteracy, data=states,
         subset=state.region=='West')

 mList = list(m1, m2, m3, m4)

 coefficient_forestplot(model_list = mList,
                        model_names =c('Northeast', 'South',
                                       'North Central', 'West'),
                        horiz = FALSE)

tloux/paramhetero documentation built on May 17, 2022, 4:16 p.m.