MAGMA.R (version 1.0.3)

Density_overlap: Density_overlap

Description

This function shows and quantifies the kernel density overlap of a variable for two or more groups.

Usage

Density_overlap(
  Data,
  variable,
  group,
  variable_name = NULL,
  group_labels = NULL,
  group_name = NULL,
  step_num = NULL,
  step_var = NULL,
  verbose = TRUE
)

Value

A plot showing the kernel density for a specified variable separately for specified groups and the quantification of this overlap.

Arguments

Data

A data frame that contains the desired variable for density plotting as well as the specified grouping variable.

variable

A character specifying the variable for which the density should be plotted (e.g., "ps_gifted").

group

A character specifying the groups for which the density should be plotted. Can be an independent group comparison (e.g., comparing matched groups) or the comparison of pre and post matched samples.

variable_name

A character specifying the name to appear in the plot for the variable.

group_labels

A character vector specifying the labels for the groups to ppear in the legend of the plot.

group_name

A character specifying the name of the grouping variable to appear in the title of the legend.

step_num

An integer specifying the number of cases to be included per group in this post matching comparison. Is based on the step variable of MAGMA.

step_var

A character specifying the name of the step variable.

verbose

TRUE or FALSE indicating whether matching information should be printed to the console.

Author

Julian Urban

Details

This function enables the comparison of the density of variables for two or more groups. It plots the kernel density separately for each group and quantifies the amount of overlap.

References

Pastore, M., Loro, P.A.D., Mingione, M., Calcagni, A. (2022). overlapping: Estimation of Overlapping in Empirical Distributions. R package version 2.1, https://CRAN.R-project.org/package=overlapping.

Examples

# Estimating density overlap using the data set 'MAGMA_sim_data
# Estimating density overlap for 'ps_gifted' (propensity scores for
# giftedness support)
# Defining plot aesthetics with 'group', 'variable_name', "group_lables',
# and 'group_name'
# Estimating pre-matching density overlap by not specifying 'step_num' and
# 'step_var'
Density_overlap(Data = MAGMA_sim_data,
variable = "ps_gifted",
group = "gifted_support",
step_num = NULL,
step_var = NULL,
variable_name = "Propensity Score",
group_labels = c("No Support", "Support"),
group_name = "Gifted Support")


# Estimating density overlap using the matched data set
#'MAGMA_sim_data_gifted'
# Estimating density overlap for 'ps_gifted' (propensity scores for
# giftedness support)
# Defining plot aesthetics with 'group', 'variable_name', 'group_lables',
# and 'group_name'
# Estimating post-matching overlap for 250 cases per group ('step_num')
# Name of the step variable is 'step'
Density_overlap(Data = MAGMA_sim_data,
variable = "ps_gifted",
group = "gifted_support",
step_num = 250,
step_var = "step_gifted",
variable_name = "Propensity Score",
group_labels = c("No Support", "Support"),
group_name = "Gifted Support")

# Estimating density overlap using the data set 'MAGMA_sim_data
# Estimating density overlap for 'teacher_ability_rating' (ability rated
# from teacher as below average, average, or above average)
# Defining plot aesthetics with 'group', 'variable_name', 'group_lables',
# and 'group_name'
# Estimating pre-matching density overlap by not specifying 'step_num' and
# 'step_var'
Density_overlap(Data = MAGMA_sim_data,
variable = "GPA_school",
group = "teacher_ability_rating",
variable_name = "School Achievement",
group_labels = c("Low", "Medium", "High"),
group_name = "Rating")