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Package {CHOIRBM}

Title: Plots the CHOIR Body Map
Version: 0.0.3
Description: Collection of utility functions for visualizing body map data collected with the Collaborative Health Outcomes Information Registry.
License: MIT + file LICENSE
URL: https://github.com/emcramer/CHOIRBM
BugReports: https://github.com/emcramer/CHOIRBM/issues
Depends: R (≥ 3.5.0)
Imports: broom, ggplot2, rlang, stringr
Suggests: knitr, rmarkdown, testthat (≥ 2.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-07-28 06:19:25 UTC; cramere
Author: Eric Cramer ORCID iD [aut, cre], Stanford University School of Medicine [cph, fnd]
Maintainer: Eric Cramer <dev.emc503@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-28 08:20:13 UTC

CHOIRBM: Plots the CHOIR Body Map

Description

Collection of utility functions for visualizing body map data collected with the Collaborative Health Outcomes Information Registry.

Author(s)

Maintainer: Eric Cramer dev.emc503@gmail.com (ORCID)

Other contributors:

See Also

Useful links:

Converts a list of CBMs to a single data frame

Description

Takes a list of data frames where each data frame is the CBM of a patient and the values column is a binary endorsement of the CBM segment. Then it collapses the information to a single data frame for plotting by adding the 'value' columns of each data frame.

Usage

agg_choirbm_list(cbm_list)

Arguments

cbm_list

a list of CBMs to collapse

Value

map_df a single CBM data frame with the value column summed.

Examples

## Not run: 
data(validation)
cbm_list <- lapply(validation[["bodymap_regions_csv"]], string_to_map)
agg_df <- agg_choirbm_list(cbm_list)

## End(Not run)

Compare CBM segment endorsement across categorical variable using Chi-Square

Description

Compare CBM segment endorsement across categorical variable using Chi-Square

Usage

comp_choirbm_chi(cbm_list, ...)

Arguments

cbm_list

a named list of CBMs

...

additional parameters passed to p.adjust()

Value

a data frame with the p-values, chi statistic, and degrees of freedom

Examples

## Not run: 
data(validation)
# split male and female data
male_data <- validation[validation[['gender']] == "Male", ]
male_bodymap_list <- lapply(
 male_data[["bodymap_regions_csv"]]
 , string_to_map)
male_bodymap_df <- agg_choirbm_list(male_bodymap_list)
female_data <- validation[validation[['gender']] == "Female", ]
female_bodymap_list <- lapply(
 female_data[["bodymap_regions_csv"]]
 , string_to_map)
female_bodymap_df <- agg_choirbm_list(female_bodymap_list)
# compare with chi square test
chi_res <- comp_choirbm_chi(
 list("male" = male_bodymap_df
 , "female" = female_bodymap_df)
 , method = 'bonferroni'
)

## End(Not run)

Examine the effect of a continuous variable on CBM location endorsement

Description

Examine the effect of a continuous variable on CBM location endorsement

Usage

comp_choirbm_glm(in_df, comp_var, method = "bonferroni", ...)

Arguments

in_df

a data.frame with at least one column for the CBM as a delimited string, and another column as the continuous variable for modeling.

comp_var

the name of the variable to model as a string

method

the method for p-value corrections

...

additional parameters passed to glm.

Value

a data.frame with the following columns: id, term, estimate, std.error, statistic, p.value. Each row is the result of one glm using the continuous variable to predict CBM location endorsement.

Examples

## Not run: 
data(validation)
set.seed(123)
sampled_data <- validation[sample(1:nrow(validation), 100, replace = FALSE),]
model_ouput <- comp_choirbm_glm(sampled_data, "age")

## End(Not run)

Compare CBM segment endorsement across categorical variable using z-test(s)

Description

Compare CBM segment endorsement across categorical variable using z-test(s)

Usage

comp_choirbm_ztest(cbm_list, tail = "two", p.method = "bonferroni")

Arguments

cbm_list

a named list of CBMs

tail

whether to do a single or two tailed z test

p.method

the method for p-value corrections

Value

a data frame with the p-values and z statistic

Examples

library(CHOIRBM)
# isolate and process male data
male_data <- validation[validation[["gender"]] == "Male", ]
# isolate and process female data
female_data <- validation[validation[["gender"]] == "Female", ]
comp_choirbm_ztest(list( "male" = male_data, "female" = female_data), tail = "two")

Calculate the co-occurrence between locations on the CBM

Description

Calculates the raw number of times two locations on the CBM are endorsed together in a data set.

Usage

comp_cooccurrence(df)

Arguments

df

a data.frame with the CBMs as delimited strings in a single column.

Value

a data.frame with every combination of CBM locations and the number of times those locations occur together (the "co-occurrence").

Examples

## Not run: 
set.seed(123)
sampled_data <- validation[sample(1:nrow(validation), 100, replace = FALSE),]
colnames(sampled_data)[5] <- "bodymap"
con_mat <- comp_cooccurrence(sampled_data)

## End(Not run)

convert_bodymap Helper function to convert a single bodymap

Description

convert_bodymap Helper function to convert a single bodymap

Usage

convert_bodymap(segments)

Arguments

segments

a character vector containing segment numbers as individual strings in the vector that need to be adjusted/standardized

Value

a character vector containing standardized segment numbers as individual strings in the vector

Examples

exampledata <- data.frame(
    GENDER = as.character(c("Male", "Female", "Female")),
    BODYMAP_CSV = as.character(c("112,125","112,113","128,117"))
 )
convert_bodymap(exampledata[2,2])

convert_bodymaps Function to convert multiple bodymaps

Description

convert_bodymaps Function to convert multiple bodymaps

Usage

convert_bodymaps(f_maps)

Arguments

f_maps

a character vector where each string is a CHOIR bodymap in csv form

Value

a character vector of bodymaps using the male CHOIR bodymap numberings as a standard. Each bodymap is in csv form

Examples

exampledata <- data.frame(
    GENDER = as.character(c("Male", "Female", "Female")),
    BODYMAP_CSV = as.character(c("112,125","112,113","128,117"))
 )
convert_bodymaps(
    as.character(
        exampledata$BODYMAP_CSV[exampledata$GENDER == 'Female']
     )
 )

Generate Simple Example Data

Description

Creates a data frame with CHOIR Body Map segment IDs and a randomly associated value. Also adds grouping information for facetting while plotting.

Usage

gen_example_data(seed = 123)

Arguments

seed

integer to seed the random number generator

Value

values data.frame

Examples

cbm_df <- gen_example_data()
head(cbm_df)

Count the number of areas indicated in a CBM

Description

Counts the number of areas a person endorses/indicates on their CHOIR Body Map.

Usage

num_areas(cbm_str, delim = ",")

Arguments

cbm_str

a delimited string of 3-digit codes indicating CBM areas.

delim

the delimiter character, defaults to a comma.

Value

nareas

Examples

cbm_str <- c("101,102,103,104")
num_areas(cbm_str, ",")

Plot a concurrence matrix

Description

Generates a concurrence matrix as a heatmap to show which CBM locations are commonly endorsed together.

Usage

plot_cooccurrence(con_mat, ...)

Arguments

con_mat

a long form data frame or matrix produced by the plot_concurrence function, with every combination of locations and the number of times each combination occurs.

...

additional parameters for plotting

Value

a ggplot heatmap of the concurrence.

Examples

## Not run: 
set.seed(123)
sampled_data <- validation[sample(1:nrow(validation), 100, replace = FALSE),]
con_mat <- comp_cooccurrence(sampled_data)
plot_cooccurrence(con_mat)

## End(Not run)

Plot the male CHOIR Body Map

Description

Creates a new plot of the front and back of the female CHOIR body map.

Usage

plot_female_choirbm(df, value)

Arguments

df

data.frame

value

string

Value

ggrob

Examples

cbm_df <- gen_example_data()
plot_female_choirbm(cbm_df, "value")

Plot the male CHOIR Body Map

Description

Creates a new plot of the male CHOIR body map.

Usage

plot_male_choirbm(df, value)

Arguments

df

data.frame

value

string

Value

ggrob

Examples

cbm_df <- gen_example_data()
plot_male_choirbm(cbm_df, "value")

Plots a histogram of the number of CBM areas indicated

Description

This is a wrapper for ggplot2's histogram function that incorporates calculating the number of CBM areas each individual indicates.

Usage

plot_nareas_histogram(cbms, ...)

Arguments

cbms

a list of delimited CBM strings

...

additional arguments passed to geom_histogram

Value

a histogram of the number of CBM areas endorsed by individuals in the dataset.

Examples

## Not run: 
data(validation)
below20 <- validation[
 sapply(validation$bodymap_regions_csv, num_areas) < 20
 , ]
plot_nareas_histogram(
 below20$bodymap_regions_csv
 , binwidth = 1
 , fill = "grey"
 , color = "white")

## End(Not run)

prep_bodymaps converts a single charcter vector of bodymaps into a list of character vectors, each a bodymap

Description

prep_bodymaps converts a single charcter vector of bodymaps into a list of character vectors, each a bodymap

Usage

prep_bodymaps(maps)

Arguments

maps

a character vector containing the endorsed bodymap segments of patients in csv form

Value

a list of character vectors, where each vector contains the patient's endorsed segments

Examples

exampledata <- data.frame(
    GENDER = as.character(c("Male", "Female", "Female")),
    BODYMAP_CSV = as.character(c("112,125","112,113","128,117"))
 )
prep_bodymaps(as.character(exampledata$BODYMAP_CSV))

Converts a comma-separated string to a CHOIR BM

Description

Takes a string of IDs that are separated by a comma and converts the information into a data frame with a binary indication of whether or not an ID appeared. Useful for plotting an individual's CHOIR BM or for isolating particular sections to highlight.

Usage

string_to_map(map_str = "", delim = ",")

Arguments

map_str

The delimited CBM string.

delim

The delimiter for the CBM string.

Value

ret_df data.frame with all of the CHOIR BM segment IDs with a 1 if the segment was present and 0 otherwise.

Examples

# from a choir database
cbm_str <- "101,102,103,104,201,202"
cbm_df <- string_to_map(cbm_str)
# plot in a male or female bodymap...
plot_male_choirbm(cbm_df, "value")

# from a REDCap project
cbm_str <- "b07,b18,b19,b23,b24,b28,b33,f01,f03,f08,f17,f27,f29"
cbm_df <- string_to_map(cbm_str)
# plot in a male or female bodymap...
plot_male_choirbm(cbm_df, "value")

CHOIR Body Map data for approximately 7,000 patients

Description

A non-identifiable, simulated data set generated by randomly permuting data from the CHOIR Body Map validation study.

Usage

data(validation)

Format

An object of class "data.frame"

id

A randomly generated numeric code for each patient.

gender

The patient's gender.

race

The patient's race.

age

The patient's age.

bodymap_regions_csv

The patient's CHOIR Body Map in a comma separated string.

score

A simulated pain score for demonstration purposes.

References

This data set was derived from the data collected during the study validating the CHOIR Body Map as an instrument for recording a patient's anatomical pain location. doi:10.1097/pr9.0000000000000880

Examples


data(validation)
head(validation)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.