| Title: | Explore and Code Responses to Check-All-that-Apply Survey Items |
| Version: | 1.0.0 |
| Description: | Analyzing responses to check-all-that-apply survey items often requires data transformations and subjective decisions for combining categories. 'CATAcode' contains tools for exploring response patterns, facilitating data transformations, applying a set of decision rules for coding responses, and summarizing response frequencies. |
| License: | GPL (≥ 3) |
| URL: | https://github.com/knickodem/CATAcode |
| BugReports: | https://github.com/knickodem/CATAcode/issues |
| Depends: | R (≥ 3.6) |
| Imports: | rlang, dplyr (≥ 1.1.0), tidyr, ggplot2 |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.2.3 |
| Config/testthat/edition: | 3 |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2025-08-20 20:40:00 UTC; nicko013 |
| Author: | Kyle Nickodem 
[aut, cre],
Gabriel J. Merrin [aut] |
| Maintainer: | Kyle Nickodem <kyle.nickodem@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-08-26 14:20:17 UTC |
CATAcode: Explore and Code Responses to Check-All-that-Apply Survey Items
Description
Analyzing responses to check-all-that-apply survey items often requires data transformations and subjective decisions for combining categories. CATAcode contains tools for exploring response patterns, facilitating data transformations, applying a set of decision rules for coding responses, and summarizing response frequencies.
Author(s)
Maintainer: Kyle Nickodem kyle.nickodem@gmail.com (ORCID)
Authors:
Gabriel J. Merrin gjmerrin@syr.edu
See Also
Useful links:
Code check-all-that-apply responses into a single variable
Description
In a cross-sectional or longitudinal context, select a set of decision rules to combine responses to multiple categories from a check-all-that-apply survey question into a single variable.
Usage
cata_code(
data,
id,
categ,
resp,
approach,
endorse = 1,
time = NULL,
priority = NULL,
new.name = "Variable",
multi.name = "Multiple",
sep = "-"
)
Arguments
data |
A data frame with one row for each |
id |
The column in |
categ |
Column in |
resp |
Column in |
approach |
One of "all", "count", "multiple", "priority", or "mode". See Details. |
endorse |
The value in |
time |
The column in |
priority |
Character vector of one or more categories in the |
new.name |
Character; column name for the created variable. |
multi.name |
Character; value given to participants with multiple category endorsements when |
sep |
Character; separator to use between values when |
Details
For all approach options, participants with missing data for all categories in categ are removed and not present in the output.
There are two options for approach that provide summary information rather than a single code for each id.
*"all" returns a data frame with new.name variable comprised of all categories
endorsed by separated by sep. The time argument is ignored when approach = "all". Rather,
if data includes a column for time, then output includes a row for each id at each time point.
This approach is a useful exploratory first step for identifying all of the response patterns present in the data.
*"counts" is only relevant for longitudinal data and returns a data frame with the number of times an id endorsed
a category. Only categories with >= 1 endorsement are included for a particular id. As with "all", the time argument
is ignored and instead assumes data is in longer format with a row for each id by time combination. If not,
the column of counts will be 1 for all rows.
The three remaining options for approach produce a single code for each id.
The output is a data frame with one row for each id. The choice of approach is
only relevant for participants who selected more than one category whereas
participants who only selected one category will be given that code in the output
regardless of which approach is chosen.
*"multiple" If participant endorsed multiple categories within or across time, code as multi.name.
*"priority" Same as "multiple" unless participant endorsed category in priority argument at any point.
If so, then code in order specified in priority.
*"mode" Participant is coded as the category with the mode (i.e., most common) endorsement across all time points.
Ties are coded as as the value given in multi.name. If the priority argument is specified, these categories are prioritized
first, followed by the mode response. The "mode" approach is only relevant if time is specified.
When time = NULL it operates as "priority" (when specified) or "multiple".
Value
data.frame
Examples
# prepare data
data(sources_race)
sources_long <- cata_prep(data = sources_race, id = ID, cols = Black:White, time = Wave)
# Identify all unique response patterns
all <- cata_code(sources_long, id = ID, categ = Category, resp = Response,
approach = "all", time = Wave, new.name = "Race_Ethnicity")
unique(all$Race_Ethnicity)
# Coding endorsement of multiple categories as "Multiple
multiple <- cata_code(sources_long, id = ID, categ = Category, resp = Response,
approach = "multiple", time = Wave, new.name = "Race_Ethnicity")
# Prioritizing "Native_American" and "Pacific_Islander" endorsements
# If participant endorsed both, they are coded as "Native_American" because it is listed first
# in the priority argument.
priority <- cata_code(sources_long, id = ID, categ = Category, resp = Response,
approach = "priority", time = Wave, new.name = "Race_Ethnicity",
priority = c("Native_American", "Pacific_Islander"))
# Code as category with the most endorsements. In the case of ties, code as "Multiple"
mode <- cata_code(sources_long, id = ID, categ = Category, resp = Response,
approach = "mode", time = Wave, new.name = "Race_Ethnicity")
# Compare frequencies across coding schemes
table(multiple$Race_Ethnicity)
table(priority$Race_Ethnicity)
table(mode$Race_Ethnicity)
Prepare data for cata_code()
Description
A helper function to transform data into a longer format in preparation for use in cata_code().
Usage
cata_prep(
data,
id,
cols,
time = NULL,
names_to = "Category",
values_to = "Response",
...
)
Arguments
data |
A data frame where rows are participants or participant by time combinations if |
id |
The column in |
cols |
< |
time |
The column in |
names_to |
Character. The name for the new column of category labels (i.e., names of the |
values_to |
Character. The name for the new column of responses (i.e., cell values in the |
... |
Optional additional arguments passed to |
Value
An object of the same type as data with one row for each id (by time, if specified) by response category combination.
Examples
data(sources_race)
cata_prep(data = sources_race, id = ID, cols = Black:White, time = Wave)
Sources of Strength Race/Ethnicity Data
Description
Responses to the check-all-that-apply race/ethnicity question at four time points from a randomized controlled trial of the Sources of Strength program.
Usage
sources_race
Format
A data frame with 16,922 rows and 9 columns:
- ID
Subject identification number
- Wave
Data collection time point
- Black, Native_American, Asian, Hispanic, Multiracial, Pacific_Islander, White
Indicator variables for check-all-that-apply responses where 1 = endorsement