In CCMH-PSU/CCMHr: CCMH Data Cleaning

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CCMHr

The goal of CCMHr is to collect functions commonly used when working with CCMH data.

This package isn't on CRAN, so you'll need to use the devtools package to install it.

devtools::install_github("CCMH-PSU/CCMHr")

then load it

library(CCMHr)

check_CCAPS is used in initially cleaning the CCAPS data from TI or the webservice to check that all of the CCAPS item values are in bounds. It alerts you if any of the items are out of bounds. Karl at TI also runs a check on this, so it should never return an error, but better safe than sorry. This is run before the CCAPS subscales are scored each time we get a new year of data.
score_CCAPS runs all the scoring syntax to produce CCAPS subscale scores for the CCAPS-34 and CCAPS-62, running checks for validity and not scoring any administrations that don't pass validity checks (e.g. variance of 0 or too much missing data).
CCAPS34_cuts and CCAPS62_cuts create dichotomous variables for the CCAPS-34 and CCAPS-62 indicating whether each subsclae was above the low and high cut scores. The function takes a data frame with CCAPS subscales, either in the form Depression34 or Depression34_first, specified by the first argument, as well as an arguemnt specifying which year of cut scores to use, with options currently for 2018 & 2019.

create_courses separates the data into courses of therapy based on a 90 day criteria. This provides the option of keeping all courses or only each client's first course.
sds_to_factor converts SDS variables from numeric into factors of their actual response options.
delete_duplicate_appointments removes a client's duplicate appointments that have the same AppointID
CCAPS_change creates change scores for the CCAPS from first to last administration, with the option to also include first and last CCAPS scores and change scores for specific CCAPS items.

ccmh_theme adds some CCMH specific theming to ggplots. This includes changing the font to Avenir, adding spacing between axes and axes titles, and increasing the font size. Any of this can be overwritten by an additional ggplot theme argument if parts of it are not desired.
add_caption adds a caption to a plot attributing it to CCMH.

setup_data_request creates the folders necessary for data request cleaning and creates a skeleton data request cleaning syntax file with basic syntax that is run on most data requests.
remove_empty removes columns that are entirely empty. This is usually due to items being deactivated.
remove_free_response removes any free response columns. This is done prior to sharing data in case those columns have identifying information.
The rename_subscales functions renames CCAPS subscles them for use in a graph or a table (e.g. Anxiety34 -> Generalized Anxiety)
CLI cleaning functions: bin_enrollment, bin_utilization, bin_utilization, and bin_inst_utilization discretize the CLI variables into predetermined bins.

loadRDa loads .rda and .rdata files with the ability to assign them to a new object name instead of the one they were originally saved with. Using load on .rda files loads them into the environment with the object name they had when they were saved.
get_mode gets the mode of a numeric vector.
first_present and last_present provide the first/last non-NA value in a vector.

CCMHr also contains several data objects that can be loaded into R from the package.

alerts provides a lookup table for each subscale, starting CCAPS bin, and session indicating the score above which a CCAPS alert is produced on the CCAPS profile report.
clicc_key contains a key for the CLICC items and numbers.
case_closure_key contains a key for the Case Closure items and numbers.