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.
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