Due to update in madshapR package, the name columns internally used
in banff_launcher() have been changed. The rest of the
functions are not affected.
Implementation of the new parameter ‘version’ which allows the user to select a version of the Banff classification. At the moment of the development, the available versions are 2017 and 2022. The latest version (2022) is the default. The new version includes two new variables in the data dictionary (xm and abo_i) and 4 new diagnostics codes for diag_code_2.
calculate_adequacy() There was an error adressing the
proper order of participants, giving occasionally wrong calculation of
the adequacy. This has been fixed, using an index to ensure identical
order in the output.Error in document. There was a typo in banff_example.xlsx name. Only Read me and vignette were affected.
The banffIT package provides functions to assign standardized
diagnoses using the Banff Classification (Category 1 to 6 diagnoses,
including Acute and Chronic active T-cell mediated rejection as well as
Active, Chronic active, and Chronic antibody mediated rejection). The
main function banff_launcher()considers a minimal dataset
containing biopsies information in a specific format (described by a
data dictionary), verifies its content and format (based on the data
dictionary), assigns diagnoses, and creates a summary report.
banff_launcher() This function takes a path string
identifying the input file path. The function internally runs a series
of tests that assess the input dataset. If any of these tests fails, the
user gets information allowing them to correct the input dataset and
rerun the process. Once all tests pass, the dataset is given as an
output with a diagnosis for each observation (using the function
add_diagnoses() internally). The output dataset, along with
its associated labels (“label:en” by default) are provided to the user
in an Excel format file accessible in the output_folder specified. The
output dataset comes with a report that summarizes information about
variable distributions and descriptive statistics.banff_dataset_evaluate() This function takes a
dataset and evaluates its format and content based on the accepted
format specified in the data dictionary.
calculate_adequacy() A tibble object with two
variables: the calculated adequacy (adequacy_calculated) and the
adequacy specified in input (adequacy_input).
add_diagnoses() This function takes a dataset and
returns a diagnosis for each observation. For the function to run, the
dataset must not contain any errors that
banff_launcher()would have detected. Please prefer using
banff_launcher() to run additional tests.
get_banff_dictionary(),
get_banff_example(), get_banff_template() This
function gets the data dictionary used to control the consistency of the
input dataset, a example dataset and a template.
function banffIT_website() This function sends the
user to the online documentation for the package, which includes a
description of the latest version of the package, vignettes, user
guides, and a reference list of functions and help pages.