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EDCimport is a package designed to easily import data from EDC software TrialMaster. Browse code at https://github.com/DanChaltiel/EDCimport and read the doc at https://danchaltiel.github.io/EDCimport/.
lastnews_table() when subjid is not
numericread_all_sas() causing metadata
(e.g. date_extraction) being converted to dataframesNew function read_all_sas() to read a database of
.sas7bdat files.
New function read_all_csv() to read a database of
.csv files.
New functions edc_data_warn() and
edc_data_stop(), to alert if data has inconsistencies (#29,
#39, #43).
ae %>% filter(grade<1 | grade>5) %>% edc_data_stop("AE of invalid grade")
ae %>% filter(is.na(grade)) %>% edc_data_warn("Grade is missing", issue_n=13)
#> Warning: Issue #13: Grade is missing (8 patients: #21, #28, #39, #95, #97, ...)New function edc_data_warnings(), to get a dataframe
of all warnings thrown by edc_data_warn().
New function edc_warn_extraction_date(), to alert if
data is too old.
New function select_distinct() to select all columns
that has only one level for a given grouping scope (#57).
New function edc_population_plot() to visualize
which patient is in which analysis population (#56).
New function edc_db_to_excel() to export the whole
database to an Excel file, easier to browse than RStudio’s table viewer
(#55). Use edc_browse_excel() to browse the file without
knowing its name.
New function edc_inform_code() to show how much code
your project contains (#49).
New function search_for_newer_data() to search a
path (e.g. Downloads) for a newer data archive (#46).
New function crf_status_plot() to show the current
database completion status (#48).
New function save_sessioninfo(), to save
sessionInfo() into a text file (#42).
New function fct_yesno(), to easily format Yes/No
columns (#19, #23, #40).
New function lastnews_table() to find the last date
an information has been entered for each patient (#37). Useful for
survival analyses.
New function harmonize_subjid(), to have the same
structure for subject IDs in all the datasets of the database
(#30).
New function save_plotly(), to save a
plotly to an HTML file (#15).
New experimental functions table_format(),
get_common_cols() and get_meta_cols() that
might become useful to find keys to pivot or summarise data.
get_datasets() will now work even if a dataset is named
after a base function (#67).read_trialmaster() will output a readable error when no
password is entered although one is needed.read_trialmaster(split_mixed="TRUE") will work as
intended.assert_no_duplicate() has now a by
argument to check for duplicate in groups, for example by visit
(#17).find_keyword() is more robust and inform on the
proportion of missing if possible.edc_lookup() will now retrieve the lookup table. Use
build_lookup() to build one from a table list.extend_lookup() will not fail anymore when the database
has a faulty table.get_key_cols() is replaced by
get_subjid_cols() and get_crfname_cols().check_subjid() is replaced by
edc_warn_patient_diffs(). It can either take a vector or a
dataframe as input, and the message is more informative.Changes in testing environment so that the package can be installed from CRAN despite firewall policies forbidding password-protected archive downloading.
Fixed a bug where a corrupted XPT file can prevent the whole import to fail.
check_subjid() to check if a vector is not
missing some patients (#8).options(edc_subjid_ref=enrolres$subjid)
check_subjid(treatment$subjid)
check_subjid(ae$subjid)assert_no_duplicate() to abort if a table
has duplicates in a subject ID column(#9).tibble(subjid=c(1:10, 1)) %>% assert_no_duplicate() %>% nrow()
#Error in `assert_no_duplicate()`:
#! Duplicate on column "subjid" for value 1.manual_correction() to safely hard-code a
correction while waiting for the TrialMaster database to be
updated.edc_options() to manage
EDCimport global parameterization.edc_swimmerplot(id_lim) to subset the
swimmer plot to some patients only.read_trialmaster(use_cache="write") to read
from the zip again but still update the cache.read_trialmaster(split_mixed=c("col1", "col2")) to split
only the datasets you need to (#10).read_trialmaster() from cache will output
an error if parameters (split_mixed,
clean_names_fun) are different (#4).split_mixed_datasets() is now fully
case-insensitive.read_trialmaster(use_cache="write") is now the default.
Reading from cache is not stable yet, so you should opt-in rather than
opt-out.read_trialmaster(extend_lookup=TRUE) is now the
default.edc_id, edc_crfname, and
edc_verbose have been respectively renamed
edc_cols_id, edc_cols_crfname, and
edc_read_verbose for more clarity.New function edc_swimmerplot() to show a swimmer
plot of all dates in the database and easily find outliers.
New features in read_trialmaster():
clean_names_fun=some_fun will clean all names of all
tables. For instance,
clean_names_fun=janitor::clean_names() will turn default
SAS uppercase column names into valid R snake-case column names.split_mixed=TRUE will split tables that contain both
long and short data regarding patient ID into one long table and one
short table. See ?split_mixed_datasets() for details.extend_lookup=TRUE will improve the lookup table with
additional information. See ?extend_lookup() for
details.key_columns=get_key_cols() is where you can change the
default column names for patient ID and CRF name (used in other new
features).Standalone functions extend_lookup() and
split_mixed_datasets().
New helper unify(), which turns a vector of
duplicate values into a vector of length 1.
Reading errors are now handled by read_trialmaster()
instead of failing. If one XPT file is corrupted, the resulting object
will contain the error message instead of the dataset.
find_keyword() is now robust to non-UTF8 characters
in labels.
Option edc_lookup is now set even when reading from
cache.
SAS formats containing a = now work as
intended.
Import your data from TrialMaster using
tm = read_trialmaster("path/to/archive.zip").
Search for a keyword in any column name or label using
find_keyword("date", data=tm$.lookup). You can also
generate a lookup table for an arbitrary list of dataframe using
build_lookup(my_data).
Load the datasets to the global environment using
load_list(tm) to avoid typing tm$
everywhere.
Browse available global options using
?EDCimport_options.
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.
Health stats visible at Monitor.