This is the Data Integration, MRI, and Bioinformatics Component of the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), funded by the NIAAA.
With the latest influx of variables into Data Entry
lssaga1_youth_dm15d_dm15d_1_dm15d_y and "lssaga1_youth_dm15d_dm15d_2_dm15d_y have a bunch of In progress responses, some . responses
mrireport_mri_set*_*_mrilu6_mricns90[dh] have a bunch of . responses.
This is clocking at about 83 issues. The standard SOP is to ask the sites to go fix it in the Import project, but given the homogeneity of the errors, it might not be a bad idea to implement some filtering in update_visit_data. Implementation sketch:
a config section in sibis_sys_config.yml of the form
update_visit_data:
ignored_values:
lssaga1_youth_dm15d_dm15d_1_dm15d_y:
- "."
- "In progress"
a method in update_visit_data that goes through ignored values per field and empties them out with something like data.loc[data[varname] == value, varname] = np.nan
With the latest influx of variables into Data Entry
lssaga1_youth_dm15d_dm15d_1_dm15d_yand"lssaga1_youth_dm15d_dm15d_2_dm15d_yhave a bunch ofIn progressresponses, some.responsesmrireport_mri_set*_*_mrilu6_mricns90[dh]have a bunch of.responses.This is clocking at about 83 issues. The standard SOP is to ask the sites to go fix it in the Import project, but given the homogeneity of the errors, it might not be a bad idea to implement some filtering in
update_visit_data. Implementation sketch:sibis_sys_config.ymlof the formupdate_visit_datathat goes through ignored values per field and empties them out with something likedata.loc[data[varname] == value, varname] = np.nan