# Run Drug Level Data This module will load and modify drug-level data. ```r run_DrugLevel( conc.path, conc.columns = list(), conc.select, conc.rename, conc.mod.list = NULL, samp.path = NULL, samp.columns = list(), samp.mod.list = NULL, check.path = NULL, failmiss_fn = "MissingConcDate-", multsets_fn = "multipleSetsConc-", faildup_fn = "DuplicateConc-", drugname = NULL, LLOQ = NA, demo.list = NULL, demo.columns = list() ) ``` ## Arguments - `conc.path`: filename of concentration data (CSV, RData, RDS), or data.frame - `conc.columns`: a named list that should specify columns in concentration data. id and conc are required. idvisit may also be specified. If linking with sampling data, samplinkid is required. Otherwise datetime is required. This is the date and time when blood samples were obtained. This can refer to a single date-time variable (datetime = date_time ) or two variables holding date and time separately (e.g., datetime = c(Date , Time )). - `conc.select`: columns to select from concentration data - `conc.rename`: new column names for concentration data - `conc.mod.list`: list of expressions, giving modifications to make - `samp.path`: filename of data with sampling time (CSV, RData, RDS), or data.frame - `samp.columns`: a named list that should specify columns in sampling data. conclinkid and datetime are required to link sampling data to concentration data. conclinkid should match the id variable provided as samplinkid in the conc.columns argument. datetime is the date and time when blood samples were obtained. This can refer to a single date-time variable (datetime = date_time ) or two variables holding date and time separately (e.g., datetime = c(Date , Time )). - `samp.mod.list`: list of expressions, giving modifications to make - `check.path`: path to check directory, where check files are created. The default (NULL) will not produce any check files. - `failmiss_fn`: filename for data missing concentration date - `multsets_fn`: filename for data with multiple concentration sets - `faildup_fn`: filename for data with duplicate concentration observations - `drugname`: drug of interest, included in filename of check files. The default (NULL) will produce filenames without drugname included. - `LLOQ`: lower limit of concentration values; values below this are invalid - `demo.list`: demographic information; if available, concentration records must have a valid demo record - `demo.columns`: a named list that should specify columns in demographic data; id , is required. If idvisit is present in the concentration data, then it is required here too. ## Returns drug-level data set ## Details See EHR Vignette for Structured Data. ## Examples ```r # concentrations conc_data <- data.frame(mod_id = rep(1:3,each=4), mod_visit = rep(c(2,1,1),each=4), mod_id_visit = as.numeric(paste(rep(1:3,each=4), rep(c(2,1,1),each=4), sep=".")), samp = rep(1:4,times=3), drug_calc_conc=15*exp(-1*rep(1:4,times=3))+rnorm(12,0,0.1)) # sample times build_date <- function(x) format(seq(x, length.out=4, by="1 hour"), "%Y-%m-%d %H:%M") dates <- unlist(lapply(rep(Sys.time(),3), build_date)) samp_data <- data.frame(mod_id = rep(1:3,each=4), mod_visit = rep(c(2,1,1),each=4), mod_id_visit = as.numeric(paste(rep(1:3,each=4), rep(c(2,1,1),each=4), sep=".")), samp = rep(1:4,times=3), Sample.Collection.Date.and.Time = dates) run_DrugLevel( conc.path = conc_data, conc.columns = list( id = 'mod_id', idvisit = 'mod_id_visit', samplinkid = 'mod_id_event', conc = 'conc.level' ), conc.select = c('mod_id','mod_id_visit','samp','drug_calc_conc'), conc.rename = c(drug_calc_conc= 'conc.level', samp='event'), conc.mod.list = list(mod_id_event = expression(paste(mod_id_visit, event, sep = "_"))), samp.path = samp_data, samp.columns = list(conclinkid = 'mod_id_event', datetime = 'Sample.Collection.Date.and.Time'), samp.mod.list = list(mod_id_event = expression(paste(mod_id_visit, samp, sep = "_"))), drugname = 'drugnm', LLOQ = 0.05 ) # minimal example with data in required format conc_data <- conc_data[,c('mod_id','mod_id_visit','samp','drug_calc_conc')] conc_data[,'mod_id_event'] <- paste(conc_data[,'mod_id_visit'], conc_data[,'samp'], sep = "_") names(conc_data)[3:4] <- c('event','conc.level') samp_data[,'mod_id_event'] <- paste(samp_data[,'mod_id_visit'], samp_data[,'samp'], sep = "_") conc_samp_link <- match(conc_data[,'mod_id_event'], samp_data[,'mod_id_event']) conc_date <- samp_data[conc_samp_link, 'Sample.Collection.Date.and.Time'] conc_data[,'date.time'] <- as.POSIXct(conc_date) run_DrugLevel(conc_data, conc.columns = list( id = 'mod_id', idvisit = 'mod_id_visit', datetime = 'date.time', conc = 'conc.level' )) ```

run_DrugLevel function