From b44fd3d99ad43001d91cda8daefe4bac33cf2865 Mon Sep 17 00:00:00 2001 From: jim Date: Fri, 25 Oct 2024 13:37:11 -0700 Subject: [PATCH] Closes #2526 data raw data round/2 (#2539) * Corrected code for data-raw/create_admiral_*.R functions. But throws errors. * Delete data-backup directory * chore: #2526 remove old admiral adlb script; push up newly run data * chore: #2526 rename file to be explicit in what it is doing; reran queries code and some fun things were found!! /s --------- Co-authored-by: Ben Straub --- data-backup/admiral_adlb.rda | Bin 110433 -> 0 bytes data-backup/admiral_adsl.rda | Bin 12508 -> 0 bytes data-raw/admiral_adlb.R | 466 ------------------ data-raw/create_admiral_adlb.R | 103 +--- data-raw/create_admiral_adsl.R | 83 +--- ...erive_single_dose.R => create_ex_single.R} | 0 .../{example_qs.R => create_example_qs.R} | 0 ...urce.R => create_queries_and_queries_mh.R} | 9 +- data/admiral_adlb.rda | Bin 102552 -> 102504 bytes data/queries.rda | Bin 2087 -> 761 bytes data/queries_mh.rda | Bin 2004 -> 739 bytes 11 files changed, 37 insertions(+), 624 deletions(-) delete mode 100644 data-backup/admiral_adlb.rda delete mode 100644 data-backup/admiral_adsl.rda delete mode 100644 data-raw/admiral_adlb.R rename data-raw/{derive_single_dose.R => create_ex_single.R} (100%) rename data-raw/{example_qs.R => create_example_qs.R} (100%) rename data-raw/{example_query_source.R => create_queries_and_queries_mh.R} (93%) diff --git a/data-backup/admiral_adlb.rda b/data-backup/admiral_adlb.rda deleted file mode 100644 index 9bf8663e65d840383e87d90bb6593075300862ba..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 110433 zcmafZWmp?b(=Kf(6fFd|776Yag7v{6fdIk1cnJ{PDSdDcg#@>vfdseUE$&btP#lUE zF9qs--_!5N?=#n4yEDIbcXqCsd+%Kh8xKWkb!!1rYi645+J{re|Ni&?Cm*pw50Z!r z#)?8b+$7iSzEO9;Op+%tySGsnH%I-Ki1`P@Koay}+rwL>52c-bH1G=A5zACrD37n5+U)q zjO+G78Gj;qs*#P`e_&GcR;3D00;RjBEn!J7a=X9CN@kt1H3!ev5Q$d0jJ7T#c?d9` zZcOYsDbhr`lC@4Hd#eUWx>qx%VhpMxq&Lh`6AYVi!or(xLr9)S#%O-xA}7wvk&rco zU-d^0mywVV=Sk*CNPb0n43LnJxT$er{tj{^B-BZe86^^ut!NV3XeGuV5)$5z-x$jt zm!D=6yrQ}p^%SJ;Z4av-4cdBE0e~?w_et{OG!W%jn6%tNISA`Pfii+I7?~Qd#t+cP 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- by_vars = exprs(STUDYID, USUBJID) - ) %>% - ## Calculate ADT, ADY ---- - derive_vars_dt( - new_vars_prefix = "A", - dtc = LBDTC - ) %>% - derive_vars_dy(reference_date = TRTSDT, source_vars = exprs(ADT)) - -adlb <- adlb %>% - ## Add PARAMCD PARAM and PARAMN - from LOOK-UP table ---- - # Replace with PARAMCD lookup function - derive_vars_merged_lookup( - dataset_add = param_lookup, - new_vars = exprs(PARAMCD, PARAM, PARAMN), - by_vars = exprs(LBTESTCD), - check_type = "none", - print_not_mapped = FALSE - ) %>% - ## Calculate PARCAT1 AVAL AVALC ANRLO ANRHI ---- - mutate( - PARCAT1 = LBCAT, - AVAL = LBSTRESN, - # Only populate AVALC if character value is non-redundant with AVAL - AVALC = ifelse( - is.na(LBSTRESN) | as.character(LBSTRESN) != LBSTRESC, - LBSTRESC, - NA - ), - ANRLO = LBSTNRLO, - ANRHI = LBSTNRHI - ) - -# Derive Absolute values from fractional Differentials using WBC -# Only derive where absolute values do not already exist -# Need to populate ANRLO and ANRHI for newly created records -adlb <- adlb %>% - # Derive absolute Basophils - derive_param_wbc_abs( - by_vars = exprs(STUDYID, USUBJID, !!!adsl_vars, DOMAIN, VISIT, VISITNUM, ADT, ADY), - set_values_to = exprs( - PARAMCD = "BASO", - PARAM = "Basophils Abs (10^9/L)", - PARAMN = 6, - DTYPE = "CALCULATION", - PARCAT1 = "HEMATOLOGY" - ), - get_unit_expr = extract_unit(PARAM), - diff_code = "BASOLE" - ) %>% - # Derive absolute Lymphocytes - derive_param_wbc_abs( - by_vars = exprs(STUDYID, USUBJID, !!!adsl_vars, DOMAIN, VISIT, VISITNUM, ADT, ADY), - set_values_to = exprs( - PARAMCD = "LYMPH", - PARAM = "Lymphocytes Abs (10^9/L)", - PARAMN = 25, - DTYPE = "CALCULATION", - PARCAT1 = "HEMATOLOGY" - ), - get_unit_expr = extract_unit(PARAM), - diff_code = "LYMPHLE" - ) - -## Get Visit Info ---- -# See also the "Visit and Period Variables" vignette -# (https://pharmaverse.github.io/admiral/articles/visits_periods.html#visits) -adlb <- adlb %>% - # Derive Timing - mutate( - AVISIT = case_when( - str_detect(VISIT, "SCREEN") ~ "Baseline", - !is.na(VISIT) ~ str_to_title(VISIT), - TRUE ~ NA_character_ - ), - AVISITN = case_when( - AVISIT == "Baseline" ~ 0, - !is.na(VISITNUM) ~ VISITNUM - ) - ) - -adlb <- adlb %>% - ## Calculate ONTRTFL ---- - derive_var_ontrtfl( - start_date = ADT, - ref_start_date = TRTSDT, - ref_end_date = TRTEDT, - filter_pre_timepoint = AVISIT == "Baseline" - ) - -## Calculate ANRIND : requires the reference ranges ANRLO, ANRHI ---- -adlb <- adlb %>% - derive_var_anrind() - -## Derive baseline flags ---- -adlb <- adlb %>% - # Calculate BASETYPE - mutate( - BASETYPE = "LAST" - ) %>% - # Calculate ABLFL - restrict_derivation( - derivation = derive_var_extreme_flag, - args = params( - by_vars = exprs(STUDYID, USUBJID, BASETYPE, PARAMCD), - order = exprs(ADT, VISITNUM, LBSEQ), - new_var = ABLFL, - mode = "last" - ), - filter = (!is.na(AVAL) & ADT <= TRTSDT & !is.na(BASETYPE)) - ) - -## Derive baseline information ---- -adlb <- adlb %>% - # Calculate BASE - derive_var_base( - by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE), - source_var = AVAL, - new_var = BASE - ) %>% - # Calculate BASEC - derive_var_base( - by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE), - source_var = AVALC, - new_var = BASEC - ) %>% - # Calculate BNRIND - derive_var_base( - by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE), - source_var = ANRIND, - new_var = BNRIND - ) %>% # nolint start - # Calculate CHG for post-baseline records - # The decision on how to populate pre-baseline and baseline values of CHG is left to producer choice - # nolint end - restrict_derivation( - derivation = derive_var_chg, - filter = AVISITN > 0 - ) %>% # nolint start - # Calculate PCHG for post-baseline records - # The decision on how to populate pre-baseline and baseline values of PCHG is left to producer choice - # nolint end - restrict_derivation( - derivation = derive_var_pchg, - filter = AVISITN > 0 - ) - -## Calculate lab grading ---- - -# Assign ATOXDSCL and ATOXDSCH to hold lab grading terms -# ATOXDSCL and ATOXDSCH hold terms defined by NCI-CTCAEv4. -# See (https://pharmaverse.github.io/admiral/articles/lab_grading.html#implement_ctcv4) -grade_lookup <- tibble::tribble( - ~PARAMCD, ~ATOXDSCL, ~ATOXDSCH, - "ALB", "Hypoalbuminemia", NA_character_, - "ALKPH", NA_character_, "Alkaline phosphatase increased", - "ALT", NA_character_, "Alanine aminotransferase increased", - "AST", NA_character_, "Aspartate aminotransferase increased", - "BILI", NA_character_, "Blood bilirubin increased", - "CA", "Hypocalcemia", "Hypercalcemia", - "CHOLES", NA_character_, "Cholesterol high", - "CK", NA_character_, "CPK increased", - "CREAT", NA_character_, "Creatinine increased", - "GGT", NA_character_, "GGT increased", - "GLUC", "Hypoglycemia", "Hyperglycemia", - "HGB", "Anemia", "Hemoglobin increased", - "POTAS", "Hypokalemia", "Hyperkalemia", - "LYMPH", "CD4 lymphocytes decreased", NA_character_, - "PHOS", "Hypophosphatemia", NA_character_, - "PLAT", "Platelet count decreased", NA_character_, - "SODIUM", "Hyponatremia", "Hypernatremia", - "WBC", "White blood cell decreased", "Leukocytosis", -) - -# Assign grade criteria -# metadata atoxgr_criteria_ctcv4 used to implement NCI-CTCAEv4 -# user could change to atoxgr_criteria_ctcv5 to implement NCI-CTCAEv5 -# Note: Hyperglycemia and Hypophosphatemia not defined in NCI-CTCAEv5 so -# user would need to amend look-up table grade_lookup -# See (https://pharmaverse.github.io/admiral/articles/lab_grading.html#implement_ctcv5) -grade_crit <- atoxgr_criteria_ctcv4 - - -# Add ATOXDSCL and ATOXDSCH -adlb <- adlb %>% - derive_vars_merged( - dataset_add = grade_lookup, - by_vars = exprs(PARAMCD) - ) %>% - # Derive toxicity grade for low values ATOXGRL - - derive_var_atoxgr_dir( - meta_criteria = grade_crit, - new_var = ATOXGRL, - tox_description_var = ATOXDSCL, - criteria_direction = "L", - get_unit_expr = extract_unit(PARAM) - ) %>% - # Derive toxicity grade for low values ATOXGRH - # default metadata atoxgr_criteria_ctcv4 used - derive_var_atoxgr_dir( - meta_criteria = grade_crit, - new_var = ATOXGRH, - tox_description_var = ATOXDSCH, - criteria_direction = "H", - get_unit_expr = extract_unit(PARAM) - ) %>% - # (Optional) derive overall grade ATOXGR (combining ATOXGRL and ATOXGRH) - derive_var_atoxgr() %>% - # Derive baseline toxicity grade for low values BTOXGRL - derive_var_base( - by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE), - source_var = ATOXGRL, - new_var = BTOXGRL - ) %>% - # Derive baseline toxicity grade for high values BTOXGRH - derive_var_base( - by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE), - source_var = ATOXGRH, - new_var = BTOXGRH - ) %>% - # Derive baseline toxicity grade for for overall grade BTOXGR - derive_var_base( - by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE), - source_var = ATOXGR, - new_var = BTOXGR - ) - - -## Calculate R2BASE, R2ANRLO and R2ANRHI ---- -adlb <- adlb %>% - derive_var_analysis_ratio( - numer_var = AVAL, - denom_var = BASE - ) %>% - derive_var_analysis_ratio( - numer_var = AVAL, - denom_var = ANRLO - ) %>% - derive_var_analysis_ratio( - numer_var = AVAL, - denom_var = ANRHI - ) - -## SHIFT derivation ---- -adlb <- adlb %>% - # Derive shift from baseline for analysis indicator - derive_var_shift( - new_var = SHIFT1, - from_var = BNRIND, - to_var = ANRIND - ) %>% - # Derive shift from baseline for overall grade - restrict_derivation( - derivation = derive_var_shift, - args = params( - new_var = SHIFT2, - from_var = BTOXGR, - to_var = ATOXGR - ), - filter = !is.na(ATOXDSCL) | !is.na(ATOXDSCH) - ) - -## Flag variables (ANL01FL, LVOTFL) ---- -# ANL01FL: Flag last result within an AVISIT for post-baseline records -# LVOTFL: Flag last valid on-treatment record -adlb <- adlb %>% - restrict_derivation( - derivation = derive_var_extreme_flag, - args = params( - by_vars = exprs(USUBJID, PARAMCD, AVISIT), - order = exprs(ADT, AVAL), - new_var = ANL01FL, - mode = "last" - ), - filter = !is.na(AVISITN) & ONTRTFL == "Y" - ) %>% - restrict_derivation( - derivation = derive_var_extreme_flag, - args = params( - by_vars = exprs(USUBJID, PARAMCD), - order = exprs(ADT, AVAL), - new_var = LVOTFL, - mode = "last" - ), - filter = ONTRTFL == "Y" - ) - -## Get treatment information ---- -# See also the "Visit and Period Variables" vignette -# (https://pharmaverse.github.io/admiral/articles/visits_periods.html#treatment_bds) -adlb <- adlb %>% - # Assign TRTA, TRTP - mutate( - TRTP = TRT01P, - TRTA = TRT01A - ) - -## Get extreme values ---- -adlb <- adlb %>% - # get MINIMUM value - derive_extreme_records( - dataset_add = adlb, - by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE), - order = exprs(AVAL, ADT, AVISITN), - mode = "first", - filter_add = (!is.na(AVAL) & ONTRTFL == "Y"), - set_values_to = exprs( - AVISITN = 9997, - AVISIT = "POST-BASELINE MINIMUM", - DTYPE = "MINIMUM" - ) - ) %>% - # get MAXIMUM value - derive_extreme_records( - dataset_add = adlb, - by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE), - order = exprs(desc(AVAL), ADT, AVISITN), - mode = "first", - filter_add = (!is.na(AVAL) & ONTRTFL == "Y"), - set_values_to = exprs( - AVISITN = 9998, - AVISIT = "POST-BASELINE MAXIMUM", - DTYPE = "MAXIMUM" - ) - ) %>% - # get LOV value - derive_extreme_records( - dataset_add = adlb, - by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE), - order = exprs(ADT, AVISITN), - mode = "last", - filter_add = (ONTRTFL == "Y"), - set_values_to = exprs( - AVISITN = 9999, - AVISIT = "POST-BASELINE LAST", - DTYPE = "LOV" - ) - ) - -## Get ASEQ ---- -adlb <- adlb %>% - # Calculate ASEQ - derive_var_obs_number( - new_var = ASEQ, - by_vars = exprs(STUDYID, USUBJID), - order = exprs(PARAMCD, ADT, AVISITN, VISITNUM), - check_type = "error" - ) - -# Add all ADSL variables -adlb <- adlb %>% - derive_vars_merged( - dataset_add = select(adsl, !!!negate_vars(adsl_vars)), - by_vars = exprs(STUDYID, USUBJID) - ) - -# Final Steps, Select final variables and Add labels -# This process will be based on your metadata, no example given for this reason -# ... - -# Save output ---- - -# Change to whichever directory you want to save the dataset in -dir <- tools::R_user_dir("admiral_templates_data", which = "cache") -if (!file.exists(dir)) { - # Create the folder - dir.create(dir, recursive = TRUE, showWarnings = FALSE) -} -save(adlb, file = file.path(dir, "adlb.rda"), compress = "bzip2") diff --git a/data-raw/create_admiral_adlb.R b/data-raw/create_admiral_adlb.R index 779d912e17..a92a07e45e 100644 --- a/data-raw/create_admiral_adlb.R +++ b/data-raw/create_admiral_adlb.R @@ -1,61 +1,13 @@ # Create dataset: data/admiral_adlb.rda # This script: create_admiral_adlb.R creates dataset data/admiral_adlb.rda. -# -# Preliminary -library(diffdf) # nolint +# Create dataset data/admiral_adlb.rda -# To clarify directories (can be removed) -# nolint start: object_name_linter -CACHE_DIR <- "~/.cache/R/admiral_templates_data/" -DATA_DIR <- "data-dir" -DATA_RAW <- "data-raw" -TEMPLATE_DIR <- "inst/templates/" +# Run template script to create adlb +source("inst/templates/ad_adlb.R", echo = TRUE) # nolint -# clean CACHE_DIR -THE_FILE <- paste0(CACHE_DIR, "/adlb.rda") -THE_FILE <- paste0(CACHE_DIR, "/adsl.rda") -if (file.exists(THE_FILE)) file.remove(THE_FILE) -# nolint end - -# -# STEPS -# -# First, use template to create the R script (in data-raw/admiral_adlb.R). -# Next, source this script and create the data (~/.cache/R/admiral_template_data/admiral_adlb.rda) -# Finally, shorten this data (now ~ 1.2 MB) by selecting only certain USUBJID - -# orignal method - OMIT -if (FALSE) { - # ### original mehtod (method 1) - # # First, create the R script (from a template) - adam_name <- "adlb" - save_path <- paste0("./data-raw/admiral_", adam_name, ".R") - use_ad_template( - adam_name = adam_name, - save_path = save_path, - open = FALSE, - overwrite = TRUE - ) - # Second, source the script and save data in .cache - source("data-raw/admiral_adlb.R") # nolint - load("~/.cache/R/admiral_templates_data/adlb.rda") -} - -# -# Instead, USE template, as recommened by Buzz -# -source(paste0(TEMPLATE_DIR, "/ad_adlb.R")) # nolint -load(paste0(CACHE_DIR, "adlb.rda")) - -# -# limit rows, by selecting only these USUBJID -# -#' 01-701-1015, 01-701-1023, 01-701-1028, 01-701-1033, -#' 01-701-1034, 01-701-1047, 01-701-1097, 01-705-1186, -#' 01-705-1292, 01-705-1310, 01-708-1286 - -usubjid <- +# Limit rows by selecting only these USUBJIDs +usubjids <- c( "01-701-1015", "01-701-1023", @@ -70,42 +22,17 @@ usubjid <- "01-708-1286" ) -# prepare for inner join -user <- tibble( - USUBJID = usubjid -) -result <- inner_join(adlb, user) -admiral_adlb <- result -admiral_adlb - -# -# Finally, save reduced ds -# -use_data(admiral_adlb, overwrite = TRUE) - -# -# TEST - is dataset identical to .... backup of unaltered dataset -# -e1 <- new.env() -e2 <- new.env() -load("data/admiral_adlb.rda", e1) - -# CHANGE to YOUR location of original dataset -load("data-backup/admiral_adlb.rda", e2) - -# compare field names -t <- tibble(e1 = names(e1$admiral_adlb), e2 = names(e2$admiral_adlb)) -t |> print(n = 111) +admiral_adlb <- filter(adlb, USUBJID %in% usubjids) -identical(e1$admiral_adlb, e2$admiral_adlb) -diffdf(e1$admiral_adlb, e2$admiral_adlb) +# Get previous dataset for comparison +adlb_old <- admiral::admiral_adlb -## Capture diffdf to file +# Finally, save reduced dataset +usethis::use_data(admiral_adlb, overwrite = TRUE) -capture.output( - diffdf( - compare = e1$admiral_adlb, base = e2$admiral_adlb, - keys = c("STUDYID", "DOMAIN", "USUBJID", "AVAL", "VISIT") - ), - file = "data-raw/diffdf_adlb_23SEPT" +# Compare with previous version +diffdf::diffdf( + base = adlb_old, + compare = admiral_adlb, + keys = c("USUBJID", "PARAMCD", "AVISIT", "ADT") ) diff --git a/data-raw/create_admiral_adsl.R b/data-raw/create_admiral_adsl.R index 2649141e10..a2077f883c 100644 --- a/data-raw/create_admiral_adsl.R +++ b/data-raw/create_admiral_adsl.R @@ -1,78 +1,23 @@ # Create dataset: data/admiral_adsl.rda -# This script: create_admiral_adsl.R creates dataset data/admiral_adsl.rda. +# This script, create_admiral_adsl.R, creates dataset data/admiral_adsl.rda. # -# Preliminary -library(diffdf) # nolint +# Create dataset data/admiral_adsl.rda +# Run template script to create adsl +source("inst/templates/ad_adsl.R", echo = TRUE) # nolint -# nolint start: object_name_linter. -# To clarify directories (can be removed) -CACHE_DIR <- "~/.cache/R/admiral_templates_data/" -DATA_DIR <- "data-dir" -DATA_RAW <- "data-raw" -TEMPLATE_DIR <- "inst/templates/" +admiral_adsl <- adsl # use correct name -# clean CACHE_DIR -THE_FILE <- paste0(CACHE_DIR, "/adlb.rda") -THE_FILE <- paste0(CACHE_DIR, "/adsl.rda") -if (file.exists(THE_FILE)) file.remove(THE_FILE) -# nolint end - -# -# STEPS -# -# First, use template to create the R script (in data-raw/admiral_adlb.R). -# Next, source this script and create the data (~/.cache/R/admiral_template_data/admiral_adlb.rda) -# Finally, shorten this data (now ~ 1.2 MB) by selecting only certain USUBJID - -# OMIT -- orignal method - OMIT -if (FALSE) { - # ### original mehtod (method 1) - # # First, create the R script (from a template) - adam_name <- "adlb" - save_path <- paste0("./data-raw/admiral_", adam_name, ".R") - use_ad_template( - adam_name = adam_name, - save_path = save_path, - open = FALSE, - overwrite = TRUE - ) - # Second, source the script and save data in .cache - source("data-raw/admiral_adlb.R") # nolint - load("~/.cache/R/admiral_templates_data/adlb.rda") -} - -# -# -# Instead, USE template, as recommened by Buzz -# -source(paste0(TEMPLATE_DIR, "/ad_adsl.R")) # nolint -load(paste0(CACHE_DIR, "adsl.rda")) -admiral_adsl <- adsl - -# -# Finally, save reduced ds -# -use_data(admiral_adsl, overwrite = TRUE) - -# -# TEST - is dataset identical to .... backup of unaltered dataset -# -e1 <- new.env() -e2 <- new.env() -load("data/admiral_adsl.rda", e1) - -# CHANGE to YOUR location of original dataset -load("data-backup/admiral_adsl.rda", e2) +# Get previous dataset for comparison +adsl_old <- admiral::admiral_adsl +# Finally, save reduced dataset +usethis::use_data(admiral_adsl, overwrite = TRUE) -identical(e1$admiral_adsl, e2$admiral_adsl) -diffdf(compare = e1$admiral_adsl, base = e2$admiral_adsl, keys = c("STUDYID", "USUBJID")) -capture.output( - diffdf( - compare = e1$admiral_adsl, base = e2$admiral_adsl, - keys = c("STUDYID", "USUBJID") - ), - file = "data-raw/diffdf_23SEPT" +# Compare with previous version +diffdf::diffdf( + base = adsl_old, + compare = admiral_adsl, + keys = c("STUDYID", "USUBJID") ) diff --git a/data-raw/derive_single_dose.R b/data-raw/create_ex_single.R similarity index 100% rename from data-raw/derive_single_dose.R rename to data-raw/create_ex_single.R diff --git a/data-raw/example_qs.R b/data-raw/create_example_qs.R similarity index 100% rename from data-raw/example_qs.R rename to data-raw/create_example_qs.R diff --git a/data-raw/example_query_source.R b/data-raw/create_queries_and_queries_mh.R similarity index 93% rename from data-raw/example_query_source.R rename to data-raw/create_queries_and_queries_mh.R index b598fe62af..e63259ff2b 100644 --- a/data-raw/example_query_source.R +++ b/data-raw/create_queries_and_queries_mh.R @@ -54,13 +54,20 @@ adae <- tibble::tribble( "APPLICATION SITE ERYTHEMA", "Application site erythema", 1 ) +# create queries.rda in data/ +usethis::use_data(queries, overwrite = TRUE) + # try below: derive_vars_query(adae, queries) - # example to use for ADMH: queries_mh <- queries %>% filter(SRCVAR %in% c("AELLT", "AEDECOD")) %>% mutate(SRCVAR = ifelse(SRCVAR == "AELLT", "MHLLT", "MHDECOD")) +usethis::use_data(queries_mh, overwrite = TRUE) + +source("inst/templates/ad_admh.R", echo = TRUE) # nolint + +# Currently producing an error derive_vars_query(admh, queries_mh) diff --git a/data/admiral_adlb.rda b/data/admiral_adlb.rda 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