Amalgamate domain data and pivot wider to convert the IDDO-SDTM format data into a more analysable format. Function works on one domain and requires the two letter domain name as well as the domain data file.
Usage
prepare_domain(
domain,
data,
include_LOC = FALSE,
include_METHOD = FALSE,
variables_include = c(),
timing_variables = c(str_c(domain, "HR"), str_c(domain, "DY"), str_c(domain, "STDY"),
"VISITDY", "VISITNUM", "VISIT", "EPOCH", str_c(domain, "EVLINT"), str_c(domain,
"EVINTX")),
values_fn = first,
print_messages = TRUE
)Arguments
- domain
Character. The two letter domain name of the data.
- data
Domain data frame.
- include_LOC
Boolean. Should the location (–LOC) be included in the output. Default is FALSE.
- include_METHOD
Boolean. Should the method (–METHOD) be included in the output. Default is FALSE.
- variables_include
Character list. List of variables to include in the output. Default is to include all available variables.
- timing_variables
Character list. List of timing variables which are to be used to separate time points, this is hierarchical so the order is taken into account. Default is: –HR, –DY, –STDY, VISITDY, VISITNUM, VISIT, EPOCH, –EVLINT, –EVINTX.
(using default for example) Each row will be initially summarised based on the –HR (study hour) variable, if that is missing then the –DY (study day) variable is used, and so on. The output will be one row per participant, per time point, where the time point for each row is the first available variable listed in timing_variables.
- values_fn
Function. The function which will determine which data row is used in the output, in the event there are multiple rows for the same subject with the same time points (as listed in timing_variables). Default is first(), i.e. if there is two rows from the same day and time, the first record will be taken, the second will be dropped. Choice of timing_variables will impact the number of rows affected.
- print_messages
Boolean. Should messages from the function be generated and shown in the user's console. Default is TRUE.
Examples
prepare_domain("DM", DM_RPTESTB)
#> # A tibble: 3 × 21
#> STUDYID DOMAIN USUBJID SUBJID RFSTDTC DTHDTC DTHFL SITEID INVID INVNAM BRTHDTC
#> <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr> <lgl> <lgl> <lgl>
#> 1 RPTESTB DM RPTEST… 1 2023/01 2023/… Y OXFORD NA NA NA
#> 2 RPTESTB DM RPTEST… 2 2023/01 NA NA OXFORD NA NA NA
#> 3 RPTESTB DM RPTEST… 3 2023/02 NA NA OXFORD NA NA NA
#> # ℹ 10 more variables: AGE_YEARS <dbl>, AGETXT <lgl>, SEX <chr>, RACE <chr>,
#> # ETHNIC <chr>, ARMCD <chr>, ARM <chr>, COUNTRY <chr>, DMDTC <chr>,
#> # DMDY <dbl>
# Select just ARMCD, AGE & SEX
prepare_domain("DM", DM_RPTESTB, variables_include = c("ARMCD", "AGE", "SEX"))
#> # A tibble: 3 × 5
#> STUDYID USUBJID ARMCD AGE SEX
#> <chr> <chr> <chr> <dbl> <chr>
#> 1 RPTESTB RPTESTB_001 PBO 67 F
#> 2 RPTESTB RPTESTB_002 TRT 18 F
#> 3 RPTESTB RPTESTB_003 TRT 48 M
# Change which timing_variables are used to summarise the data
prepare_domain("lb", LB_RPTESTB, timing_variables = c("VISITNUM", "VISITDY"))
#> [1] "Number of rows where values_fn has been used to pick record in the LB domain: 0"
#> # A tibble: 9 × 7
#> STUDYID USUBJID TIME TIME_SOURCE HCG_NA `HGB_g/L` `PLAT_10^9/L`
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 RPTESTB RPTESTB_001 1 VISITNUM NA 95 NA
#> 2 RPTESTB RPTESTB_001 2 VISITNUM NA NA 181
#> 3 RPTESTB RPTESTB_001 3 VISITNUM NA 88 NA
#> 4 RPTESTB RPTESTB_002 1 VISITNUM NEGATIVE 101 NA
#> 5 RPTESTB RPTESTB_002 2 VISITNUM NA NA 100
#> 6 RPTESTB RPTESTB_002 3 VISITNUM NA 99 NA
#> 7 RPTESTB RPTESTB_003 1 VISITNUM NA 98 NA
#> 8 RPTESTB RPTESTB_003 2 VISITNUM NA NA 90
#> 9 RPTESTB RPTESTB_003 3 VISITNUM NA 102 NA
# Include location in the output and change the values_fn to select the last result
prepare_domain("vs", VS_RPTESTB, include_LOC = TRUE, values_fn = dplyr::last)
#> [1] "Number of rows where values_fn has been used to pick record in the VS domain: 0"
#> # A tibble: 9 × 9
#> STUDYID USUBJID TIME TIME_SOURCE `BMI_NA_kg/m2` HEIGHT_NA_cm TEMP_AXILLA_C
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 RPTESTB RPTESTB_0… 1 DY 21.5 167 36.2
#> 2 RPTESTB RPTESTB_0… 3 DY NA NA 37.4
#> 3 RPTESTB RPTESTB_0… 42 DY NA NA 37.5
#> 4 RPTESTB RPTESTB_0… 1 DY 20.5 143 NA
#> 5 RPTESTB RPTESTB_0… 4 DY NA NA NA
#> 6 RPTESTB RPTESTB_0… 40 DY NA NA NA
#> 7 RPTESTB RPTESTB_0… 2 DY 0.01 84 37.2
#> 8 RPTESTB RPTESTB_0… 5 DY NA NA 37.1
#> 9 RPTESTB RPTESTB_0… 3 VISITNUM NA NA 37.7
#> # ℹ 2 more variables: TEMP_ORAL_CAVITY_C <chr>, WEIGHT_NA_kg <chr>