Merge user-defined lookup table with the input dataset. Optionally print a list of records from the input dataset that do not have corresponding mapping from the lookup table.
Usage
derive_vars_merged_lookup(
dataset,
dataset_add,
by_vars,
order = NULL,
new_vars = NULL,
mode = NULL,
filter_add = NULL,
check_type = "warning",
duplicate_msg = NULL,
print_not_mapped = TRUE
)Arguments
- dataset
Input dataset
The variables specified by the
by_varsargument are expected to be in the dataset.- dataset_add
Lookup table
The variables specified by the
by_varsargument are expected.- by_vars
Grouping variables
The input dataset and the selected observations from the additional dataset are merged by the specified variables.
Variables can be renamed by naming the element, i.e.
by_vars = exprs(<name in input dataset> = <name in additional dataset>), similar to thedplyrjoins.Permitted Values: list of variables created by
exprs()e.g.exprs(USUBJID, VISIT)- order
Sort order
If the argument is set to a non-null value, for each by group the first or last observation from the additional dataset is selected with respect to the specified order.
Variables defined by the
new_varsargument can be used in the sort order.For handling of
NAs in sorting variables see Sort Order.Permitted Values: list of expressions created by
exprs(), e.g.,exprs(ADT, desc(AVAL))orNULL- new_vars
Variables to add
The specified variables from the additional dataset are added to the output dataset. Variables can be renamed by naming the element, i.e.,
new_vars = exprs(<new name> = <old name>).For example
new_vars = exprs(var1, var2)adds variablesvar1andvar2fromdataset_addto the input dataset.And
new_vars = exprs(var1, new_var2 = old_var2)takesvar1andold_var2fromdataset_addand adds them to the input dataset renamingold_var2tonew_var2.Values of the added variables can be modified by specifying an expression. For example,
new_vars = LASTRSP = exprs(str_to_upper(AVALC))adds the variableLASTRSPto the dataset and sets it to the upper case value ofAVALC.If the argument is not specified or set to
NULL, all variables from the additional dataset (dataset_add) are added.Permitted Values: list of variables or named expressions created by
exprs()- mode
Selection mode
Determines if the first or last observation is selected. If the
orderargument is specified,modemust be non-null.If the
orderargument is not specified, themodeargument is ignored.Permitted Values:
"first","last",NULL- filter_add
Filter for additional dataset (
dataset_add)Only observations fulfilling the specified condition are taken into account for merging. If the argument is not specified, all observations are considered.
Variables defined by the
new_varsargument can be used in the filter condition.Permitted Values: a condition
- check_type
Check uniqueness?
If
"warning"or"error"is specified, the specified message is issued if the observations of the (restricted) additional dataset are not unique with respect to the by variables and the order.If the
orderargument is not specified, thecheck_typeargument is ignored: if the observations of the (restricted) additional dataset are not unique with respect to the by variables, an error is issued.Permitted Values:
"none","warning","error"- duplicate_msg
Message of unique check
If the uniqueness check fails, the specified message is displayed.
Default:
paste( "Dataset {.arg dataset_add} contains duplicate records with respect to", "{.var {vars2chr(by_vars)}}." )- print_not_mapped
Print a list of unique
by_varsvalues that do not have corresponding records from the lookup table?Default:
TRUEPermitted Values:
TRUE,FALSE
Value
The output dataset contains all observations and variables of the
input dataset, and add the variables specified in new_vars from the lookup
table specified in dataset_add. Optionally prints a list of unique
by_vars values that do not have corresponding records
from the lookup table (by specifying print_not_mapped = TRUE).
See also
General Derivation Functions for all ADaMs that returns variable appended to dataset:
derive_var_extreme_flag(),
derive_var_joined_exist_flag(),
derive_var_merged_ef_msrc(),
derive_var_merged_exist_flag(),
derive_var_merged_summary(),
derive_var_obs_number(),
derive_var_relative_flag(),
derive_vars_cat(),
derive_vars_computed(),
derive_vars_joined(),
derive_vars_merged(),
derive_vars_transposed()
Examples
library(dplyr, warn.conflicts = FALSE)
vs <- tribble(
~STUDYID, ~DOMAIN, ~USUBJID, ~VISIT, ~VSTESTCD, ~VSTEST,
"PILOT01", "VS", "01-1028", "SCREENING", "HEIGHT", "Height",
"PILOT01", "VS", "01-1028", "SCREENING", "TEMP", "Temperature",
"PILOT01", "VS", "01-1028", "BASELINE", "TEMP", "Temperature",
"PILOT01", "VS", "01-1028", "WEEK 4", "TEMP", "Temperature",
"PILOT01", "VS", "01-1028", "SCREENING 1", "WEIGHT", "Weight",
"PILOT01", "VS", "01-1028", "BASELINE", "WEIGHT", "Weight",
"PILOT01", "VS", "01-1028", "WEEK 4", "WEIGHT", "Weight",
"PILOT01", "VS", "04-1325", "SCREENING", "HEIGHT", "Height",
"PILOT01", "VS", "04-1325", "SCREENING", "TEMP", "Temperature",
"PILOT01", "VS", "04-1325", "BASELINE", "TEMP", "Temperature",
"PILOT01", "VS", "04-1325", "WEEK 4", "TEMP", "Temperature",
"PILOT01", "VS", "04-1325", "SCREENING 1", "WEIGHT", "Weight",
"PILOT01", "VS", "04-1325", "BASELINE", "WEIGHT", "Weight",
"PILOT01", "VS", "04-1325", "WEEK 4", "WEIGHT", "Weight",
"PILOT01", "VS", "10-1027", "SCREENING", "HEIGHT", "Height",
"PILOT01", "VS", "10-1027", "SCREENING", "TEMP", "Temperature",
"PILOT01", "VS", "10-1027", "BASELINE", "TEMP", "Temperature",
"PILOT01", "VS", "10-1027", "WEEK 4", "TEMP", "Temperature",
"PILOT01", "VS", "10-1027", "SCREENING 1", "WEIGHT", "Weight",
"PILOT01", "VS", "10-1027", "BASELINE", "WEIGHT", "Weight",
"PILOT01", "VS", "10-1027", "WEEK 4", "WEIGHT", "Weight"
)
param_lookup <- tribble(
~VSTESTCD, ~VSTEST, ~PARAMCD, ~PARAM,
"SYSBP", "Systolic Blood Pressure", "SYSBP", "Syst Blood Pressure (mmHg)",
"WEIGHT", "Weight", "WEIGHT", "Weight (kg)",
"HEIGHT", "Height", "HEIGHT", "Height (cm)",
"TEMP", "Temperature", "TEMP", "Temperature (C)",
"MAP", "Mean Arterial Pressure", "MAP", "Mean Art Pressure (mmHg)",
"BMI", "Body Mass Index", "BMI", "Body Mass Index(kg/m^2)",
"BSA", "Body Surface Area", "BSA", "Body Surface Area(m^2)"
)
derive_vars_merged_lookup(
dataset = vs,
dataset_add = param_lookup,
by_vars = exprs(VSTESTCD),
new_vars = exprs(PARAMCD, PARAM),
print_not_mapped = TRUE
)
#> All `VSTESTCD` are mapped.
#> # A tibble: 21 × 8
#> STUDYID DOMAIN USUBJID VISIT VSTESTCD VSTEST PARAMCD PARAM
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 PILOT01 VS 01-1028 SCREENING HEIGHT Height HEIGHT Height (cm)
#> 2 PILOT01 VS 01-1028 SCREENING TEMP Temperature TEMP Temperature …
#> 3 PILOT01 VS 01-1028 BASELINE TEMP Temperature TEMP Temperature …
#> 4 PILOT01 VS 01-1028 WEEK 4 TEMP Temperature TEMP Temperature …
#> 5 PILOT01 VS 01-1028 SCREENING 1 WEIGHT Weight WEIGHT Weight (kg)
#> 6 PILOT01 VS 01-1028 BASELINE WEIGHT Weight WEIGHT Weight (kg)
#> 7 PILOT01 VS 01-1028 WEEK 4 WEIGHT Weight WEIGHT Weight (kg)
#> 8 PILOT01 VS 04-1325 SCREENING HEIGHT Height HEIGHT Height (cm)
#> 9 PILOT01 VS 04-1325 SCREENING TEMP Temperature TEMP Temperature …
#> 10 PILOT01 VS 04-1325 BASELINE TEMP Temperature TEMP Temperature …
#> # ℹ 11 more rows