![[Deprecated]](figures/lifecycle-deprecated.svg)
The get_summary_records() has been
deprecated in favor of derive_summary_records() (call it with the dataset_add
argument and without the dataset argument).
It is not uncommon to have an analysis need whereby one needs to derive an
analysis value (AVAL) from multiple records. The ADaM basic dataset
structure variable DTYPE is available to indicate when a new derived
records has been added to a dataset.
get_summary_records(dataset, by_vars, filter = NULL, set_values_to = NULL)Arguments
- dataset
Input dataset
The variables specified by the
by_varsargument are expected to be in the dataset.- Default value
none
- by_vars
Grouping variables
Variables to consider for generation of groupwise summary records.
- Default value
none
- filter
Filter condition as logical expression to apply during summary calculation. By default, filtering expressions are computed within
by_varsas this will help when an aggregating, lagging, or ranking function is involved.For example,
filter_rows = (AVAL > mean(AVAL, na.rm = TRUE))will filter all AVAL values greater than mean of AVAL with inby_vars.filter_rows = (dplyr::n() > 2)will filter n count ofby_varsgreater than 2.
- Default value
NULL
- set_values_to
Variables to be set
The specified variables are set to the specified values for the new observations.
Set a list of variables to some specified value for the new records
LHS refer to a variable.
RHS refers to the values to set to the variable. This can be a string, a symbol, a numeric value, an expression or NA. If summary functions are used, the values are summarized by the variables specified for
by_vars.
For example:
set_values_to = exprs( AVAL = sum(AVAL), PARAMCD = "TDOSE", PARCAT1 = "OVERALL" )- Default value
NULL
Value
A data frame of derived records.
Details
This function only creates derived observations and does not append them
to the original dataset observations. If you would like to this instead,
see the derive_summary_records() function.
See also
derive_summary_records(), derive_var_merged_summary()
Other deprecated:
call_user_fun(),
date_source(),
derive_param_extreme_record(),
derive_var_dthcaus(),
derive_var_extreme_dt(),
derive_var_extreme_dtm(),
dthcaus_source()
Examples
library(tibble)
adeg <- tribble(
~USUBJID, ~EGSEQ, ~PARAM, ~AVISIT, ~EGDTC, ~AVAL, ~TRTA,
"XYZ-1001", 1, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:50", 385, NA_character_,
"XYZ-1001", 2, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:52", 399, NA_character_,
"XYZ-1001", 3, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:56", 396, NA_character_,
"XYZ-1001", 4, "QTcF Int. (msec)", "Visit 2", "2016-03-08T09:45", 384, "Placebo",
"XYZ-1001", 5, "QTcF Int. (msec)", "Visit 2", "2016-03-08T09:48", 393, "Placebo",
"XYZ-1001", 6, "QTcF Int. (msec)", "Visit 2", "2016-03-08T09:51", 388, "Placebo",
"XYZ-1001", 7, "QTcF Int. (msec)", "Visit 3", "2016-03-22T10:45", 385, "Placebo",
"XYZ-1001", 8, "QTcF Int. (msec)", "Visit 3", "2016-03-22T10:48", 394, "Placebo",
"XYZ-1001", 9, "QTcF Int. (msec)", "Visit 3", "2016-03-22T10:51", 402, "Placebo",
"XYZ-1002", 1, "QTcF Int. (msec)", "Baseline", "2016-02-22T07:58", 399, NA_character_,
"XYZ-1002", 2, "QTcF Int. (msec)", "Baseline", "2016-02-22T07:58", 410, NA_character_,
"XYZ-1002", 3, "QTcF Int. (msec)", "Baseline", "2016-02-22T08:01", 392, NA_character_,
"XYZ-1002", 4, "QTcF Int. (msec)", "Visit 2", "2016-03-06T09:50", 401, "Active 20mg",
"XYZ-1002", 5, "QTcF Int. (msec)", "Visit 2", "2016-03-06T09:53", 407, "Active 20mg",
"XYZ-1002", 6, "QTcF Int. (msec)", "Visit 2", "2016-03-06T09:56", 400, "Active 20mg",
"XYZ-1002", 7, "QTcF Int. (msec)", "Visit 3", "2016-03-24T10:50", 412, "Active 20mg",
"XYZ-1002", 8, "QTcF Int. (msec)", "Visit 3", "2016-03-24T10:53", 414, "Active 20mg",
"XYZ-1002", 9, "QTcF Int. (msec)", "Visit 3", "2016-03-24T10:56", 402, "Active 20mg"
)
# Summarize the average of the triplicate ECG interval values (AVAL)
get_summary_records(
adeg,
by_vars = exprs(USUBJID, PARAM, AVISIT),
set_values_to = exprs(
AVAL = mean(AVAL, na.rm = TRUE),
DTYPE = "AVERAGE"
)
)
#> `get_summary_records()` was deprecated in admiral 1.2.0.
#> ℹ Please use `derive_summary_records()` instead.
#> ✖ This message will turn into a warning at the beginning of 2026.
#> ℹ See admiral's deprecation guidance:
#> https://pharmaverse.github.io/admiraldev/dev/articles/programming_strategy.html#deprecation
#> # A tibble: 6 × 5
#> USUBJID PARAM AVISIT AVAL DTYPE
#> <chr> <chr> <chr> <dbl> <chr>
#> 1 XYZ-1001 QTcF Int. (msec) Baseline 393. AVERAGE
#> 2 XYZ-1001 QTcF Int. (msec) Visit 2 388. AVERAGE
#> 3 XYZ-1001 QTcF Int. (msec) Visit 3 394. AVERAGE
#> 4 XYZ-1002 QTcF Int. (msec) Baseline 400. AVERAGE
#> 5 XYZ-1002 QTcF Int. (msec) Visit 2 403. AVERAGE
#> 6 XYZ-1002 QTcF Int. (msec) Visit 3 409. AVERAGE
# Derive more than one summary variable
get_summary_records(
adeg,
by_vars = exprs(USUBJID, PARAM, AVISIT),
set_values_to = exprs(
AVAL = mean(AVAL),
ASTDTM = min(convert_dtc_to_dtm(EGDTC)),
AENDTM = max(convert_dtc_to_dtm(EGDTC)),
DTYPE = "AVERAGE"
)
)
#> # A tibble: 6 × 7
#> USUBJID PARAM AVISIT AVAL ASTDTM AENDTM DTYPE
#> <chr> <chr> <chr> <dbl> <dttm> <dttm> <chr>
#> 1 XYZ-1001 QTcF Int.… Basel… 393. 2016-02-24 07:50:00 2016-02-24 07:56:00 AVER…
#> 2 XYZ-1001 QTcF Int.… Visit… 388. 2016-03-08 09:45:00 2016-03-08 09:51:00 AVER…
#> 3 XYZ-1001 QTcF Int.… Visit… 394. 2016-03-22 10:45:00 2016-03-22 10:51:00 AVER…
#> 4 XYZ-1002 QTcF Int.… Basel… 400. 2016-02-22 07:58:00 2016-02-22 08:01:00 AVER…
#> 5 XYZ-1002 QTcF Int.… Visit… 403. 2016-03-06 09:50:00 2016-03-06 09:56:00 AVER…
#> 6 XYZ-1002 QTcF Int.… Visit… 409. 2016-03-24 10:50:00 2016-03-24 10:56:00 AVER…
# Sample ADEG dataset with triplicate record for only AVISIT = 'Baseline'
adeg <- tribble(
~USUBJID, ~EGSEQ, ~PARAM, ~AVISIT, ~EGDTC, ~AVAL, ~TRTA,
"XYZ-1001", 1, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:50", 385, NA_character_,
"XYZ-1001", 2, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:52", 399, NA_character_,
"XYZ-1001", 3, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:56", 396, NA_character_,
"XYZ-1001", 4, "QTcF Int. (msec)", "Visit 2", "2016-03-08T09:48", 393, "Placebo",
"XYZ-1001", 5, "QTcF Int. (msec)", "Visit 2", "2016-03-08T09:51", 388, "Placebo",
"XYZ-1001", 6, "QTcF Int. (msec)", "Visit 3", "2016-03-22T10:48", 394, "Placebo",
"XYZ-1001", 7, "QTcF Int. (msec)", "Visit 3", "2016-03-22T10:51", 402, "Placebo",
"XYZ-1002", 1, "QTcF Int. (msec)", "Baseline", "2016-02-22T07:58", 399, NA_character_,
"XYZ-1002", 2, "QTcF Int. (msec)", "Baseline", "2016-02-22T07:58", 410, NA_character_,
"XYZ-1002", 3, "QTcF Int. (msec)", "Baseline", "2016-02-22T08:01", 392, NA_character_,
"XYZ-1002", 4, "QTcF Int. (msec)", "Visit 2", "2016-03-06T09:53", 407, "Active 20mg",
"XYZ-1002", 5, "QTcF Int. (msec)", "Visit 2", "2016-03-06T09:56", 400, "Active 20mg",
"XYZ-1002", 6, "QTcF Int. (msec)", "Visit 3", "2016-03-24T10:53", 414, "Active 20mg",
"XYZ-1002", 7, "QTcF Int. (msec)", "Visit 3", "2016-03-24T10:56", 402, "Active 20mg"
)
# Compute the average of AVAL only if there are more than 2 records within the
# by group
get_summary_records(
adeg,
by_vars = exprs(USUBJID, PARAM, AVISIT),
filter = n() > 2,
set_values_to = exprs(
AVAL = mean(AVAL, na.rm = TRUE),
DTYPE = "AVERAGE"
)
)
#> # A tibble: 2 × 5
#> USUBJID PARAM AVISIT AVAL DTYPE
#> <chr> <chr> <chr> <dbl> <chr>
#> 1 XYZ-1001 QTcF Int. (msec) Baseline 393. AVERAGE
#> 2 XYZ-1002 QTcF Int. (msec) Baseline 400. AVERAGE