get_summary_records {admiral}R Documentation

Create Summary Records

Description

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.

Usage

get_summary_records(
  dataset,
  by_vars,
  filter = NULL,
  analysis_var,
  summary_fun,
  set_values_to
)

Arguments

dataset

A data frame.

by_vars

Variables to consider for generation of groupwise summary records. Providing the names of variables in vars() will create a groupwise summary and generate summary records for the specified groups.

filter

Filter condition as logical expression to apply during summary calculation. By default, filtering expressions are computed within by_vars as 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 in by_vars.

  • filter_rows = (dplyr::n() > 2) will filter n count of by_vars greater than 2.

analysis_var

Analysis variable.

summary_fun

Function that takes as an input the analysis_var and performs the calculation. This can include built-in functions as well as user defined functions, for example mean or function(x) mean(x, na.rm = TRUE).

set_values_to

A list of variable name-value pairs. Use this argument if you need to change the values of any newly derived records.

Set a list of variables to some specified value for the new observation(s)

  • 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 or NA. (e.g. vars(PARAMCD = "TDOSE",PARCAT1 = "OVERALL")). More general expression are not allowed.

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.

Value

A data frame of derived records.

Author(s)

Pavan Kumar, updated by Alana Harris

See Also

derive_summary_records()

General Derivation Functions for all ADaMs that returns variable appended to dataset: derive_var_confirmation_flag(), derive_var_extreme_flag(), derive_var_last_dose_amt(), derive_var_last_dose_date(), derive_var_last_dose_grp(), derive_var_merged_cat(), derive_var_merged_character(), derive_var_merged_exist_flag(), derive_var_obs_number(), derive_var_worst_flag(), derive_vars_last_dose(), derive_vars_merged_lookup(), derive_vars_merged(), derive_vars_transposed()

Examples

library(dplyr, warn.conflicts = FALSE)
adeg <- tibble::tribble(
  ~USUBJID, ~EGSEQ, ~PARAM, ~AVISIT, ~EGDTC, ~AVAL, ~TRTA,
  "XYZ-1001", 1, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:50", 385, "",
  "XYZ-1001", 2, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:52", 399, "",
  "XYZ-1001", 3, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:56", 396, "",
  "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, "",
  "XYZ-1002", 2, "QTcF Int. (msec)", "Baseline", "2016-02-22T07:58", 410, "",
  "XYZ-1002", 3, "QTcF Int. (msec)", "Baseline", "2016-02-22T08:01", 392, "",
  "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 = vars(USUBJID, PARAM, AVISIT),
  analysis_var = AVAL,
  summary_fun = function(x) mean(x, na.rm = TRUE),
  set_values_to = vars(DTYPE = "AVERAGE")
)

advs <- tibble::tribble(
  ~USUBJID, ~VSSEQ, ~PARAM, ~AVAL, ~VSSTRESU, ~VISIT, ~VSDTC,
  "XYZ-001-001", 1164, "Weight", 99, "kg", "Screening", "2018-03-19",
  "XYZ-001-001", 1165, "Weight", 101, "kg", "Run-In", "2018-03-26",
  "XYZ-001-001", 1166, "Weight", 100, "kg", "Baseline", "2018-04-16",
  "XYZ-001-001", 1167, "Weight", 94, "kg", "Week 24", "2018-09-30",
  "XYZ-001-001", 1168, "Weight", 92, "kg", "Week 48", "2019-03-17",
  "XYZ-001-001", 1169, "Weight", 95, "kg", "Week 52", "2019-04-14",
)

# Set new values to any variable. Here, `DTYPE = MAXIMUM` refers to `max()` records
# and `DTYPE = AVERAGE` refers to `mean()` records.
get_summary_records(
  advs,
  by_vars = vars(USUBJID, PARAM),
  analysis_var = AVAL,
  summary_fun = max,
  set_values_to = vars(DTYPE = "MAXIMUM")
) %>%
  get_summary_records(
    by_vars = vars(USUBJID, PARAM),
    analysis_var = AVAL,
    summary_fun = mean,
    set_values_to = vars(DTYPE = "AVERAGE")
  )

# Sample ADEG dataset with triplicate record for only AVISIT = 'Baseline'
adeg <- tibble::tribble(
  ~USUBJID, ~EGSEQ, ~PARAM, ~AVISIT, ~EGDTC, ~AVAL, ~TRTA,
  "XYZ-1001", 1, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:50", 385, "",
  "XYZ-1001", 2, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:52", 399, "",
  "XYZ-1001", 3, "QTcF Int. (msec)", "Baseline", "2016-02-24T07:56", 396, "",
  "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, "",
  "XYZ-1002", 2, "QTcF Int. (msec)", "Baseline", "2016-02-22T07:58", 410, "",
  "XYZ-1002", 3, "QTcF Int. (msec)", "Baseline", "2016-02-22T08:01", 392, "",
  "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 = vars(USUBJID, PARAM, AVISIT),
  filter = dplyr::n() > 2,
  analysis_var = AVAL,
  summary_fun = function(x) mean(x, na.rm = TRUE),
  set_values_to = vars(DTYPE = "AVERAGE")
)

[Package admiral version 0.8.4 Index]