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admiral (version 1.1.1)

get_summary_records: Create Summary Records

Description

[Superseded]

Development on get_summary_records() is complete, and for new code we recommend switching to using the dataset_add argument in derive_summary_records().

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 = NULL
)

Value

A data frame of derived records.

Arguments

dataset

Input dataset

The variables specified by the by_vars and analysis_var arguments are expected to be in the dataset.

by_vars

Grouping variables

Variables to consider for generation of groupwise summary records.

Permitted Values: list of variables created by exprs() e.g. exprs(USUBJID, VISIT)

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.

[Deprecated] Please use set_values_to instead.

summary_fun

Function that takes as an input the analysis_var and performs the calculation.

[Deprecated] Please use set_values_to instead.

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

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"
  )

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 superseded: date_source(), derive_param_extreme_record(), derive_var_dthcaus(), derive_var_extreme_dt(), derive_var_extreme_dtm(), dthcaus_source()

Examples

Run this code
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"
  )
)

# 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"
  )
)

# 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"
  )
)

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