Function reference • admiral

Derivations for Adding Variables

All ADaMs

derive_var_extreme_flag(): Add a Variable Flagging the First or Last Observation Within Each By Group

derive_var_joined_exist_flag(): Derives a Flag Based on an Existing Flag

derive_var_last_dose_amt(): Derive Last Dose Amount

derive_var_last_dose_date(): Derive Last Dose Date-Time

derive_var_last_dose_grp(): Derive Last Dose with User-Defined Groupings

derive_var_merged_cat(): Merge a Categorization Variable

derive_var_merged_character(): Merge a Character Variable

derive_var_merged_exist_flag(): Merge an Existence Flag

derive_var_merged_summary(): Merge a Summary Variable

derive_var_obs_number(): Adds a Variable Numbering the Observations Within Each By Group

derive_var_relative_flag(): Flag Observations Before or After a Condition is Fulfilled

derive_var_trtdurd(): Derive Total Treatment Duration (Days)

derive_vars_dt(): Derive/Impute a Date from a Date Character Vector

derive_vars_dtm(): Derive/Impute a Datetime from a Date Character Vector

derive_vars_dtm_to_dt(): Derive Date Variables from Datetime Variables

derive_vars_dtm_to_tm(): Derive Time Variables from Datetime Variables

derive_vars_duration(): Derive Duration

derive_vars_dy(): Derive Relative Day Variables

derive_vars_joined(): Add Variables from an Additional Dataset Based on Conditions from Both Datasets

derive_vars_last_dose(): Derive Last Dose

derive_vars_merged(): Add New Variable(s) to the Input Dataset Based on Variables from Another Dataset

derive_vars_merged_lookup(): Merge Lookup Table with Source Dataset

derive_vars_transposed(): Derive Variables by Transposing and Merging a Second Dataset

get_summary_records(): Create Summary Records

ADSL-specific

Derivation functions helpful for building the ADSL dataset

derive_var_age_years(): Derive Age in Years

derive_var_dthcaus(): Derive Death Cause

derive_var_extreme_dt(): Derive First or Last Date from Multiple Sources

derive_var_extreme_dtm(): Derive First or Last Datetime from Multiple Sources

derive_vars_aage(): Derive Analysis Age

derive_vars_period(): Add Subperiod, Period, or Phase Variables to ADSL

BDS-specific

Derivation functions helpful for building the BDS datasets (e.g. advs, adlb, adeg, adex)

derive_var_analysis_ratio(): Derive Ratio Variable

derive_var_anrind(): Derive Reference Range Indicator

derive_var_atoxgr(): Derive Lab High toxicity Grade 0 - 4 and Low Toxicity Grades 0 - (-4)

derive_var_atoxgr_dir(): Derive Lab Toxicity Grade 0 - 4

derive_var_base(): Derive Baseline Variables

derive_var_basetype(): Derive Basetype Variable

derive_var_chg(): Derive Change from Baseline

derive_var_ontrtfl(): Derive On-Treatment Flag Variable

derive_var_pchg(): Derive Percent Change from Baseline

derive_var_shift(): Derive Shift

OCCDS-specific

Derivation functions helpful for building the OCCDS datasets (e.g. adae, adcm, admh)

derive_var_trtemfl(): Derive Treatment-emergent Flag

derive_vars_atc(): Derive ATC Class Variables

derive_vars_query(): Derive Query Variables

get_terms_from_db(): Get Terms from the Queries Database

Derivations for Adding Parameters/Records

BDS-specific

default_qtc_paramcd(): Get Default Parameter Code for Corrected QT

derive_expected_records(): Derive Expected Records

derive_extreme_event(): Add the Worst or Best Observation for Each By Group as New Records

derive_extreme_records(): Add the First or Last Observation for Each By Group as New Records

derive_locf_records(): Derive LOCF (Last Observation Carried Forward) Records

derive_param_bmi(): Adds a Parameter for BMI

derive_param_bsa(): Adds a Parameter for BSA (Body Surface Area) Using the Specified Method

derive_param_computed(): Adds a Parameter Computed from the Analysis Value of Other Parameters

derive_param_doseint(): Adds a Parameter for Dose Intensity

derive_param_exist_flag(): Add an Existence Flag Parameter

derive_param_exposure(): Add an Aggregated Parameter and Derive the Associated Start and End Dates

derive_param_extreme_event(): Add an Extreme Event Parameter

derive_param_framingham(): Adds a Parameter for Framingham Heart Study Cardiovascular Disease 10-Year Risk Score

derive_param_map(): Adds a Parameter for Mean Arterial Pressure

derive_param_qtc(): Adds a Parameter for Corrected QT (an ECG measurement)

derive_param_rr(): Adds a Parameter for Derived RR (an ECG measurement)

derive_param_wbc_abs(): Add a parameter for lab differentials converted to absolute values

derive_summary_records(): Add New Records Within By Groups Using Aggregation Functions

TTE-specific

derive_param_tte(): Derive a Time-to-Event Parameter

Metadata

Auxiliary datasets providing definitions as input for derivations, e.g. grading criteria or dose frequencies

atoxgr_criteria_ctcv4: Metadata Holding Grading Criteria for NCI-CTCAEv4

atoxgr_criteria_ctcv5: Metadata Holding Grading Criteria for NCI-CTCAEv5

dose_freq_lookup: Pre-Defined Dose Frequencies

Advanced Functions

Admiral Options

get_admiral_option(): Get the Value of an Admiral Option

set_admiral_options(): Set the Value of Admiral Options

Higher Order

call_derivation(): Call a Single Derivation Multiple Times

derivation_slice(): Create a derivation_slice Object

restrict_derivation(): Execute a Derivation on a Subset of the Input Dataset

slice_derivation(): Execute a Derivation with Different Arguments for Subsets of the Input Dataset

Creating Auxiliary Datasets

consolidate_metadata(): Consolidate Multiple Meta Datasets Into a Single One

create_period_dataset(): Create a Reference Dataset for Subperiods, Periods, or Phases

create_query_data(): Creates a queries dataset as input dataset to the dataset_queries argument in derive_vars_query()

create_single_dose_dataset(): Create dataset of single doses

Source Objects

basket_select(): Create a basket_select object

censor_source(): Create a censor_source Object

date_source(): Create a date_source object

dthcaus_source(): Create a dthcaus_source Object

event(): Create a event Object

event_source(): Create an event_source Object

query(): Create an query object

tte_source(): Create a tte_source Object

death_event lastalive_censor ae_event ae_ser_event ae_gr1_event ae_gr2_event ae_gr3_event ae_gr4_event ae_gr5_event ae_gr35_event ae_sev_event ae_wd_event: Pre-Defined Time-to-Event Source Objects

Other

assert_db_requirements(): Check required parameters for a basket

assert_terms(): Asserts Requirements for Terms for Queries

assert_valid_queries(): Verify if a Dataset Has the Required Format as Queries Dataset.

extend_source_datasets(): Add By Groups to All Datasets if Necessary

filter_date_sources(): Select the First or Last Date from Several Sources

format(<basket_select>): Returns a Character Representation of a basket_select() Object

list_tte_source_objects(): List all tte_source Objects Available in a Package

params(): Create a Set of Parameters

validate_basket_select(): Validate an object is indeed a basket_select object

validate_query(): Validate an object is indeed a query object

Computation Functions for Vectors

All ADaMs

compute_dtf(): Derive the Date Imputation Flag

compute_duration(): Compute Duration

compute_tmf(): Derive the Time Imputation Flag

convert_date_to_dtm(): Convert a Date into a Datetime Object

convert_dtc_to_dt(): Convert a Date Character Vector into a Date Object

convert_dtc_to_dtm(): Convert a Date Character Vector into a Datetime Object

impute_dtc_dt(): Impute Partial Date Portion of a '--DTC' Variable

impute_dtc_dtm(): Impute Partial Date(-time) Portion of a '--DTC' Variable

BDS-specific

compute_bmi(): Compute Body Mass Index (BMI)

compute_bsa(): Compute Body Surface Area (BSA)

compute_framingham(): Compute Framingham Heart Study Cardiovascular Disease 10-Year Risk Score

compute_map(): Compute Mean Arterial Pressure (MAP)

compute_qtc(): Compute Corrected QT

compute_qual_imputation(): Function to Impute Values When Qualifier Exists in Character Result

compute_qual_imputation_dec(): Compute Factor for Value Imputations When Character Value Contains < or >

compute_rr(): Compute RR Interval From Heart Rate

compute_scale(): Compute Scale Parameters

Utility Functions

Utilities for Formatting Observations

convert_blanks_to_na(): Convert Blank Strings Into NAs

convert_na_to_blanks(): Convert NAs Into Blank Strings

yn_to_numeric(): Map "Y" and "N" to Numeric Values

Utilities for Dataset Checking

extract_duplicate_records(): Extract Duplicate Records

get_duplicates_dataset(): Get Duplicate Records that Led to a Prior Error

get_many_to_one_dataset(): Get Many to One Values that Led to a Prior Error

get_one_to_many_dataset(): Get One to Many Values that Led to a Prior Error

Utilities used within Derivation Functions

call_user_fun(): Calls a Function Provided by the User

extract_unit(): Extract Unit From Parameter Description

get_not_mapped(): Get list of records not mapped from the lookup table.

signal_duplicate_records(): Signal Duplicate Records

Utilities for Filtering Observations

count_vals(): Count Number of Observations Where a Variable Equals a Value

filter_extreme(): Filter the First or Last Observation for Each By Group

filter_joined(): Filter Observations Taking Other Observations into Account

filter_relative(): Filter the Observations Before or After a Condition is Fulfilled

max_cond(): Maximum Value on a Subset

min_cond(): Minimum Value on a Subset

Utilities used for Date Imputation

dt_level(): Create a dt_level object

dtm_level(): Create a dtm_level object

get_imputation_target_date(): Get Date Imputation Targets

get_imputation_target_time(): Get Time Imputation Targets

get_partialdatetime(): Parse DTC variable and Determine Components

restrict_imputed_dtc_dt(): Restrict Imputed DTC date to Minimum/Maximum Dates

restrict_imputed_dtc_dtm(): Restrict Imputed DTC date to Minimum/Maximum Dates

Utilities for Quosures

chr2vars(): Turn a Character Vector into a List of Expressions

negate_vars(): Negate List of Variables

Utilities used for Examples and Template Scripts

list_all_templates(): List All Available ADaM Templates

use_ad_template(): Open an ADaM Template Script

Utilities for Printing

print(<adam_templates>): Print adam_templates Objects

print(<source>): Print source Objects

print_named_list(): Print Named List

Example Datasets

You can run use_ad_template() to produce additional datasets

admiral_adlb: Lab Analysis Dataset

admiral_adsl: Subject Level Analysis Dataset

ex_single: Single Dose Exposure Dataset

example_qs: Example QS Dataset

queries: Queries Dataset

queries_mh: Queries MH Dataset

Objects exported from other packages

To maximize the user-friendliness of admiral, functions from other packages are provided without changes made to them, follow the links below to see their documentation.

`%>%`: Pipe operator

desc: dplyr desc

exprs: rlang exprs

Deprecated

As admiral is still evolving, functions/parameters may need to be removed or replaced over time. In such cases, the function/parameter will enter the following 6-month deprecation cycle:

In the first release (0-3 months), there will be a warning issued if you use the function/parameter, but it will still be available to use.
In the following release (3-6 months), an error will be produced if you use the function/parameter.
Finally, from the 3rd release (6 months) onwards, the function/parameter will be removed from admiral and its documentation completely.

Note: Guidance on replacement functionality can be found in the warning/error message produced or in the function’s documentation.

Below, you can find a list of functions in the process of being deprecated:

derive_var_confirmation_flag(): Derive Confirmation Flag

derive_var_disposition_status(): Derive a Disposition Status at a Specific Timepoint

derive_var_worst_flag(): Adds a Variable Flagging the Maximal / Minimal Value Within a Group of Observations

derive_vars_disposition_reason(): Derive a Disposition Reason at a Specific Timepoint

format_eoxxstt_default(): Default Format for Disposition Status

format_reason_default(): Default Format for the Disposition Reason