Package index
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GeomAdmin - GeomAdmin ggproto object
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StatAdmin - StatAdmin ggproto object
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add_administration() - Append administration events
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add_ae_observation()experimental - Add AE observation
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add_baseline() - Attach baseline covariate
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add_bl_crcl() - Add baseline creatinine clearance field.
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add_bl_lbm() - Add baseline lean body mass (LBM)
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add_bl_odwg() - Add baseline hepatic function class
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add_bl_renal() - Add baseline renal function class
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add_cfb() - Add baseline and change from baseline fields
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add_covariate() - Attach time-varying covariate
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add_dose_level() - Add dose level (
DL) column
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add_obs_per_dosing_interval() - Add the number of observations per dosing interval
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add_observation() - Append observation events
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add_rtb() - Add baseline and relative-to-baseline fields
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add_tad() - Add time-after-dose (TAD) field
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add_trtdy() - Add treatment day ('TRTDY') column
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administration_summary() - Overview on the number of administrations in the subjects by parent
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ae_summary() - AE summary
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analyte_overview() - Overview on analytes and parents
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analytes() - Analytes within a NIF or SDTM object
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analytes(<data.frame>) - Analytes within a NIF object
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analytes(<nif>) - Analytes within a NIF object
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analytes(<sdtm>) - Analytes in a sdtm object
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as_nif() - Convert data frame to nif object
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cmt_mapping() - Analyte - compartment mapping
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coalesce_join() - Coalescing join
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covariate_barplot() - Generic covariate barplot
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covariate_hist() - Generic covariate distribution histogram
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crea_mdrd() - Serum creatinine estimation from eGFR (MDRD)
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crea_raynaud() - Serum creatinine estimation from eGFR (Raynaud method)
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derive_sld()experimental - Calculate SLD for SDTM.TR domain
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disposition_summary() - Subject disposition overview
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domain() - Return a specific domain from a sdtm object
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domain_model - SDTM Domain Model variables
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dose_levels() - Dose levels within a NIF object
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dose_lin()experimental - Test for dose linearity
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dose_red_sbs() - Subjects with dose reduction
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doses() - Doses in a nif or sdtm object
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doses(<nif>) - Doses within a NIF object
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doses(<sdtm>) - Doses in a sdtm object
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edish_plot() - Drug-induced serious hepatotoxicity (eDISH) plot
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egfr_cg() - Glomerular filtration rate estimation from serum creatinine (Cockcroft-Gault)
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egfr_mdrd() - Glomerular filtration rate estimation from serum creatinine (MDRD)
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egfr_raynaud() - Glomerular filtration rate estimation from serum creatinine (Raynaud method)
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examplinib_fe - Synthetic SDTM data from a fictional clinical food effect study for 'examplinib'.
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examplinib_fe_nif - Synthetic NIF data from a fictional clinical food effect study for 'examplinib'.
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examplinib_poc - Synthetic SDTM data from a fictional clinical single-arm study with rich and sparse pk sampling.
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examplinib_poc_min_nif - Synthetic NIF data from a fictional clinical single-arm study with rich and sparse pk sampling. Reduced to the minimally required fields.
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examplinib_poc_nif - Synthetic NIF data from a fictional clinical single-arm study with rich and sparse pk sampling.
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examplinib_sad - Synthetic SDTM data from a fictional clinical SAD FIH study with rich PK sampling
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examplinib_sad_min_nif - Synthetic NIF data from a fictional clinical SAD FIH study with rich PK sampling. Reduced to the minimally required fields.
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examplinib_sad_nif - Synthetic NIF data from a fictional clinical SAD FIH study with rich PK sampling
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filter_subject() - Keep only selected USUBJID in the data set
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find_duplicates() - Find duplicate rows in a data frame
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geom_admin() - Administration geom layer for ggplot
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has_domain() - Check whether a domain is present in an SDTM object
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import_from_connection() - Import nif object from connection
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import_nif() - Import nif file
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import_observation()experimental - Add observation from non-SDTM-formatted data table
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index_dosing_interval() - Index dosing intervals
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index_rich_sampling_intervals()experimental - Identify and index rich PK sampling intervals
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is_iso8601_date() - Check if a string matches ISO 8601 date format
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is_iso8601_datetime() - Check if a string matches ISO 8601 date-time format
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is_iso_date_time() - Test whether string represents ISO 8601-formatted date-time
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lbm_boer() - Lean body mass (Boer formula)
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lbm_hume() - Lean body mass (Hume formula)
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lbm_peters() - Lean body mass (Peters formula)
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limit() - Subset nif to rows with DTC before the last individual or global observation
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make_ntime() - Make nominal time
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make_ntime_from_tpt() - Convert time point text to numeric time values
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make_subjects_sdtm() - Make subject data frame from SDTM object
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make_time() - Calculate time fields based on DTC
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max_admin_time() - Maximal administration time
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max_observation_time() - Maximal observation time
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max_time() - Maximal time in nif object
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minimal_nif_fields - Minimal nif fields
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n_administrations() - Number of administrations per subject
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nca() - Non-compartmental analysis
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nca1()experimental - Non-compartmental analysis of NIF data
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nca2() - Non-compartmental analysis with analyte-based grouping
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nca_from_pp() - Generate NCA table from the SDTM.PP domain
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nca_power_model()experimental - Power fit for PK parameters
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nca_summary() - PK parameter summary statistics by dose
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nca_summary_table() - PK parameter summary statistics table by dose
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new_nif() - nif class constructor
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new_sdtm() - SDTM class constructor, creating a sdtm object from a set of SDTM domains
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nif_auto()experimental - Auto-generate nif from sdtm object
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nif_disclaimer() - Disclaimer statement
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nif_nca_new() - Perform Non-Compartmental Analysis (NCA) for each subject and analyte
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nif_option() - Set or get global options
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nif_viewer() - NIF viewer
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normalize_nif() - Normalize nif object
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obs_per_dose_level() - Observations per dose level
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parents() - Parent compounds within a NIF object
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plot(<nif>) - Plot NIF object.
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plot(<sdtm>) - Plot SDTM object
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print_debug() - Debug output
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read_sdtm() - Read SDTM data
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resolve_duplicates() - Remove duplicate rows from a data frame
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rich_sampling_sbs() - Identify subjects with rich sampling
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sdtm_missing_times() - Number of DTC entries with missing time information
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standard_nif_fields - Standard nif fields
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standardize_date_format() - Convert date fields to POSIX format
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stat_admin() - ggplot stat for treatment administrations
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studies() - Studies within a nif object
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subject_info() - Baseline details for specific subjects
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subject_info(<sdtm>) - Baseline details for specific subjects
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subjects() - Unique subjects within a data set
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subjects(<nif>) - Unique subjects within a NIF object
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subs_per_dose_level() - Subjects per dose level
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suggest() - Suggest data programming steps to generate a nif object from an sdtm object
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summary(<sdtm>) - SDTM summary
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testcd() - Generic function testcd
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testcd(<sdtm>) - Extract TESTCD fields by domain from a sdtm object
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treatments() - Treatments in a nif or sdtm object
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treatments(<nif>) - Treatments in a nif object
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treatments(<sdtm>) - Treatments in a sdtm object
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usubjid() - Get the USUBJID of subject
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validate_domain() - Check whether fields in domain are compliant with SDTM
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validate_sdtm() - Check whether sdtm object is compliant with SDTM standard
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watermark() - Add a watermark annotation layer for a ggplot2 object
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write_monolix() - Write as comma-separated file, complying with the format used by Monolix
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write_nif() - Write as space-delimited, fixed-width file as required by NONMEM or a character-separated file