Package index • cancR

Data management functions

Functions for typical data management tasks

cpR(): Fix CPR numbers with removed leading zeros

cutR(): Cut numeric variables into intervals

datR(): Convert dates from character to date format

distributR(): Assessment of distribution of continuous variables with histograms, QQ-plots and the Shapiro-Wilks test

factR(): Factorize variables

groupR(): Extract first n groups in data frame

joinR(): Join two or more dataframes

missR(): Overview of NAs in a dataframe

pvertR(): Format p-values to AMA manual of style

structR(): Convert dates to status indicator and time-to-event

readR(): Load csv, excel, rds and parquet files

recodR(): Recode multiple variables

redcapR(): Autoformatting of redcap exports

rowR(): Perform rowwise operations

summarisR(): Graphical overview of an entire dataset

Statistical Analyses

Functions that perform statistical analysis

estimatR(): Absolute risk estimation of time-to-event data with competing risks

extractR(): Extraction of key results from the estimatR function

followR(): Calculate median follow-up time using the inverse Kaplan-Meier method

incidencR(): Directly standardized incidence rates using the WHO standard population

inferencR(): Causal inference of time-to-event data

iteratR(): Perform multiple estimatR analyses

weightR(): Weight diagnostics for IPTW

Tables and figures

Functions for producing and formatting tables and figures

collectR(): Collection of multiple plots into one. Wrapper for ggarrange. Input must be a list of plots.

dagR(): Draw directed acyclic graphs (DAGS)

plotR(): Autoplot for estimatR, inferencR and clustR

savR(): Save plots and tables

swimmR(): Plot individual patient trajectories from time-to-event data (Swimmer plot)

tablR(): Create frequency tables

Register-specific functions

Functions customized for the danish registers

cci_timR(): Generation of time-dependent CCI and comorbidities from the Charlson Comorbidity Index

decodR(): Decoding of the main codelist for loading and searching in registries

formatR(): Auto-formatting of a data frame with layout option for typical levels and labels

includR(): Inclusion criteria for registry-studies

loadR(): Load registers

matchR(): Perform exposure-density matching for multilevel data

reportR(): Overview of matched and unmatched cases

searchR(): Find covariates or outcomes from the registers

simulatR(): Simulate danish health registers

updatR(): Update of Charlson Comorbidity Index or covariate values over time

Built-in datasets

Datasets for testing functions

analysis_df: Simulated dataset for model testing

match_df: Simulated dataset for the matchR algorithm

redcap_df: Simulated Redcap dataset

covariates_df: Simulated time-dependent covariates dataset.

population_denmark: Population table, Denmark

population_who: Population table, WHO

Miscellaneous functions

Small utility functions

checkR(): Detection of positivity violations (empty levels)

closR(): Pick the closest value from a range in vector.

colR(): Set default color palette

combinR(): Generate all possible cominations/permutations

formatR(): Auto-formatting of a data frame with layout option for typical levels and labels

listR(): Routine modifications of lists

modeR(): Get the mode (most common value) of a vector.

multitaskR(): Start a multisession with automatic reset

numbR(): Format numeric vectors

powR(): Automated keyboard strokes

rollR(): Assign rolling ID.

tickR(): First timestamp for taking time

tockR(): Last timestamp for taking time

viewR(): Graphical overview of the structure of a multilevel list