## Overview

A set of tools for preparing and summarizing data for publication purposes. Includes functions for tabulating models, means to produce human-readable summary statistics from raw data, tools for calculating durations, and simplistic hypothesis testing tools.

## Functions

### > tabulate_

`tabulate_model()`

: Converts parameters from a model object into a usable table for publication purposes. By default, formats the table into a human-readable/exportable form.
`tabulate_at_risk()`

: Returns a risk table from a model object and specified time points.

### > paste_

`paste_freq()`

: Returns a human-readable frequency from count(able) data. Handily has methods for several types of data.
`paste_median()`

: Returns a human-readable median with inter-quartile range from numeric data.
`paste_mean()`

: Returns a human-readable mean with standard deviation from numeric data.
`paste_efs()`

: Returns a human-readable event-free-survival from a survfit object and a specified time point.

### > calc_

`calc_duration()`

: Returns the duration of time between two provided date objects. Essentially a macro of `lubridate::`

functions with extra logic built in.
`calc_chunks()`

: Returns mapped “chunk” indices for a data object given a specified chunk size (e.g. number of rows in a tibble).

### > test_

`test_hypothesis()`

: Returns a p-value from null hypothesis testing of stratified continuous or categorical data. Provides parametric and non-parametric testing options (see docs).

### > chunk_

`chunk_data_()`

: Returns a factory function which returns chunks of a given data object (table, vector) with successive function calls.