polish: Do some final polishing of the scrubbed mason analysis data.

In lwjohnst86/mason: Build Data Structures for Common Statistical Analysis

Description

Do some final polishing of the scrubbed mason analysis data.

Usage

polish_renaming(data, renaming.fun, columns = NULL)

polish_filter(data, keep.pattern, column)

polish_transform_estimates(data, transform.fun)

polish_adjust_pvalue(data, method = "BH")

Arguments

data	The scrubbed object.
renaming.fun	A function, typically with base::gsub(), that searches and replaces strings.
columns	The columns to apply the renaming function to. Defaults to columns that are a factor or character vectors.
keep.pattern	Rows to keep based on a regular expression pattern.
column	The column to apply the filtering to.
transform.fun	A function to modify continuous variable columns.
method	Correction method for the p-value adjustment (stats::p.adjust()).

Functions

• polish_renaming: polish_renaming simply takes a function, most likely one that uses base::gsub(), and uses that to search and replace words, etc, in the specified columns.

• polish_filter: polish_filter is basically a thin wrapper around dplyr::filter(), but using base::grepl() for the pattern searching.

• polish_transform_estimates: polish_transform_estimates is simply a thin wrapper around dplyr::mutate().

• polish_adjust_pvalue: polish_adjust_pvalue is a thin wrapper around dplyr::mutate() and stats::p.adjust()

Examples

library(magrittr)
ds <- swiss %>%
 design('glm') %>%
 add_settings() %>%
 add_variables('yvar', c('Fertility', 'Education')) %>%
 add_variables('xvar', c('Agriculture', 'Catholic')) %>%
 add_variables('covariates', 'Examination') %>%
 construct() %>%
 scrub()
polish_renaming(ds, function(x) gsub('Education', 'Schooling', x))
polish_filter(ds, 'Xterm', 'term')
polish_adjust_pvalue(ds)[c('p.value', 'adj.p.value')]
polish_transform_estimates(ds, function(x) exp(x))

lwjohnst86/mason documentation built on June 7, 2020, 3:08 a.m.