correct.changes: Correct Changes from 'textcleaner'
In SemNetCleaner: An Automated Cleaning Tool for Semantic and Linguistic Data

Description Usage Arguments Value Author(s) Examples

A function that corrects changes that were made automatically by textcleaner

1	correct.changes(textcleaner.obj)

textcleaner.obj

Object from textcleaner

This function returns the corrected lists from textcleaners:

`binary`	A matrix of responses where each row represents a participant and each column represents a unique response. A response that a participant has provided is a '`1`' and a response that a participant has not provided is a '`0`'
`responses`	A list containing two objects: clean A response matrix that has been spell-checked and de-pluralized with duplicates removed. This can be used as a final dataset for analyses (e.g., fluency of responses) original The original response matrix that has had white spaces before and after words response. Also converts all upper-case letters to lower case
`spellcheck`	A list containing three objects: `full` All responses regardless of spell-checking changes `auto` Only the incorrect responses that were changed during spell-check `changes` Only the changes made within the function `correct.changes`
`removed`	A list containing two objects: `rows` Identifies removed participants by their row (or column) location in the original data file `ids` Identifies removed participants by their ID (see argument `data`)
`partChanges`	A list where each participant is a list index with each response that was been changed. Participants are identified by their ID (see argument `data`). This can be used to replicate the cleaning process and to keep track of changes more generally. Participants with `NA` did not have any changes from their original data and participants with missing data are removed (see `removed$ids`)

Alexander Christensen <alexpaulchristensen@gmail.com>

# Toy example
raw <- open.animals[c(1:10),-c(1:3)]

if(interactive())
{
    #Full test
    clean <- textcleaner(open.animals[,-c(1,2)], partBY = "row", dictionary = "animals")
}