clean_va

cleanVA

VA cleaning:<ol>
<li>tidyNA:
Replacing empty placeholders (".","", "(any number of empty space)",
"NULL", "NA", "N/A" , "-") - any cases - with NA</li>
<li>Simplifying the notation for qualitative
VA notation (NPL becomes NLP, PL becomes LP)</li>
<li>Removing non-Snellen character strings</li>
</ol>

internal

There is no ophthalmic researcher who has not had headaches from
the handling of visual acuity entries. Different notations, untidy entries.
This shall now be a matter of the past. Eye makes it as easy as pie to work
with VA data - easy cleaning, easy conversion between
Snellen, logMAR, ETDRS letters, and qualitative visual acuity
shall never pester you again. The eye
package automates the pesky task to count number of patients and eyes,
and can help to clean data with easy re-coding for right and left eyes.
It also contains functions to help reshaping eye side specific variables
between wide and long format. Visual acuity conversion is based on
Schulze-Bonsel et al. (2006) <doi:10.1167/iovs.05-0981>,
Gregori et al. (2010) <doi:10.1097/iae.0b013e3181d87e04>,
Beck et al. (2003) <doi:10.1016/s0002-9394(02)01825-1> and
Bach (2007) <https://michaelbach.de/sci/acuity.html>.

Tjebo Heeren

Analysis of Eye Data

Antoine Fabri

clean_va function

<dl><dt>x</dt>
<dd>Vector with VA entries</dd>
<dt>message</dt>
<dd>message for replaced NA values</dd></dl>

Arguments

Cleaning up Visual acuity entries — clean_va

<dl>

<dt>x</dt>
<dd>Vector with VA entries</dd>


<dt>message</dt>
<dd>message for replaced NA values</dd>

</dl>

clean_va: Cleaning up Visual acuity entries

Description

Usage

Value

Arguments

See Also