blink: Your data in a blink of an eye

In eye: Analysis of Eye Data

Description

blink summarizes your data tailored to the need of ophthalmic research: It looks for VA and IOP columns and summarises those with common statistics. In order to make it work, it requires specific column naming - please see section "column names" and "data coding". For more details how blink works, see vignette("eye")

Usage

blink(x, va_to = "logmar", va_cols = NULL, iop_cols = NULL, fct_level = 0:4)

Arguments

x	data frame
va_to	to which VA notation (passed to va())
va_cols	if specified, overruling automatic VA columns selection. tidyselection supported
iop_cols	if specified, overruling automatic IOP columns selection. tidyselection supported
fct_level	Remove columns for Summarizing when all unique values fall into range. character or numeric vector, default 1:4

Details

blink is basically a wrapper around myop, eyes and reveal:

• Duplicate rows are always removed

• Column names are prepared for myopization (see myop)

• VA will always be converted to logmar

Value

object of class blink and list. Class blink contains the myopized data, count of patients and eyes, and summaries for visual acuities and intraocular pressure.

Data coding

• Only common codes supported:

• eyes: "r", "re", "od", "right" - or numeric coding r:l = 0:1 or 1:2

• Visual acuity: "VA", "BCVA", "Acuity"

• Intraocular pressure: "IOP", "GAT", "NCT", "pressure"

Column name rules

• No spaces!

• Do not use numeric coding for eyes in column names

• Separate eye and VA and IOP codes with underscores ("bcva_l_preop", "VA_r", "left_va", "IOP_re")

• Avoid separate VA or IOP codes if this is not actually containing VA/ IOP data (e.g. "stableVA" instead of "stable_va", ChangeIOP instead of "change_IOP")

• Keep names short

• Don't use underscores when you don't have to. Consider each section divided by an underscore as a relevant characteristic of your variable. ("preop" instead of "pre_op", "VA" instead of "VA_ETDRS_Letters")

• Use common codes for your patient column (see eyes, section Guessing) (e.g., "pat", "patient" or "ID", ideally both: "patientID" or "patID")

• Don't be too creative with your names!

Names examples

Good names:

-c("patid", "surgery_right", "iop_r_preop", "va_r_preop", "iop_r", "iop_l")

OK names

-c("Id", "Eye", "BaselineAge", "VA_ETDRS_Letters", "InjectionNumber"): Names are long and there are two unnecessary underscore in the VA column. Better just "VA" -c("id", "r", "l"): All names are commonly used (good!), but which dimension of "r"/"l" are we exactly looking at?

Bad names (eye will fail)

• c("id", "iopr", "iopl", "VAr", "VAl"): eye won't be able to recognize IOP and VA columns

• c("id", "iop_r", "iop_l", "stable_iop_r", "stable_iop_l"): eye may wrongly identify the (probably logical) columns "stable_iop" as columns containing IOP data. Better maybe: "stableIOP_l"

• c("person", "goldmann", "vision"): eye will not recognize that at all

tidy data

blink and myop work more reliably with clean data (any package will, really!). clean data.

column removal

Done with remCols: Removes columns that only contain values defined in fct_levels or logicals from selected columns (currently for both automatically and manually selected columns). fct_levels are removed because they are likely categorical codes.

See Also

About tidyselection.

How to rename your columns (two threads on stackoverflow.com):

• Rename columns 1

• Rename columns 2

Examples

library(eyedata)
blink(amd2)

messy_df <- data.frame( id = letters[1:3],
iop_r_preop = sample(21:23), iop_r_postop = sample(11:13),
iop_l_postop = sample(11:13), iop_l_preop = sample(31:33),
va_r_preop = sample(41:43),  va_l_preop = sample(41:43),
va_r_postop = sample(51:53), va_l_postop = sample(45:47)
)
blink(messy_df)

eye documentation built on Sept. 5, 2021, 5:25 p.m.