visualFields (version 0.6.2)

vfobject: visualField objects

Description

This is the main object of the visualFields package. It is essentially a dataframe, but with a fixed number of columns (with pre-determined names) for information about the subject and test data and a variable number of columns for the perimetry results. These can be the sensitivities, or total-deviation values, or pattern-deviation values obtained from static automated perimetry (SAP), frequency-doubling perimetry (FDP), or any other perimetry device. (The number of columns for tested locations is variable as is different for different testing patterns, 24-2, 30-2, 10-2, etc.) Mean deviation, pattern standard deviation, vfi, etc are stored too in a visualField-type object

Details

The fixed columns of the visualField object with information about subject and test are:

id	subject identification number
tperimetry	test perimetry. The type of perimetry analysis performed. Possible values include
	"sap" and "fdp". The value of this column, tperimetry, is used
	in conjunction with the value in talgorithm, and tpattern to find the
	corresponding normative values (see help on nv) to use for data analysis (e.g.
	calculation of total-deviation and pattern-deviation values and probability maps). At
	the moment, only normative values for SAP, 24-2, SITA standard, is distributed with
	visualFields. Nevertheless, visualFields contains a number of functions
	that can be used for the generation of normative values (see getnv,
	ageLinearModel, sdnv, tdval, pdval, locperc,
	vfstats, vfindex, gloperc, vfiperc, setnv).
talgorithm	test algorithm. The algorithm used for the perimetric test. Posible values are
	sitas and zest. At the moment, only normative values for SAP, 24-2, SITA
	standard, is distributed with visualFields
tpattern	test pattern. The pattern of locations used for the perimetric test. Posible values
	are p24d2 or p10d2. At the moment, only normative values for SAP, 24-2,
	SITA standard, is distributed with visualFields
tdate	test date
ttime	test time
stype	type of subject. Values can be ctr for controls, pwg for patients with
	glaucoma, sus for suspect subjects. This is just for information to display in
	the printouts
sage	subject age. Important for the calculation of total-deviation values and probabiliby
	maps.
seye	eye tested
sbsx	estimated x-position of the blind spot in degrees of angle of vision
sbsy	estimated y-position of the blind spot in degrees of angle of vision
sfp	false positives
sfn	false negatives
sfl	fixation losses
sduration	total duration of the test

The reminder of the columns can be different things. For threshold sensitivity values, and total-deviation and pattern-deviation values, and their corresponding probability maps, they are:

L1 .. L54 .. L68 .. L76	location number. There are up to 54 locations for the 24-2, up to 68 for
	the 10-2, and 76 for the 30-2. Information about the position of the
	locations, the size of the stimulus, and the x and y coordinates in
	degrees of visual angles are specified in saplocmap (for SAP)

For statistical values of the visual-fields results (mean deviation, pattern standard deviation, and others) and their corresponding probability mapped value, they are:

msens	mean sensitivity value; or the probability mapped value
ssens	standard deviation of the sensitivity values; or the probability mapped value
mtdev	mean deviation (mean value of the total-deviation values; or the probability mapped value)
stdev	standard deviation of the total-deviation values; or the probability mapped value
mpdev	mean value of the pattern-deviation values; or the probability mapped value)
stdev	standard pattern deviation (standard deviation pattern-deviation values; or the

For visual field index (VFI) value and the corresponding probability mapped value, they are:

mvfi	visual field indes (VFI); or the probability mapped value
svfi	standard deviation of the VFI at each location; or the probability mapped value

See Also

vfsettings

Examples

# NOT RUN {
# DO NOT EXECUTE
# one can load sensitivities using loadvfcsv or loadvfxml the data so
# vf <- loadvfcsv( filename = "foo.csv", , patternMap = saplocmap$p24d2 )
# calculate total deviation values using \code{\link{visualFields}} normative values for
# SAP SITAS 24-2 (and Goldman size III stimulus)
# td <- tdval( vf )
# calculate pattern deviation values using total deviation values SAP SITAS 24-2
# pd <- tdval( td )
# OR
# pd <- tdval( tdval( vf ) )
# calculate total deviation proabiliby maps
# tdp <- tdpmap( td )
# calculate pattern deviation proabiliby maps
# pdp <- pdpmap( pd )
# }