vfprogression: Visual Field (VF) Progression Analysis and Plotting Methods

Realization of published methods to analyze visual field (VF) progression. Introduction to the plotting methods (designed by author TE) for VF output visualization. A sample dataset for two eyes, each with 10 follow-ups is included. The VF analysis methods could be found in – Musch et al. (1999) <doi:10.1016/S0161-6420(99)90147-1>, Nouri-Mahdavi et at. (2012) <doi:10.1167/iovs.11-9021>, Schell et at. (2014) <doi:10.1016/j.ophtha.2014.02.021>, Aptel et al. (2015) <doi:10.1111/aos.12788>.

Version:	0.7.1
Depends:	R (≥ 2.10)
Imports:	stats, grDevices, graphics
Published:	2019-05-24
Author:	Tobias Elze, Dian Li (documentation), Eun Young Choi (QC)
Maintainer:	Dian Li <lidian at zju.edu.cn>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	vfprogression results

Documentation:

Reference manual:

vfprogression.pdf

Downloads:

Package source:	vfprogression_0.7.1.tar.gz
Windows binaries:	r-prerel: vfprogression_0.7.1.zip, r-release: vfprogression_0.7.1.zip, r-oldrel: vfprogression_0.7.1.zip
macOS binaries:	r-prerel (arm64): vfprogression_0.7.1.tgz, r-release (arm64): vfprogression_0.7.1.tgz, r-oldrel (arm64): vfprogression_0.7.1.tgz, r-prerel (x86_64): vfprogression_0.7.1.tgz, r-release (x86_64): vfprogression_0.7.1.tgz

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