linreg: Global and pointwise linear regression analyses

Description Usage Arguments Details Value References Examples

Description

Functions that compute global and pointwise linear regression analyses:

Usage

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glr(g, type = "md", testSlope = 0)

plr(vf, type = "td", testSlope = 0)

poplr(vf, type = "td", testSlope = 0, nperm = factorial(7), trunc = 1)

Arguments

g

global indices

type

type of analysis. For glr, it can be 'ms', 'ss', 'md', 'sd', 'pmd', 'psd', 'vfi', or 'gh' for mean sensitivity, standard deviation of sensitivities, mean deviation, standard deviation of total deviation values, pattern mean deviation, pattern standard deviation, VFI, and general height, respectively. For plr and poplr, it can be 's', 'td', or 'pd' for sensitivities, total deviation values, or pattern deviation values, respectively

testSlope

slope, or slopes, to test as null hypothesis. Default is 0. if a single value, then the same null hypothesis is used for all locations. If a vector of values, then (for plr and poplr) each location of the visual field will have a different null hypothesis. The length of testSlope must be 1 or equal to the number of locations to be used in the PLR or PoPLR analysis

vf

visual fields sensitivity data

nperm

number of permutations. If the number of visits is 7 or less, then nperm = factorial(nrow(vf)). For series greater than 8 visits, default is factorial(7). For series up to 7 visits, it is the factorial of the number of visits (with less than 7 visits, the number of possible permutations is small and results can be unreliable. For instance, for 5 visits, the number of possible permutations is only 120.)

trunc

truncation value for the Truncated Product Method (see reference)

Details

Value

References

N. O'Leary, B. C. Chauhan, and P. H. Artes. Visual field progression in glaucoma: estimating the overall significance of deterioration with permutation analyses of pointwise linear regression (PoPLR). Investigative Ophthalmology and Visual Science, 53, 2012

Examples

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vf <- vffilter(vfpwgRetest24d2, id == 1) # select one patient
res <- glr(getgl(vf)) # linear regression with global indices
res <- plr(vf)   # pointwise linear regression (PLR) with TD values
res <- poplr(vf) # Permutation of PLR with TD values

visualFields documentation built on Aug. 17, 2021, 1:06 a.m.