category_boundaries: Get the category boundary based on an glmer fit and model...
In kleinschmidt/phonetic-sup-unsup: Supervised/unsupervised adaptation analysis
Description
Usage
Arguments
Value
Description
Works by computing predictions at each level of bvotCond and supCond, for
vot predictor of 0 (to get y intercept) and 1 (to get VOT slope). Then finds
the x intercept, and adjusts for how VOT is scaled and shifted to return the
actual VOT value where the boundary is.
Usage
1
category_boundaries(dat_mod, fit, trials_prop = 5/6)
Arguments
dat_mod
Model input data (data.frame with at least columns for
bvotCond, bvotCond.s, supervised (numeric supCond predictor), and supCond).
fit
Fitted glmer model object
trials_prop
(Default: 5/6) which point in the experiment to estimate
the category boundary at.
Value
data.frame with columns bvotCond, supCond, and boundary_vot
kleinschmidt/phonetic-sup-unsup documentation built on May 20, 2019, 12:33 p.m.
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Description Usage Arguments Value
Description
Works by computing predictions at each level of bvotCond and supCond, for vot predictor of 0 (to get y intercept) and 1 (to get VOT slope). Then finds the x intercept, and adjusts for how VOT is scaled and shifted to return the actual VOT value where the boundary is.
Usage
1 | category_boundaries(dat_mod, fit, trials_prop = 5/6)
|
Arguments
dat_mod |
Model input data (data.frame with at least columns for bvotCond, bvotCond.s, supervised (numeric supCond predictor), and supCond). |
fit |
Fitted glmer model object |
trials_prop |
(Default: 5/6) which point in the experiment to estimate the category boundary at. |
Value
data.frame with columns bvotCond, supCond, and boundary_vot
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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