Description Usage Arguments Details Value Note References See Also Examples
Estimate the Point of Subjective Equivalence (PSE), the Just Noticeable Difference (JND) and the related Standard Errors for an univariate distribution by means of Delta Method.
1 | MixDelta(xplode.obj, alpha = 0.05)
|
xplode.obj |
an object of class |
alpha |
significance level of the confidence interval. Default is 0.05. |
MixDelta
estimates PSE and JND of a univariable psychometric
function (object of class "glm"
).The method only applies to univariable GLMMs
having a probit link function. Use MixTreatment
for multivariable GLMMs.
MixDelta
returns a list of length 1 including Estimate, Standard Error,
Inferior and Superior Confidence Interval of PSE and JND. Confidence Intervals
are computed as: Estimate +/- z(1-(α/2)) * Std.Error.
The function assumes that the first model coefficient is the intercept and the second is the slope. The estimate of the JND assumes a probit link function.
Moscatelli, A., Mezzetti, M., & Lacquaniti, F. (2012). Modeling psychophysical data at the population-level: The generalized linear mixed model. Journal of Vision, 12(11):26, 1-17. https://doi.org/10.1167/12.11.26
Casella, G., & Berger, R. L. (2002). Statistical inference (2nd ed.). Pacific Grove, CA: Duxbury Press
MixTreatment
for univarible and multivariable GLMM.
pseMer
for bootstrap-based confidence intervals.
xplode
objects of class xplode.obj
.
1 2 3 4 5 6 7 8 | library(lme4)
data(vibro_exp3)
formula.mod <- cbind(faster, slower) ~ speed + (1 + speed| subject)
mod <- glmer(formula = formula.mod, family = binomial(link = "probit"),
data = vibro_exp3[vibro_exp3$vibration == 0,])
define.mod <- list(pf = list(intercept = 1, slope = 2))
xplode.mod <- xplode(model = mod, name.cont = "speed", define.pf = define.mod)
pse.jnd <- MixDelta(xplode.mod)
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