Description Usage Arguments Details Value References See Also Examples

Estimate the Point of Subjective Equivalence (PSE), the Just Noticeable
Difference (JND) and the related Standard Errors for a multivariate distribution by means of Delta Method.
The method applies to multivariable GLMM having a *probit* link function.
The function is based on a recursive use of `glmer`

and
`MixDelta`

1 | ```
MixTreatment(xplode.obj, datafr)
``` |

`xplode.obj` |
an object of class |

`datafr` |
the data frame fitted with the GLMM model |

The function `MixTreatment`

is based on a recursive use of
`glmer`

and `PsychDelta`

to multivariable GLMM including
continuous and factorial predictors. The same caveats of `PsychDelta`

apply (e.g., confidence interval based on normality assumption).

A list, whose lenght is equal to the levels of the factorial predictor, i.
Each cell of the list is equal to the output of `delta.psy.probit`

applied to
a multivariable model whose baseline is level i of the factorial predictor.

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

`glmer`

for Generalized Linear Mixed Models (including
random effects).`MixDelta`

for univariable model with delta method.
`pseMer`

for bootstrap-based confidence intervals.

1 2 3 4 5 6 | ```
library(lme4)
data(vibro_exp3)
formula.mod <- cbind(faster, slower) ~ speed * vibration + (1 + speed| subject)
mod <- glmer(formula = formula.mod, family = binomial(link = "probit"), data = vibro_exp3)
xplode.mod <- xplode(model = mod, name.cont = "speed", name.factor = "vibration")
MixTreatment(xplode.mod, vibro_exp3)
``` |

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