MixPlot: Plot Individual Responses from GLMM
In MixedPsy: Statistical Tools for the Analysis of Psychophysical Data

Description Usage Arguments Details Value See Also Examples

Plot response curve for each individual in a population sample, given a GLMM with one continuous predictor and one (optional) factorial predictor. If the factorial predictor is specified, the response is plotted separately for each individual and each predictor level.

1	MixPlot(xplode.obj, facet_by = NULL, showData = TRUE)

`xplode.obj`	an object of class `xplode`.
`facet_by`	optional. A string specifying the name of the faceting variable (either the participant identification or the factorial predictor).
`showData`	logical, defines if proportion of binomial responses for each stimulus level are presented. Default is TRUE.

If the model includes only a continuous predictor, the figure consist of a single panel, and each individual's response is assigned a different color. If a factorial predictor is included in the model, the faceting variable can be either the participant identification or the factorial predictor. By default, each panel shows an individual's response, different levels of the factorial predictor are coded by color.

MixPlot returns a ggplot object.

xplode for objects of class xplode. ggplot2 for creating data visualizations. PsychPlot for plotting a a psychometric function from a GLM.

library(lme4)
mod.multi <- glmer(cbind(faster, slower) ~ speed * vibration + (1 + speed| subject), 
family = binomial(link = "probit"), data = vibro_exp3)
xplode.multi <- xplode(model = mod.multi, name.cont = "speed", name.factor = "vibration")

MixPlot(xplode.multi)
#alternative visualization
MixPlot(xplode.multi, facet_by = "vibration", showData = FALSE)