MixPlot: Plot Individual Responses from GLMM

In MixedPsy: Statistical Tools for the Analysis of Psychophysical Data

Plot Individual Responses from GLMM

Description

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.

Usage

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

Arguments

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.

Details

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.

Value

MixPlot returns a ggplot object.

See Also

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

Examples

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)

MixedPsy documentation built on April 4, 2025, 3:50 a.m.