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A Function for Creating Item Response Theory based reliability plot based on plotly.

Source: R/ggreliability_plotly.R
ggreliability_plotly.Rd

This function will create Item Response Theory based based reliability plot with standard error using ggplot2 and plotly from objects created from mirt pack. Using ggplot2 will enable the user to modify the Item plot.

Usage

ggreliability_plotly(dataframe, model)

Arguments

dataframe

your data.

model

A mirt package fitted object.

Value

A publication quality reliability plot (dashed line). Output object is a ggplot object.

Examples

data <- tabledown::Rotter[, 11:31]
model <- mirt::mirt(data, model = 1, itemtype = '2PL')
#> 
Iteration: 1, Log-Lik: -5444.747, Max-Change: 0.56424
Iteration: 2, Log-Lik: -5374.008, Max-Change: 0.30858
Iteration: 3, Log-Lik: -5357.722, Max-Change: 0.17532
Iteration: 4, Log-Lik: -5353.406, Max-Change: 0.09162
Iteration: 5, Log-Lik: -5352.045, Max-Change: 0.06068
Iteration: 6, Log-Lik: -5351.603, Max-Change: 0.03828
Iteration: 7, Log-Lik: -5351.412, Max-Change: 0.01627
Iteration: 8, Log-Lik: -5351.383, Max-Change: 0.01187
Iteration: 9, Log-Lik: -5351.371, Max-Change: 0.00751
Iteration: 10, Log-Lik: -5351.365, Max-Change: 0.00390
Iteration: 11, Log-Lik: -5351.364, Max-Change: 0.00344
Iteration: 12, Log-Lik: -5351.363, Max-Change: 0.00026
Iteration: 13, Log-Lik: -5351.363, Max-Change: 0.00024
Iteration: 14, Log-Lik: -5351.363, Max-Change: 0.00109
Iteration: 15, Log-Lik: -5351.363, Max-Change: 0.00081
Iteration: 16, Log-Lik: -5351.363, Max-Change: 0.00031
Iteration: 17, Log-Lik: -5351.363, Max-Change: 0.00011
Iteration: 18, Log-Lik: -5351.363, Max-Change: 0.00054
Iteration: 19, Log-Lik: -5351.363, Max-Change: 0.00012
Iteration: 20, Log-Lik: -5351.363, Max-Change: 0.00035
Iteration: 21, Log-Lik: -5351.363, Max-Change: 0.00010

plot <- ggreliability_plotly(data, model)