md.plot.logit: Plot aggregate logit model from quick estimation of MaxDiff...

In cnchapman/choicetools: Tools for Choice Modeling, Conjoint Analysis, and MaxDiff analysis of Best-Worst Surveys

Plot aggregate logit model from quick estimation of MaxDiff utilities

Description

This gives a quick plot of results from md.quicklogit() to check whether one's data looks reasonable before running hierarchical Bayes estimation. See md.quicklogit() for details. A good alternative is a simple plot of best and worst counts, as done by plot.md.counts()

Usage

md.plot.logit(md.define, item.disguise = FALSE)

Arguments

md.define	A MaxDiff study object that contains aggregate utility estimates in an object member called $md.model.logit, as estimated by md.quicklogit() in this package.
item.disguise	Remove the item labels and number them generically. This is included to make it easy to share and show results at a conference or other audience when the underlying details are confidential.

Value

A ggplot2 object plotting the CI ranges for each item, as estimated by md.quicklogit().

cnchapman/choicetools documentation built on May 28, 2023, 9:14 a.m.