Introduction
1
Overview
Interdisciplinary guide to conjoint analysis
Introduction
1
Overview
Dealing with data
2
Process, clean, and reshape data
Estimands
3
Causal effects: marginal means (MMs) and average marginal component effects (AMCEs)
4
Preferences: Utilities, predictions, and simulations
Causal effects
5
MMs and AMCEs with OLS
6
MMs and AMCEs with frequentist multinomial regression
7
MMs and AMCEs with Bayesian multinomial logistic regression
Preferences
8
Utilities and predictions with frequentist multinomial regression
9
Utilities and predictions with Bayesian multinomial regression
Final things
1
Overview
Introduction
1
Overview
Interdisciplinary guide to conjoint analysis
Author
Andrew Heiss
Published
December 23, 2024
2
Process, clean, and reshape data
