Conjoint Analysis with Reliability Correction and Visualization
Make a projoint_data object from a labelled tibble
Organize data for estimation (internal helper)
Internal Estimation Function
Plot choice-level marginal means (MMs) (helper)
Plot method for projoint_results
Plot method for projoint_tau
Estimate intra-respondent reliability (tau) without a repeated task
Print a projoint_data object
Print method for projoint_results
Print method for projoint_tau objects
Create a projoint_data Object
Estimate subgroup differences (internal)
Estimate profile- or choice-level effects (internal)
Create a projoint_qoi Object
Create a projoint_results Object
Analyze a conjoint dataset with measurement-error correction
Read and apply a reordered attribute/level mapping
Read and re-format a Qualtrics CSV (choice text)
Reshape survey response data for conjoint analysis (single task set)
Save attribute and level labels to a CSV file
Set the quantities of interest (QoIs)
Summary for projoint_data
Summary method for projoint_results
Summary method for projoint_tau objects
Provides tools for analyzing data generated from conjoint survey experiments, a method widely used in the social sciences for studying multidimensional preferences. The package implements estimation of marginal means (MMs) and average marginal component effects (AMCEs), with corrections for measurement error. Methods include profile-level and choice-level estimators, bias correction using intra-respondent reliability (IRR), and visualization utilities. For details on the methodology, see Clayton, Horiuchi, Kaufman, King, and Komisarchik (2025) <https://gking.harvard.edu/conjointE>.