# Conjoint Analysis with Reliability Correction and Visualization

## Documentation for package ‘projoint’ version 1.0.6

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

exampleData1 | Projoint Example Data Set 1: Building Conjoint with a Repeated, Flipped Task
exampleData1_labelled_tibble | Projoint Example Data Set 1: "Labelled Tibble"
exampleData2 | Projoint Example Data Set 2: Building Conjoint with a Repeated, Non-Flipped Task
exampleData3 | Projoint Example Data Set 3: Building Conjoint with No Repeated Task
make_projoint_data | Make a 'projoint_data' object from a labelled tibble
out1_arranged | Example Output: Manually Rearranged Labels
plot.projoint_results | Plot method for 'projoint_results'
plot.projoint_tau | Plot method for 'projoint_tau'
predict_tau | Estimate intra-respondent reliability (tau) without a repeated task
print.projoint_data | Print a projoint_data object
print.projoint_results | Print method for projoint_results
print.projoint_tau | Print method for projoint_tau objects
projoint | Analyze a conjoint dataset with measurement-error correction
read_labels | Read and apply a reordered attribute/level mapping
read_Qualtrics | Read and re-format a Qualtrics CSV (choice text)
reshape_projoint | Reshape survey response data for conjoint analysis (single task set)
save_labels | Save attribute and level labels to a CSV file
set_qoi | Set the quantities of interest (QoIs)
summary.projoint_data | Summary for 'projoint_data'
summary.projoint_results | Summary method for 'projoint_results'
summary.projoint_tau | Summary method for projoint_tau objects