Package index • projoint

📦 Data Sets

Example data sets to get started quickly

exampleData1: Projoint Example Data Set 1: Building Conjoint with a Repeated, Flipped Task

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

out1_arranged: Example Output: Manually Rearranged Labels

exampleData1_labelled_tibble: Projoint Example Data Set 1: "Labelled Tibble"

🔧 Setup

Functions to read, clean, and structure data

read_Qualtrics(): Read and re-format a Qualtrics CSV (choice text)

read_labels(): Read and apply a reordered attribute/level mapping

reshape_projoint(): Reshape survey response data for conjoint analysis (single task set)

make_projoint_data(): Make a projoint_data object from a labelled tibble

save_labels(): Save attribute and level labels to a CSV file

set_qoi(): Set the quantities of interest (QoIs)

📊 Analysis

Core estimation methods

projoint(): Analyze a conjoint dataset with measurement-error correction

predict_tau(): Estimate intra-respondent reliability (tau) without a repeated task

🎨 Visualization

Functions to visualize profile- and choice-level results

plot(<projoint_results>): Plot method for projoint_results

plot(<projoint_tau>): Plot method for projoint_tau

🧩 S3 methods

Print and summary helpers for key objects

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

summary(<projoint_data>): Summary for projoint_data

summary(<projoint_results>): Summary method for projoint_results

summary(<projoint_tau>): Summary method for projoint_tau objects