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(): Reads in a CSV of reordered attributes and levels, and applies it to a projoint_data object.

reshape_projoint(): Reshapes survey response data for conjoint analysis

make_projoint_data(): Make a projoint_data object using a labelled tibble (data frame)

save_labels(): Save the attributes and levels, and their order, from a conjoint data set, to a CSV file.

set_qoi(): Set the quantities of interest

📊 Analysis

Core estimation methods

predict_tau(): Estimate tau when there is no repeated task.

projoint(): Analyze a Conjoint Data Set with Measurement Error Correction

🎨 Visualization

Functions to visualize profile- and choice-level results

plot(<projoint_results>): Plot Marginal Means (MMs) or AMCEs from projoint Results

plot(<projoint_tau>): Visualize the results of the extrapolation method for estimating tau.