projoint_data

Internal constructor for <code>projoint_data</code> objects. 
Used by <code>reshape_projoint</code> and <code>make_projoint_data</code> to
bundle conjoint survey labels and response data into a consistent structure.

internal

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>.

Yusaku Horiuchi

projoint

Conjoint Analysis with Reliability Correction and Visualization

projoint_data function

<dl><dt>labels</dt>
<dd>A data frame of conjoint attribute–level metadata. Must include
attribute names, attribute IDs (e.g., <code>"att1"</code>), and level IDs
(e.g., <code>"att1:lev1"</code>).</dd>
<dt>data</dt>
<dd>A data frame (typically a tibble) containing the reshaped conjoint
survey responses, one row per respondent–task–profile, with attribute columns,
<code>selected</code>, <code>agree</code>, and any covariates.</dd></dl>

Arguments

Create a projoint_data Object — projoint_data

<dl>

<dt>labels</dt>
<dd>A data frame of conjoint attribute–level metadata. Must include
attribute names, attribute IDs (e.g., <code>"att1"</code>), and level IDs
(e.g., <code>"att1:lev1"</code>).</dd>


<dt>data</dt>
<dd>A data frame (typically a tibble) containing the reshaped conjoint
survey responses, one row per respondent–task–profile, with attribute columns,
<code>selected</code>, <code>agree</code>, and any covariates.</dd>

</dl>

projoint_data: Create a projoint_data Object

Description

Usage

Value

Arguments