![]() Library ( tidyverse ) # ggplot, dplyr, and friends library ( haven ) # Read Stata files library ( broom ) # Convert model objects to tidy data frames library ( cregg ) # Automatically calculate frequentist conjoint AMCEs and MMs library ( survey ) # Panel-ish regression models library ( scales ) # Nicer labeling functions library ( marginaleffects ) # Calculate marginal effects library ( broom.helpers ) # Add empty reference categories to tidy model data frames library ( ggforce ) # For facet_col() library ( brms ) # The best formula-based interface to Stan library ( tidybayes ) # Manipulate Stan results in tidy ways library ( ggdist ) # Fancy distribution plots library ( patchwork ) # Combine ggplot plots # Custom ggplot theme to make pretty plots # Get the font at theme_nice % as_factor ( ) # Convert all the Stata categories to factors # Make a little lookup table for nicer feature labels variable_lookup % mutate (variable_nice = fct_inorder ( variable_nice ) ) How conjoint experiments workĬonjoint experiments are a special kind of randomized experiment where study participants are asked questions that have experimental manipulations. Finding conjoint AMCEs and marginal means Bayesianly.Subgroup differences in AMCEs and marginal means.marginal_means() with the full actual model.Marginal effects instead of coefficients.Finding conjoint AMCEs and marginal means frequentistly.AMCEs and marginal means across subgroups.Conjoint AMCEs and marginal means (finally!).Relationship between AMCEs and marginal means.Average marginal component effect (AMCE).Estimands: what quantities of interest can you get from conjoint designs?.
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