Design and Analysis for Factorial Experiments
Decompose the difference between the pAMCEs
Estimating the population AMCE using a design-based approach
Diagnose modeling assumptions for the model-based approach
Estimating the population AMCE using a model-based approach
Plot decomposition of the difference between pAMCEs
Plotting diagnostic checks
Plotting the estimated population AMCEs
Summarizing the estimated population AMCEs
Computing weights for estimating the population AMCE using a design-ba...
Provides design-based and model-based estimators for the population average marginal component effects in general factorial experiments, including conjoint analysis. The package also implements a series of recommendations offered in de la Cuesta, Egami, and Imai (2022) <doi:10.1017/pan.2020.40>, and Egami and Imai (2019) <doi:10.1080/01621459.2018.1476246>.