Introduction | What Amelia Does | Assumptions | Algorithm | Analysis | References

Data | Multiple Imputation | Saving imputed datasets | Combining multiple calls to amelia() | Screen output | Parallel Imputation | Improving Imputations via Transformations | Ordinal | Nominal | Natural log | Square root | Logistic | Identification Variables | Time Series, or Time Series Cross Sectional Data | Lags and leads | Including Prior Information | Ridge priors for high missingness, Small samples, or large correlations | Observation-level priors | Logical bounds | Post-imputations Transformations | Analysis Models | The amelia class | References

Introduction | Data | Nonparametric bounds | Bayesian parametric model

Quantity of interest | Implementation | References

Introduction | A Selection Bias Approach to Sensitivity Analysis | An Illustration

References

Loading AmeliaView | Loading data into AmeliaView | Variable Dashboard | Amelia Options | Numerical options | Add Distributional Prior | Add Range Prior | Imputing and checking diagnostics | Diagnostics Dialog | Sessions

Overimpute | Overdispersed Starting Values | Time-series Plots | Missingness maps | References

factiv: Noncompliance and Instrumental Variables in Factorial Experiments | What are factorial effects? | What is noncompliance? | Complier effects in factorial experiments | Estimating complier effects with factiv | Covariate profiling | References